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UNIVERSITY OF OULU P .O. B 00 F I -90014 UNIVERSITY OF OULU FINLAND
A C T A U N I V E R S I T A T I S O U L U E N S I S
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SCIENTIAE RERUM NATURALIUM
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EDITOR IN CHIEF
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ISBN 978-952-62-0718-6 (Paperback)ISBN 978-952-62-0719-3 (PDF)ISSN 0355-3213 (Print)ISSN 1796-2226 (Online)
U N I V E R S I TAT I S O U L U E N S I SACTAC
TECHNICA
U N I V E R S I TAT I S O U L U E N S I SACTAC
TECHNICA
OULU 2014
C 516
Pasi Karinkanta
DRY FINE GRINDING OF NORWAY SPRUCE (PICEA ABIES) WOOD IN IMPACT-BASED FINE GRINDING MILLS
UNIVERSITY OF OULU GRADUATE SCHOOL;UNIVERSITY OF OULU,FACULTY OF TECHNOLOGY
C 516
ACTA
Pasi Karinkanta
C516etukansi.kesken.fm Page 1 Tuesday, December 2, 2014 11:22 AM
A C T A U N I V E R S I T A T I S O U L U E N S I SC Te c h n i c a 5 1 6
PASI KARINKANTA
DRY FINE GRINDING OF NORWAY SPRUCE (PICEA ABIES) WOOD IN IMPACT-BASED FINE GRINDING MILLS
Academic dissertation to be presented with the assent ofthe Doctoral Training Committee of Technology andNatural Sciences of the University of Oulu for publicdefence in the Arina auditorium (TA105), Linnanmaa, on23 January 2015, at 12 noon
UNIVERSITY OF OULU, OULU 2014
Copyright © 2014Acta Univ. Oul. C 516, 2014
Supervised byProfessor Jouko NiinimäkiDoctor Mirja Illikainen
Reviewed byDoctor Junyong ZhuDoctor Michaela Eder
ISBN 978-952-62-0718-6 (Paperback)ISBN 978-952-62-0719-3 (PDF)
ISSN 0355-3213 (Printed)ISSN 1796-2226 (Online)
Cover DesignRaimo Ahonen
JUVENES PRINTTAMPERE 2014
OpponentProfessor Kari Heiskanen
Karinkanta, Pasi, Dry fine grinding of Norway spruce (Picea abies) wood inimpact-based fine grinding mills. University of Oulu Graduate School; University of Oulu, Faculty of TechnologyActa Univ. Oul. C 516, 2014University of Oulu, P.O. Box 8000, FI-90014 University of Oulu, Finland
Abstract
Wood powders are used in numerous applications such as thermoplastics and filters, and a lot ofresearch effort has been put into developing novel ways of utilising them. The mechanicalprocessing of wood powders, especially at particle sizes below 100 µm, has been reported inseveral studies, but they lack information on the effect of fine grinding conditions on the particlemorphology and cellulose crystallinity, both of which are important parameters in the furtherprocessing of wood powders and in their various applications. This makes it very difficult todesign and optimise fine grinding processes with different applications in mind. The aim of thisthesis was to study the dry fine grinding of wood in several impact-based fine grinding mills inorder to find out their effect on the properties of the wood and to study the energy required for themechanical processing of the resulting powders.
The effect of the main operational parameters on the properties of dried Norway spruce woodand the energy consumption was studied using three impact-based fine grinding mills that werecapable of pulverising the wood down to a median particle size of less than 25 µm. It was foundthat the impact events occurring in media mills can be used for the production of very fine woodpowders with lower cellulose crystallinity and rounder shaped particles having more uniformshape distribution than powders pulverised to a similar size range by means of impact events innon-media mills. A practical estimate was obtained for the minimum specific energy consumptionin fine grinding in mills involving grinding media that could be utilised as a target for optimisation.Impact-based media milling under cryogenic conditions can be used to obtain different Norwayspruce wood powders from those produced under ambient grinding conditions, i.e. without thefreezing effect of nitrogen liquid. The energy efficiency of fine grinding can be enhanced bychoosing cryogenic rather than ambient conditions. The moisture content of the wood has greaterinfluence on the size and shape of the particles when milling is accomplished under ambientconditions. Torrefaction can reduce the energy consumption in impact-based media mills formedian particle sizes over 17.4 µm (± 0.2 µm), while the shape and cellulose crystallinity of theparticles are not significantly affected by torrefaction pretreatment as a function of energyconsumption.
Keywords: aspect ratio, cellulose crystallinity, comminution, dry fine grinding, energyconsumption, Norway spruce, particle size, processing, wood flour, wood powder
Karinkanta, Pasi, Metsäkuusen (Picea abies) kuivahienojauhatus iskuihinperustuvilla hienojauhatusmyllyillä. Oulun yliopiston tutkijakoulu; Oulun yliopisto, Teknillinen tiedekuntaActa Univ. Oul. C 516, 2014Oulun yliopisto, PL 8000, 90014 Oulun yliopisto
Tiivistelmä
Puujauheita käytetään laajalti erilaisissa sovelluksissa, kuten esimerkiksi biokomposiiteissa jasuodattimissa. Tämän lisäksi on olemassa paljon tutkimustietoa siitä, kuinka puujauheita voitai-siin hyödyntää laajemminkin. Puu voidaan mekaanisesti prosessoida alle 100 µm:n kokoluok-kaan, mutta yksityiskohtaista tietoa kuivahienojauhatuksen olosuhteiden vaikutuksesta jauhei-den morfologiaan ja selluloosan kiteisyyteen ei ole saatavilla. Puujauheen morfologialla ja sellu-loosan kiteisyydellä on kuitenkin merkittävä vaikutus sovelluksia ja jatkojalostusta ajatellen.Puun kuivahienojauhatuksen tiedon puute hankaloittaa merkittävästi prosessin suunnittelua jaoptimointia erilaisia sovelluksia varten. Tämän väitöskirjan tavoitteena on selvittää iskuihinperustuvien hienojauhimien vaikutukset puun ominaisuuksiin ja tutkia mekaanisen prosessoin-nin energiatehokkuutta hienojauhatuksessa.
Tutkimuksessa selvitettiin kolmen erilaisen iskuun perustuvan hienojauhatusmyllyn pääasial-listen operointiparametrien vaikutusta kuivatun metsäkuusen ominaisuuksiin ja energiankulutuk-seen. Jokaisella hienojauhimella onnistuttiin tuottamaan puujauhoja, joiden mediaanikoko olialle 25 µm. Iskuihin perustuvalla jauhinkappalemyllyllä saatiin tuotettua puujauhoa, jonka sellu-loosan kiteisyys on alhaisempi ja partikkelimuodot pyöreämpiä verrattuna samankokoisiin puu-jauhoihin, jotka on tuotettu iskuihin perustuvilla jauhinkappaleettomilla hienojauhatusmyllyillä.Työssä saatiin käytännöllinen arvio kuivatun metsäkuusen hienojauhatuksen minimienergianku-lutukselle iskuihin perustuville jauhinkappalemyllyille, mitä voidaan käyttää kyseisten mylly-tyyppien optimoinnin tavoitteena. Työssä havaittiin lisäksi, että kryogeenisiä jauhatusolosuhtei-ta käyttämällä voidaan tuottaa erilaisia puujauhoja verrattuna puujauhoihin, jotka prosessoidaanilman nestetyppijäädytystä, kun jauhatus suoritetaan iskuihin perustuvalla jauhinkappalemyllyl-lä. Ilman nestetyppijäädytystä puun kosteuspitoisuudella on merkittävämpi vaikutus puujauhojenominaisuuksiin kuin kryogeenisissä olosuhteissa jauhetuilla. Kryogeenisillä jauhatusolosuhteillavoidaan parantaa myös jauhatuksen energiatehokkuutta. Torrefioinnilla voidaan vähentää hieno-jauhatuksen energiankulutusta iskuihin perustuvilla jauhinkappalemyllyillä, kun tavoitekoonmediaani on yli 17,4 µm (± 0,2 µm). Torrefioinnilla ei ole vaikutusta selluloosan kiteisyyteen taipartikkeleiden muotoon energiankulutuksen funktiona.
Asiasanat: aspektisuhde, energiankulutus, hienonnus, kuivahienojauhatus, metsäkuusi,partikkelikoko, prosessointi, puujauho, selluloosan kiteisyys
Dedicated to my beloved brother, Marko Karinkanta
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Acknowledgements
The work reported in this thesis was carried out at the University of Oulu Fibre
and Particle Engineering Laboratory during the years 2008–2014 in co-operation
with the Graduate School in Chemical Engineering (GSCE) and UPM. Funding
from the KAUTE Foundation, Emil Aaltonen Foundation, Tauno Tönning
Foundation, Jenny and Antti Wihuri Foundation, Finnish Cultural Foundation and
Riitta and Jorma J. Takanen Foundation is greatly appreciated.
My sincere thanks go to Professor Jouko Niinimäki for giving me an
opportunity to work on a new and interesting technology and for supervising my
thesis, and to Dr. Mirja Illikainen, for her efforts and personal guidance. In
addition, thanks are also due to Mrs. Tarja Sinkko, who coordinated the co-
operation with UPM.
I highly appreciate the reviewing work done by Dr. Michaela Eder and Dr.
Junyong Zhu, and I would also like to express my gratitude to Mr. Malcolm Hicks
for revising the English language of this thesis.
I would like to thank my fellow researchers Nina Pykäläinen, Sami Turunen,
Lauri Talikka and Jouko Lehto at the UPM for discussion and conversation
sessions that were very valuable for me, and many thanks also go to my
colleagues at the University of Oulu, especially Katja Ohenoja, Kalle
Kemppainen, Henrikki Liimatainen, Terhi Suopajärvi, Olli Taikina-aho and Antti
Haapala for their assistance in the research and their interesting conversations. I
would also like to thank to my fellow researchers in the Graduate School in
Chemical Engineering (GSCE), especially Riina Salmimies, Jari Heinonen, Juho
Lehmusto, Kalle Salonen and Jerzy Jasielec. The laboratory assistants Jarno
Karvonen and Jani Österlund deserve especial thanks for their assistance with the
experiments and laboratory work.
Finally, I would like to thank my wife Paula for keeping me going and being
on my side, and also my sons Niko and Oliver. My warm thanks go to my
relatives and siblings for their help and for believing in me, especially Heidi,
Kristiina, Markku, Pekka and Kirsti. I would also express my very special thanks
to my mother Seija and brother Marko, both of whom passed away early in 2012
– this would not have been possible without them. Lastly, I would like to thank all
my friends, especially Simo Ikonen, Lassi Urpilainen, Juho Syrjä and Antti Korpi.
Oulu, 2014 Pasi Karinkanta
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11
List of abbreviations and symbols
CS Coefficients of classifier speed in the empirical models for air
classifier milling
CML Compound middle lamella of the wood cell wall
EW Earlywood
FSP Fibre saturation point
High GP Jet milling experiments in which the average overpressure of the
grinding air was approximately 10 bar
I(long) Coefficients of the rotational direction of a rotor towards a long
edge in the empirical models for air classifier milling
I(short) Coefficients of the rotational direction of a rotor towards a short
edge in the empirical models for air classifier milling
L Direction towards the longitudinal axis of wood
Low GP Jet milling experiments in which the average overpressure of the
grinding air was approximately 6 bar
LW Latewood
MS Coefficients of mill speed in the empirical models for air classifier
milling
MC Moisture content (%)
MFA Microfibrillar angle
ML Middle lamella of the wood cell wall
P Primary layer of the wood cell wall
R Direction towards the radial axis of wood
S1, S2, S3 Secondary wall layers 1, 2 and 3 in the cell wall of tracheids
T Direction towards the tangential axis of wood
WR Wood ray
XRD X-ray diffraction
A End-to-end amplitude of the oscillation movement in oscillatory ball
milling (m)
AR10 Aspect ratio corresponding to a value of 10% in the cumulative
projected area-based aspect ratio distribution
AR50 Median aspect ratio in the projected area-based aspect ratio
distribution
AR90 Aspect ratio corresponding to a value of 90% in the cumulative
projected area-based aspect ratio distribution
12
CrI Crystallinity index according to Segal et al. (1959) (%)
dS,X Sieve aperture with X% material pass (m)
d10 Particle diameter corresponding to a value of 10% in the cumulative
volume-based particle size distribution according to the laser
diffraction method (µm)
d50 Median particle size in the volume-based particle size distribution
according to the laser diffraction method (µm)
d90 Particle diameter corresponding to a value of 90% in the cumulative
volume-based particle size distribution according to the laser
diffraction method (µm)
Ek Estimated kinetic energy of the grinding ball during one end-wall
collision period (J)
ET Estimated total kinetic energy of the grinding ball during oscillatory
ball milling, also referred to as the total available impact energy (J)
f Oscillation frequency in oscillatory ball milling (Hz)
Mair Molar mass of air (g mol-1)
m Mass of the feed (g)
mball Mass of the grinding ball (g)
mP,dry Dry mass of the product in opposed jet milling experiments (g)
ML Mass loss due to torrefaction (%)
n Molar mass of air (mol)
p Pressure (bar)
pC Pressure of compressed grinding air (bar)
pUC Pressure of grinding air before compression (bar)
Q2 Cross-validated R2
R2 Coefficient of determination
R2(Adj.) Coefficient of determination adjusted for degrees of freedom
Rg Gas constant = 8.314 J mol-1 K´-1
SEC Specific electrical energy consumption of the system (J g-1)
SECJET Specific energy consumption based on the energy needed for
compression of the grinding air in jet milling (J g-1)
SECOSC Specific energy consumption based on the estimated total available
impact energy of the grinding ball in oscillatory ball milling (J g-1)
T Temperature of air (K)
t Milling time (s)
V Volume of air (m3)
VC Volume of compressed grinding air (m3)
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VUC Volume of grinding air before compression (m3)
Δ* Width of particle size distribution
ΔAR Width of aspect ratio distribution
ΔWP Work done by a piston in isothermal and quasistatic compression of
an ideal gas (J)
ρ Density of air (g m-3)
σ Stress (MPa)
σC Crushing strength or peak stress in compression (MPa)
σu Ultimate strength (MPa)
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15
List of original publications
This thesis is based on the following publications, which are referred throughout
the text by their Roman numerals:
I Karinkanta P, Illikainen M, Niinimäki J (2012) Pulverisation of dried and screened Norway spruce (Picea abies) sawdust in an air classifier mill. Biomass and Bioenergy 44: 96–106.
II Karinkanta P, Illikainen M, Niinimäki J (2014) Effect of different impact events in fine grinding mills on the development of the physical properties of dried Norway spruce (Picea abies) wood in pulverisation. Powder Technology 253: 352–359.
III Karinkanta P, Illikainen M, Niinimäki J (2013) Impact-based pulverisation of dried and screened Norway spruce (Picea abies) sawdust in an oscillatory ball mill. Powder Technology 233: 286–294.
IV Karinkanta P, Illikainen M, Niinimäki J (2013) Effect of grinding conditions in oscillatory ball milling on the morphology of particles and cellulose crystallinity of Norway spruce (Picea abies). Holzforschung 67(3): 277–283.
V Karinkanta P, Illikainen M, Niinimäki J (2014) Effect of mild torrefaction on pulverization of Norway spruce (Picea abies) by oscillatory ball milling: particle morphology and cellulose crystallinity. Holzforschung 68(3):337–343.
All the manuscripts were written by the primary author of this thesis, whose main
responsibilities were experimental design, data analysing, modelling and
reporting of the results. The co-authors participated in the design, analyses and
writing of the publications.
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17
Contents
Abstract
Tiivistelmä
Acknowledgements 9 List of abbreviations and symbols 11 List of original publications 15 Contents 17 1 Introduction 19
1.1 Background ............................................................................................. 19 1.2 Outline of the thesis ................................................................................ 20
2 Present understanding 23 2.1 Norway spruce wood .............................................................................. 23
2.1.1 Chemical composition and microstructure ................................... 23 2.1.2 Mechanical properties and breakage behaviour ........................... 27
2.2 Dry fine grinding ..................................................................................... 32 2.2.1 Stressing conditions and material properties ................................ 33 2.2.2 Single and double impacts ............................................................ 36 2.2.3 Fine grinding techniques .............................................................. 38
2.3 Impact milling of wood and other lignocelluloses .................................. 40 2.3.1 Mills involving single impacts ..................................................... 42 2.3.2 Mills involving double impacts .................................................... 44 2.3.3 Pretreatments and milling conditions ........................................... 45
3 Aims of the study 49 4 Materials and methods 51
4.1 Raw material ........................................................................................... 51 4.2 Pretreatments prior to fine grinding ........................................................ 51 4.3 Fine grinding experiments....................................................................... 52 4.4 Wood powder sampling and analyses ..................................................... 55
4.4.1 Sampling ....................................................................................... 55 4.4.2 Analyses performed on diluted wood powder samples ................ 55 4.4.3 Analyses performed on dry wood powder samples ...................... 56
4.5 Modelling ................................................................................................ 57 5 Results and discussion 59
5.1 Fine grinding of dried Norway spruce wood in impact mills .................. 59 5.1.1 Air classifier mill .......................................................................... 59 5.1.2 Fluidised bed opposed jet mill ...................................................... 65
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5.1.3 Oscillatory ball mill ...................................................................... 69 5.2 Comparison of impact milling techniques ............................................... 76 5.3 Effects of pretreatments and milling conditions on the properties
of Norway spruce wood in impact-based media milling ......................... 80 5.3.1 Drying and cryogenic grinding conditions ................................... 80 5.3.2 Mild torrefaction ........................................................................... 84
6 Conclusions 89 References 93 Original Publications 107
19
1 Introduction
1.1 Background
Wood is a renewable, abundant, non-food and carbon dioxide-neutral raw
material that can be used to replace non-renewable materials. Wood is widely
used as a fuel, construction material or raw material in cellulose and
lignocellulose-based products. Today there are various applications in which
wood is used in powdered form, such as thermoplastics and filters, and a lot of
research effort has been put into developing novel ways of utilising wood
powders (Kobayashi et al. 2008, Mori 2009).
The particle morphology and cellulose crystallinity of wood are crucial
factors in various processing steps and applications to value chains of different
kinds. These affect the digestibility of wood (Millett et al. 1975, 1976, 1979,
Fukazawa et al. 1982, Rivers & Emert 1987, Mooney et al. 1998, Mansfield et al.
1999, Chang VS & Holtzapple 2000, Chandra et al. 2007, Dasari & Benson 2007,
Zhu L et al. 2008, 2010, Kumar et al. 2009, Hendriks & Zeeman 2009, Zhu JY et
al. 2009a, Zhang M et al. 2012a, 2012b, Leu & Zhu JY 2013, Agarwal et al.
2013), and particle morphology is also important in its thermochemical
conversion (Reuther et al. 1985, Adams et al. 1988, Thunman et al. 2002, Lu et
al. 2010). When wood powder is employed as a filler or reinforcement material in
composites its particle morphology has an important role in the mechanical
properties of those composites (Zaini et al. 1996, Takatani et al. 2000, Stark &
Rowlands 2003, Khalil et al. 2006, Chen HC et al. 2006, Migneault et al. 2008,
2009, Bouafif et al. 2009, Renner et al. 2010, Kociszewski et al. 2012). Particle
morphology and cellulose crystallinity can be modified by mechanical treatment.
Since this mechanical treatment consumes a lot of energy (see Table 1), the profits
obtained through improved processing or from the final product need to exceed
the expense of the treatment for the latter to be economically feasible.
Although the fine grinding of wood has been studied in various ways, see
Millett et al. (1979), Fukazawa et al. (1982) and Agarwal et al. (2013), the main
subject under study have been the application of wood powder, not the
mechanical processing itself. Thus our present understanding of the process does
not extend to the effects of fine grinding conditions on the particle morphology
and cellulose crystallinity, which makes it very difficult to design and optimise
processes for the fine grinding of wood for different applications. The general aim
20
of this thesis is to obtain a knowledge of how the physical properties of Norway
spruce (Picea abies) wood develop during dry fine grinding with impact-based
mills under a variety of grinding conditions, and what influence those conditions
have on energy consumption.
1.2 Outline of the thesis
This thesis is organised into six chapters. Chapter 1 presents a brief background to
the topic. Chapter 2 summarises our present understanding of the structure and
properties of Norway spruce wood and the milling of wood, especially dry fine
grinding. The aims of the present research are presented in Chapter 3 and the
materials and methods used for testing the hypotheses in Chapter 4. The results
are summarised and discussed in Chapter 5 and the conclusions are presented in
Chapter 6.
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Table 1. Energy requirements of different milling techniques in the dry grinding of
wood to a product size of less than 2 mm. Pilot-scale milling experiments are marked
(pilot). The energy requirement can be specified either for the milling equipment (mill)
or for the whole process (process).
Milling
technique
Raw material Feed size Product size Energy
requirement
Reference
Rotating knife
mill
Unspecified hardwood
(MC* = 4%–7%)
dS,100 =
22.40 mm
dS,100 = 1.60 mm 130.0 kWh t-1
(mill)
Gadoche &
López 1989
Hammer mill Unspecified hardwood
(MC* = 4%–7%)
dS,100 =
22.40 mm
dS,100 = 1.60 mm 130.0 kWh t-1
(mill)
Gadoche &
López 1989
Hammer mill
(pilot)
Poplar chips
(MC = 10%–15%)
dS,50 = 8a
mm
dS,99 = 1 mm 89.1 kWh t-1
(process)
Esteban &
Carrasco 2006
Hammer mill
(pilot)
Pine chips
(MC = 10%–15%)
dS,44 = 8a
mm
dS,99 = 1 mm 113.2 kWh t-1
(process)
Esteban &
Carrasco 2006
Hammer mill
(pilot)
Hybrid poplar wood chips
(MC* approximately 60%)
- dS,46 = 1a mm 102 kWh t-1
(process)
Schell &
Harwood 1994
Vibration mill Norway spruce
(MC* = 11%)
d = 22 mm d = 150 µm 800 kWh t-1
(process)
Kobayashi et al.
2008
Szego mill
(pilot)
Dry aspen wood chips
(MC = 13.5%)
dS,80 = 1.4
mm
dS,80 = 870 µm 310a kWh t-1
(mill)
Gravelsins 1998
Szego mill
(pilot)
Moist aspen wood chips
(MC = 45%–53%)
dS,80 = 1.4
mmc
dS,80 = 1.54 mm 200a kWh t-1
(mill)
Gravelsins 1998
Szego mill
(pilot)
Dry jack pine sawdust
(MC= 5.8%)
dS,80 = 2.2
mm
dS,80 = 970 µm 78 kWh t-1
(mill)
Gravelsins 1998
Szego mill
(pilot)
Moist jack pine sawdust
(MC= 37.4%)
dS,80 = 2.5
mm
dS,80 = 1.76 mm 100a kWh t-1
(mill)
Gravelsins 1998
Disc mill
(pilot)
Hybrid poplar wood chips
(MC* approximately 60%)
- dS,59 = 1.2a mm 122 kWh t-1
(process)
Schell &
Harwood 1994
Ultracentri-
fugal mill Spruce Sieved to
(2–4) mm
d50 = 197 µm 750 kWh t-1
(mill)
Repellin et al.
2010
Ultracentri-
fugal mill
Torrefied spruce Sieved to
(2–4) mm
d50 = 59 µm 90a kWh t-1
(mill)
Repellin et al.
2010
dS,X = sieve aperture with X% material pass, d50 = median particle diameter obtained by the laser
diffraction technique, d = particle diameter without no precise information provided in the source, MC =
moisture content in relation to total mass, MC* = moisture content with the relation to total mass or dry
mass not specified , a value read off from a graph and therefore not precise, b measuring method not
mentioned, and c obtained by sieving of dry wood chips
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2 Present understanding
2.1 Norway spruce wood
Among the various wood species, Norway spruce (Picea abies [L.] H. Karst) was
chosen for this work because its properties and structure are well known and it is
an important natural resource in Germany, Austria, Slovakia, the Czech Republic,
Romania and the Scandinavian countries (Surmiński 2007). This section focuses
on the structure and mechanical properties of mature Norway spruce wood,
whereas the differences between trees grown in different surroundings or under
different nutritional conditions are not considered in detail.
2.1.1 Chemical composition and microstructure
The chemical composition of Norway spruce wood includes primarily cellulose
(> 39%) and lignin (< 36%) but also hemicelluloses and pectins (< 28%)
(Bertraud & Holmbom 2004, Surmiński 2007). Its microstructure comprises
mainly longitudinal cells, known as tracheids (up to 90%), the remainder being
mainly the cells forming wood rays (Hejnowicz 2007). An illustration of a cross-
section of a Norway spruce tree is provided in Fig. 1. Norway spruce tracheids are
elongated cells and have sometimes been described as hollow tubes of length
varying between 1.0 mm and 7.6 mm (Buksnowitz et al. 2010). Tracheid length
varies depending on characteristics such as the age of the tree and the radial
distance from the pith (Herman et al. 1998, Sarén et al. 2001, Buksnowitz et al.
2010). The cross-section of a tracheid is approximately rectangular, including an
open space known as the lumen (Sarén et al. 2001, 2006, Derome et al. 2012).
The length of the side of a tracheid seen in cross-section is less than 50 µm
(Havimo et al. 2008), and the cell wall thickness can vary between 1 µm and 9
µm (Havimo et al. 2008, Derome et al. 2012). The average cell wall thickness is
2.1 µm in earlywood and 3.9 µm in latewood (Havimo et al. 2008). The latewood
occupies from 2% to 30% of the total growth ring thickness (Hejnowicz 2007).
The walls of the tracheids contain bordered pits between 11 µm and 22 µm in
diameter (Hejnowicz 2007). These are mainly located in the radial walls of the
earlywood and are abundant at the overlapping ends of the tracheids (Hejnowicz
2007).
24
Fig. 1. Illustration of a cross-section of a tree. L denotes longitudinal axis, R radial axis
and T tangential axis.
Structure of tracheids
Tracheids are composed of a compound middle lamella (CML) and secondary cell
wall layers S1, S2 and S3, where the S2 layer comprises 80% of the entire width of
the secondary wall (Hejnowicz 2007). The CML, which contains a relatively high
amount of lignin but low amounts of cellulose and hemicelluloses (Jääskeläinen
& Sundqvist 2007: 50–51), can be separated into the middle lamella (ML) and
primary wall layer (P) (Jääskeläinen & Sundqvist 2007: 50–51). The ML binds
the tracheids to each other (Jääskeläinen & Sundqvist 2007: 50–51). The cell wall
of a tracheid is made up of a primary wall layer and the secondary wall layers,
where P is the outermost layer and S3 the innermost (Jääskeläinen & Sundqvist
2007: 50–51). The wall layers differ from others by virtue of the orientation of the
cellulose fibrils, as shown in Fig. 2. The angle between the cellulose fibrils and
the longitudinal axis is called the microfibrillar angle (MFA). Earlywood
tracheids exhibit an asymmetrical MFA distribution with values between -20° and
90° (Peura et al. 2008a). There are certain differences in MFA between the cell
wall layers, and also within a single cell wall layer, as shown in the cell wall
models (see Fig. 2). The average MFA tends to be between 20° and 35° near the
pith and decreases to below 20° towards the bark (Sarén et al. 2001, 2006, Peura
et al. 2008a, 2008b). It also tends to decrease within a single growth ring when
moving from the earlywood towards the latewood (Sarén et al. 2006, Lanvermann
et al. 2013). Likewise the relative distribution of cellulose, hemicelluloses and
lignin is known to vary between the cell wall layers (Panshin & de Zeeuw 1980:
106–107). According to Fengel and Stoll (1973), the thicknesses of the cell wall
layers lie in the range of 0.04–0.16 µm for CML, 0.12–0.71 µm for S1, 0.91–5.60
µm for S2 and 0.01–0.36 µm for S3.
25
Fig. 2. Cell wall models for Norway spruce: a) earlywood tracheid, b) latewood
tracheid from the mature wood and c) latewood tracheid from the juvenile wood, after
Brändström (2002). Black lines represent the orientation of cellulose fibrils in the cell
wall. Reproduced by permission of Jonas Brändström.
Cell wall structure of tracheids
In the cell walls of tracheids the cellulose molecules form the helically wound
reinforcing fibrils whereas the hemicelluloses and lignin provide a gluing and
stiffening matrix (Booker & Sell 1998). Besides the orientation of microfibrils in
a cell wall of wood also hemicelluloses and lignin can form orientated molecular
structures (Stevanic & Salmén 2009, Salmén et al. 2012). An elementary cellulose
fibril of native wood consists of 10 000 glucose units of length around 5.2 µm,
arranged so that they form a well-ordered crystalline structure or less ordered
amorphous mass (Jääskeläinen & Sundqvist 2007: 67–71, Fengel & Wegener
1989: 66–105). In Norway spruce earlywood 52% (± 3%) of the cellulose by
mass is in crystalline form (Andersson et al. 2004) and 30% (± 4%) of the wood
by mass is composed of crystalline cellulose (Andersson et al. 2004), or an even
lower proportion near the pith (Andersson et al. 2003). Jakob et al. (1995) report
that an elementary cellulose fibril in the S2 layer of Norway spruce wood is
uniformly 2.5 nm (± 0.2 nm) in diameter and is made up entirely of cellulose
crystallites. The crystallites oriented along the fibre axis in the S2 layer have been
reported to be 11 nm in length (Jakob et al. 1995). On the other hand, the average
length and diameter of cellulose crystallites in the S2 layer of Norway spruce
wood have been reported by Pirkkalainen et al. (2012) to be 33 nm (± 1 nm) and
26
2.7 nm (± 0.1 nm), respectively, values that are fairly close to those reported by
Andersson et al. (2003) and Peura et al. (2008a). Peura et al. (2008a) concluded
that the length of the cellulose crystallites can vary from 19.2 nm to 28.4 nm.
Some authors have suggested that there are no systematic variations in crystallite
dimensions as a function of the number of annual rings from the pith (Andersson
et al. 2003, Pirkkalainen et al. 2012). In contrast to this, Peura et al. (2007,
2008a) reported that there are small differences in the thickness and length of
crystallites between juvenile and mature wood. Individual elementary cellulose
fibrils in the S2 layer of Norway spruce wood together with some hemicellulose
glucomannan form cellulose fibril aggregates called macrofibrils with sides
ranging in length from 5 nm to 25 nm, averaging 15–16 nm, assuming a square
cross-section (Fahlén 2005). The centres of the elementary fibrils have been
estimated to be 4 nm apart (Jakob et al. 1996). The macrofibrils are surrounded
by lignin and hemicelluloses known as xylan and glucomannan (Fahlén 2005:
10). An illustration of an elementary cellulose fibril and macrofibrils in the S2
wall layer of Norway spruce wood is presented in Fig. 3.
Fig. 3. Illustrations of an elementary cellulose fibril and macrofibrils of various sizes in
the S2 cell wall layer of Norway spruce.
27
2.1.2 Mechanical properties and breakage behaviour
In mechanical terms, Norway spruce wood is a viscoelastic material (Havimo
2010), the viscous behaviour causes internal friction which converts any
mechanical energy imposed on it into heat (Eskelinen et al. 1982, Havimo 2009).
It also exhibits linear stress-strain behaviour when exposed to low magnitude
stresses, but when exposed to stresses of magnitudes close to its ultimate strength,
i.e. its breaking strength, non-linear stress-strain behaviour prevails (Dahl 2009).
The mechanical properties of Norway spruce wood vary depending on the loading
direction (Dahl 2009) and on structural variations such as the presence or absence
of early- and latewood and differences in MFA (Reiterer et al. 1999, Reiterer et
al. 2001a, Eder et al. 2008, 2009). Wood can be generally simplified as
orthotropic, i.e. by considering the mechanical differences in its radial,
longitudinal and tangential directions.
Fracture mechanics and breakage behaviour
In fracture mechanics of wood it is typical to distinguish three modes of loading
that lead to different forms of failure behaviour (Fig. 4). Frühmann et al. (2002)
have shown that pure tension failure can be more favoured energetically than pure
shear failure in Norway spruce wood. One reason for this may be energy losses
caused by friction between the fractured surfaces brought about by shear loads
(Frühmann et al. 2002). On the other hand, mixed mode loading (modes I and II)
can lead to failure that is energetically more favourable than pure tension failure
(Tschegg et al. 2001), since in this type the initial crack propagation always takes
place along the longitudinal axis irrespective of the starting notch or the degree of
mixity (Jernkvist 2001).
28
Fig. 4. Illustrations of different loading modes in fracture mechanics: a) mode I, tensile
stress leads to tension failure, b) mode II leading to in-plane or forward shear failure,
and c) mode III, leading to out-of-plane or transverse shear failure.
The breakage of wood can occur due to the separation of cells from each other by
peeling (intercellular failure), in which case the crack propagates mainly via the
CML (Boatright & Garrett 1983, Ashby et al. 1985). It is also possible that
breakage can occur within the cell wall layer (intracellular failure) (Boatright &
Garrett 1983, Ashby et al. 1985), leading to either intrawall failure, i.e. failure
within the secondary cell wall, or transwall failure, in which the fracture path
intersects the cell wall (Côté & Hanna 1983). Tensile stressing experiments with
Norway spruce wood have shown that fracturing mainly takes place in an
intercellular or intrawall manner when the stresses are perpendicular to the
longitudinal axis (Persson 2000: 46–51, Dill-Langer et al. 2002, Frühmann et al.
2003a, Wittel et al. 2005, Keunecke et al. 2007, Lanvermann et al. 2014),
whereas transwall failure takes place when there is tension along the longitudinal
axis (Bodner et al. 1997, 1998, Frühmann et al. 2003b, Müller et al. 2003). When
tension is perpendicular to the longitudinal axis stresses in excess of 1 MPa but
significantly less than 10 MPa are needed for breakage (Dill-Langer et al. 2002,
Wittel et al. 2005, Dahl 2009, Lanvermann et al. 2014), whereas if the tension is
parallel to the longitudinal axis over 30 MPa is needed for breakage of the wood
(Dahl 2009) or of a single tracheid (Eder et al. 2009). The stressed area in
experiments with wood samples is typically calculated as the whole area of the
cross-section in which the failure takes place. This results in lower ultimate
strengths by comparison with calculations that consider only the cross-section
area of the cell wall, so that the open space represented by the lumen is excluded.
When the latter calculation method is used local longitudinal ultimate tensile
strengths may be obtained that are significantly over 200 MPa (Burgert et al.
2003, 2005, Eder et al. 2008, 2009), i.e. strengths of this magnitude need to be
exceeded locally to cause transwall failure in single tracheids. There is no
29
information about the tensile loading of single tracheids in a tangential or radial
direction as their dimensions are too small for the tensile testing equipment (Eder
et al. 2013). In the case of shear experiments, stresses over 0.8 MPa but less than
9 MPa are sufficient to cause in-plane shear failures in different loading directions
(Dahl 2009). Dahl (2009) reported that in the case of samples where the shear
loading was initially directed to cause crack propagation across the longitudinal
axis the crack did not propagate in this direction but along the longitudinal axis.
Thus the shear stresses reported by Dahl (2009) do not consider the ultimate shear
strength required for transwall failure in Norway spruce wood. By considering
only the cross-section area of the cell wall in the calculations Gindl & Teischinger
(2002) estimated the shear strength of the cell wall parallel to the longitudinal
axis to be 27.5 MPa, i.e. this figure needs to be exceeded locally for intrawall
shear failure.
Compression failure
During compression the breakage of wood takes place due to tension and shear
failures but is accompanied by plastic deformation of its cells, i.e. buckling and
collapsing (Dumail & Salmén 1996, Poulsen et al. 1997, Persson 2000: 46–51,
Reiterer & Stanzl-Tschegg 2001b, Gindl and Teischinger 2002, De Magistris &
Salmén 2005, Benabou 2008, 2010). Typical stress-strain curves for Norway
spruce wood in the case of radial, tangential and longitudinal compression are
illustrated in Fig. 5. The stress-strain curves shown in Fig. 5 have some general
characteristics that have been distinguished for wood under compression (see
Gibson and Ashby 1988: 283–290, 309–311). At low stresses linear-elastic
deformation prevails, but when the stress increases to come close to the peak
stress plastic deformation and failures take place (Gibson and Ashby 1988: 283–
290, 309–311). The plateaux of the stress-strain curves correspond to a
progressive crushing of the wood, involving plastic deformation, during which a
significant increase in density is observed due to collapsing of the cells, allowing
the denser wood to resist compression, as can be observed in the stress-strain
curve in the form of strain toughening (Gibson and Ashby 1988: 283–290, 309–
311). The increase in strength due to densification by compression nevertheless
remains lower than could be expected from the increased density alone
(Blomberg et al. 2005). The mechanical strength involved in compression is
typically reported as taking the form of crushing strength, or peak stress, as
illustrated in Fig. 5 for the longitudinal, radial and tangential compression curves.
30
The crushing strengths of spruce wood are listed in Table 2, where it can be seen
that the crushing strength is much higher in a longitudinal direction than in any
other direction and that in addition to density, the compression rate and moisture
content have a significant influence on the crushing strength.
Apart from single static loading, cyclic compressive loading in tangential and
radial directions with low applied stresses (0.5–0.7 MPa) can cause local
collapsing of the earlywood and is particularly concentrated on the surface of the
wood that is in contact with the compressive force (Salmi et al. 2009, 2012a,
2012b). When considering cyclic compression in a longitudinal direction, Clorius
et al. (2000) reported that the fatigue life in wood is highly dependent on the
loading frequency, in that the total time to failure decreases with increasing
frequency. Visual failure was observed in the form of either a fine-meshed pattern
of compression zones scattered over a larger section or else localised failure
(Clorius et al. 2000). The fine-meshed failures increased with decreasing loading
frequency and increasing moisture content (Clorius et al. 2000).
Fig. 5. Illustration of a typical stress-strain curves for Norway spruce wood under
tangential, radial and longitudinal compression.
31
Table 2. Crushing strength of spruce wood under single compression. Values
including an asterisk (*) were read off from a graph and are therefore not precise.
Otherwise crushing strength is reported in terms of mean values. Bolded values apply
to Norway spruce wood, whereas Widehammar (2004) did not specify the species of
wood.
Loading
direction
MC Density
(g cm-3)
Compression rate Crushing strength/Peak
stress σC (MPa)
Reference
Longitudinal
‘Oven-dry’ low/medium/high 90* / 130* / 160* (Widehammar 2004)
8% 0.40 5.0 mm min-1 47.4±2.4 (Benabou 2008)
12% 0.41 0.3 mm min-1 45 (Poulsen et al. 1997)
12% 0.4*–0.9* 0.5 mm min-1 30*–110*
(Gindl & Teischinger
2002)
12–13% 0.40–
0.43
5.0 mm min-1 49* (Reiterer & Stanzl-
Tschegg 2001b)
10–15% 0.42–
0.48
(1.2 / 12000 /
180000) mm/min-1
40.2a / 51.8a / 56.0a (Eisenacher et al.
2013)
‘Fiber S’ low/medium/high 30* / 39* / 56* (Widehammar 2004)
‘Fully S’ low/medium/high 26* / 37* / 52* (Widehammar 2004)
Radial
‘Oven-dry’ low/medium/high 9* / 10* / 15* (Widehammar 2004)
12–13 0.40–
0.43
5.0 mm min-1 3.5* (Reiterer & Stanzl-
Tschegg 2001b)
‘Fiber S’ low/medium/high 3.6* / 5.0* / 7.5* (Widehammar 2004)
‘Fiber S’ 0.38–
0.48
0.0025 s-1/ 25 s-1 2.4* / 3.8* (Uhmeier & Salmén
1996)
‘Fully S’ low/medium/high 2.8* / 6.0* / 11* (Widehammar 2004)
‘Fully S’ 0.38–
0.48
0.0025 s-1/ 25 s-1 2.0* / 3.8* (Uhmeier & Salmén
1996)
Tangential
‘Oven-dry’ low/medium/high 19* / 24* / 30* (Widehammar 2004)
‘Fiber S’ low/medium/high 4.5* / 7.5* / 10* (Widehammar 2004)
‘Fully S’ low/medium/high 4.0* / 11* / 16* (Widehammar 2004)
‘Fiber S’ means fibre-saturated conditions in the wood, which in the case of Norway spruce is 30–34%
on a dry basis and 23–25% on a wet basis. ‘Fully S’ means a condition of the wood in which it carries as
much water as possible. Low/medium/high represent different strain rates in the split Hopkinson pressure
bar (SHPB) experiments, although the strain rate cannot be prescribed accurately due to the testing
technique. a Lateral dilation of the samples was constrained during compression.
32
Influence of moisture content
Moisture content has a significant influence on the mechanical and fracture
properties of wood (Gerhards 1982, Eskelinen et al. 1982, Salmén 1982,
Bengtsson 2000, Vasic & Stanzl-Tschegg 2007). When the moisture of wood
increases beyond the fibre saturation point (FSP), which varies between 30% and
34% on a dry basis and between 23% and 25% on a wet basis, the cell walls cease
swelling because they are totally saturated and the timber strength no longer
varies with moisture content (Bosshard 1974: 214, Berry & Roderick 2005). The
energy loss due internal friction is significantly higher for water-saturated
Norway spruce wood than for air-dried samples, even at temperatures below 30°C
(Eskelinen et al. 1982).
Moisture content also has a significant effect on the glass transition point of
amorphous cellulose, hemicelluloses and lignin (Jääskeläinen & Sundqvist 2007:
127–130). The polymer changes its physical state from a glass-like brittle material
to a rubber-like viscous material when the temperature increases beyond the glass
transition point (Salmén 1982, Jääskeläinen & Sundqvist 2007: 127–130). This
point occurs around 200°C in hemicelluloses, amorphous cellulose and lignin in a
dry state (Salmén 1982, Jääskeläinen & Sundqvist 2007: 127–130), but when the
moisture content of the wood increases hydrophilic hemicelluloses can be
softened at room temperatures (approximately 20°C) (Salmén 1982, 2004). A
higher moisture content will also lower the glass transition point of lignin and
amorphous cellulose, but these do not soften at room temperature (Salmén 2004,
Jääskeläinen & Sundqvist 2007: 127–130). In mechanical pulping the stressing
frequency also influences the softening temperature of the wood (Salmén et al.
1999).
2.2 Dry fine grinding
In mineral processing, grinding is the last stage in mechanical size reduction and
is performed using mills of various kinds after the crushing stage (Bernotat &
Schönert 2000, Wills 2006). It is sometimes referred as milling and is also
commonly separated into two processes, wet and dry grinding. According to
Lowrison (1974: 103–108) wet grinding typically means the grinding of a
material containing about 50% of liquid by volume in the uncombined state. The
present work will consider only dry grinding processes. Jankovic (2003) separates
grinding as used in mineral processing into four subcategories based on the
33
particle size of the product: conventional grinding, regrinding, fine grinding and
very fine grinding. Other subcategories to be found in the literature include
coarse, superfine and ultrafine grinding (Lowrison 1974: 60, 115, Orumwense &
Forssberg 1992, Jankovic 2003, Wang & Forssberg 2007, Zhao et al. 2009,
Barakat et al. 2013). There are some differences between authors, however, in the
product size ranges implied by these terms, so that fine grinding, for example, has
been classified as reduction to a particle size range of 125–1000 µm by Lowrison
(1974: 60), 100–1000 µm by Hukki (Lowrison 1974: 115), 200–600 µm by
Taggart (Lowrison 1974: 115) and 10–30 µm by Jankovic (2003). Barakat et al.
(2013) categorised the fine grinding of lignocellulosic biomasses to product size
range less than 100 µm, which is used as the targeted median particle size of the
product in this work.
2.2.1 Stressing conditions and material properties
To describe the material breakage achieved by different forms of size reduction
equipment it is convenient to evaluate our knowledge of this breakage in terms of
stressing conditions (Rumpf 1990: 103–114). This would make it possible to
evaluate the breakage mechanism involved when changing the size reduction
equipment, the physical conditions or the nature of the material. Peukert and
Vogel (2001) developed a processing model which distinguishes between material
properties and stressing conditions. Material function includes the information
about breakage rate and breakage function, which are in turn dependent on the
stressing conditions and stressing history that the particle has experienced
(Peukert 2004). The stressing conditions as such are considered in the role of a
machine function which comprises the type of size reduction equipment and the
conditions of operation (Peukert and Vogel 2001).
Material function
When considering a material function it must be noted that there are various
differences between the mechanical properties of materials. Even a single particle
may contain regions with different ultimate strengths, and crack propagation
during loading will probably take place in a region where the ultimate strength is
the same or lower than the stress applied (Fig. 6). Crack propagation fatigue can
take place even when the stress is insignificant, and this can weaken the material
so that the maximum stress or energy that is required for failure in the next
34
stressing event is lowered (Scott-Emuakpor 2007, Campbell 2012). Breakage of
the material does not necessarily happen at the strain rate equivalent to the
ultimate strength (Fig. 7a), as it only takes place when the strain energy density is
sufficient for the breakage (Fig. 7b) (ASM International 2003: 205, Jenkins &
Khanna 2005: 209–211). Chemical and physical treatments can be used prior to
mechanical size reduction to weaken the particle structure.
Machine function
A machine function involves three main parameters: stress intensity, stress
number and stress type (Peukert and Vogel 2001, Peukert 2003, 2004). According
to Peukert (2013), stress intensity should properly be termed stress energy, the
energy transferred to the particle upon stressing. The stress number, or frequency,
then indicates how many stress events take place during a certain period of time
in the course of mechanical size reduction (Bernotat & Schönert 2000, Peukert
and Vogel 2001, Peukert 2003, 2004). The third parameter, stress type, refers to
the type of applied stress (Bernotat & Schönert 2000, Peukert and Vogel 2001,
Peukert 2003, 2004). Compressive stresses are applied by compression or impact,
which can cause breakdown of the initial particles to smaller ones (Wills 2006,
Ennis et al. 2008), while shear stresses are typically applied by abrasive or cutting
techniques (Ennis et al. 2008, Lowrison 1974: 255–260). Other machine
functions include physical conditions such as the processing temperature and
pressure, which can have a significant influence on the breakage behaviour of the
particles.
35
Fig. 6. Illustration of a heterogeneous particle breakage under compressive loading at
varying compressive stresses. It is assumed that the stress is maintained for as long
as is needed for breakage to occur independently of the strain.
36
Fig. 7. Illustrations of different stress-strain curves a) with breaking points and
ultimate strengths and b) the blue (Fig 7a) stress-strain curve under different
stressing conditions.
Mill and product related stressing models
Kwade (2003) make a distinction between mill and product related stressing
models, in which the stressing conditions are considered from different points of
view. In the mill related stressing model the mechanical size reduction behaviour
of a mill is characterised by the type of the stress events, the number of such
events produced in the mill per unit time and the stress energy, which is the
magnitude of the energy that can be supplied to the product particle by the mill in
each stress event (Kwade 2003). In the product related stressing model, the result
in terms of the mechanical size reduction is determined by the type of stress, the
absolute number of stress events acting on one feed particle and the magnitude of
the specific energy or specific force during each stress event (Kwade 2003).
2.2.2 Single and double impacts
Single-particle breakage tests are used to study material behaviour under
conditions of slow compression and impact (Rumpf 1973, 1990: 108–114,
Tavares 2007), whereas abrasive failure has its own branch of science, called
tribology (see ASM International 2003: 259–266). Single-particle breakage tests
involve three main loading methods that result in outcomes of different kinds:
single impact, double impact and slow compression (Tavares 2007). In the first
case the particle is loaded by impact with one contact point (Fig. 8a), in the
second there are two or more contact points (Fig. 8b) and in slow compression the
particle is compressed between two planes (Fig. 8c). Special kinds of impact
testers can also be used in relation to mechanical pulping, e.g. where movement is
37
restricted at one end of the particle and the impacting device hits the other end
(Fig. 8d) (Eskelinen et al. 1982, Marton & Eskelinen 1982, Berg 2001). In this
case the directions of the forces applied to the particle during impact are similar to
the directions of those applied in shear failure (see Section 2.1.2), so that this
impact type will be referred to as shearing impact in the present work. Single-
particle breakage tests have been used to obtain knowledge about material
breakage behaviour under different loading conditions which can be used to
predict milling behaviour (Vogel & Peukert 2002, 2003, 2004, 2005, Meier et al.
2008, 2009). Stressing conditions can also be utilised directly in milling, for
example the mathematical expression for stressing conditions in stirred media
milling evaluated by Kwade et al. (1996) is nowadays being used in many studies
aimed at the optimisation of stirred media milling.
Fig. 8. Illustrations of different stress types: a) single impact, b) double impact, c) slow
compression and d) shearing impact. In the figure vPARTICLE is the particle velocity, vBALL
the grinding ball velocity, ω1 the angular velocity of the roll 1, ω2 the angular velocity
of roll 2 and vHAMMER the velocity of the impacting hammer.
Single particle tests have been used to obtain knowledge in relation to wood
construction and mechanical pulping. The crushing strength of wood is
significantly higher when it is exposed to a single or double impact than in typical
compression tests (Reid & Peng 1997, Pierre et al. 2013). With double impacts,
for instance, the longitudinal crushing strength of Norway spruce wood increases
approximately from 50 MPa to 70 MPa when the impact speed is increased from
0.001 m s-1 to 3.0 m s-1 (Neumann et al. 2011). Pierre et al. (2013) have reported
that fibre and fully saturated spruce (Picea excelsea) and poplar (Populus
euramericana) exhibit less fractured zones and a lower crushing strength than air-
dried samples when imposed to double impacts at a speed of 1.7 m s-1. As in
double impact tests, the impact speed in the case of single impacts increases the
crushing strength, but this effect has been found to be even more marked when
the impact is imposed across the grain rather than along the grain (Reid & Peng
1997). The energy losses in a single impact are higher than in typical compression
38
tests (Reid & Peng 1997). Some of the kinetic energy carried by the specimens is
converted to thermal energy and the work needed for the inelastic deformation
during the impact event, but some is transferred back due to rebounding (Reid &
Peng 1997). The deformation mechanism is more localised in single impact cases
than in typical compression tests (Reid & Peng 1997), and disintegration of the
specimen takes place near the targeted surface when the impact is along the grain,
whereas when it is perpendicular to the grain the deformation propagates into the
undeformed part of the specimen leaving the characteristic mushroom profile in
the deformed part (Reid & Peng 1997). Shearing impact studies consider only the
specimen orientations that cause fractures along the grain, because these are the
most closely related to the behaviour of wood in mechanical pulping (Eskelinen et
al. 1982, Marton & Eskelinen 1982, Berg 2001). Eskelinen et al. (1982)
concluded that there is no significant difference in impact energy with respect to
the direction of the fracture. The fracturing energy of Norway spruce wood in the
case of radial shearing impacts can be up to four times larger than that in pure
cleavage (Marton & Eskelinen 1982). Fracturing energy in shearing impact can
also be affected by the impact velocity (Berg 2001).
2.2.3 Fine grinding techniques
Yokoyama & Inoue (2007) classified fine grinding mills into five groups: impact
mills, ball media mills, air jet mills, roller mills and those of some other type. The
mills classified in this scheme as impact mills could more conveniently be named
rotor impact mills, as in the definition proposed by Nied (2007). In rotor impact
mills the size reduction is achieved by single impacts, where the kinetic or impact
energy being applied through the rotary movement of rotors (Nied 2007). Rotor
impact mills with integrated classifiers are frequently referred to as classifier
mills and can be used for producing the finest material of all the types of rotor
impact mills, whereas typical hammer mills are used for the production of coarser
material (Nied 2007). Classifiers are used to control the residence time
distribution of the particle inside the milling zone, which correlates with the
number of stress events (Peukert & Vogel 2001). Ball media mills are mills in
which grinding media such as balls or beads are driven by movement of the mill
casing or by an agitator (Yokoyama & Inoue 2007). These mills involve single
impacts in which the grinding balls collide with particles, and also double impacts
in which particles are caught between colliding grinding balls or between
grinding balls and the mill casing. There are generally no restrictions on the use
39
of non-spherical grinding media in these mills, which is a good reason why for
referring to them as media mills or grinding media mills, as preferred by Ennis et
al. (2008), Bernotat & Schönert (2000) and Orumwense & Forssberg (1992). An
air jet mill is a fluid energy mill, or jet mill, that uses high velocity jets of air to
impart energy to particles for size reduction (Chamayou & Dodds 2007). Besides
air, nitrogen gas and steam can also be used as the fluid in such mills (Camayou
& Dodds 2007). Jet mills can be further categorised as spiral, opposed, oval
chamber and target jet mills (Camayou & Dodds 2007, Ennis et al. 2008).
Yokoyama & Inoue (2007) have classified spiral and oval chamber jet mills as
attrition type jet mills. Spiral jet mills are also known as pancake mills (Camayou
& Dodds 2007). Fluidised bed opposed jet mills are ones in which air jets are
used to provide high-energy single impacts between particles in a fluidised bed
(Chamayou & Dodds 2007). Here the kinetic energy of the grinding air can be
evaluated from the grinding pressure, which has a significant influence on the
particle breakage mechanism (De Vegt 2007, Palaniandy et al. 2008, Palaniandy
& Azizli 2009). Jet mills are typically employed in the last stage of the dry fine
grinding process, to obtain the finest particles (Camayou & Dodds 2007,
Yokoyama & Inoue 2007). Roller mills can be divided into mills that use a roller
tumbling on a table or in a vessel (roller tumbling type) and those in which the
feed is ground between cylindrical rolls (roll type) (Yokoyama & Inoue 2007).
Roller mills with smooth roll profiles can be used to apply a fine grinding
technique based on slow compression. The “mills of other types” include those
which cannot be classified as rotor impact mills, grinding media mills, jet mills or
roller mills, including those in which cutting tools such as knives, shears, saws
and spikes are employed (Lowrison 1974: 255–260). Disc refiners or disc mills
are the ones that are most commonly used for refining wood and cellulose, i.e. in
mechanical pulping (Sundholm 1999, Tienvieri et al. 1999, Zhu JY 2011). In
these a rotor provides the mechanical energy needed for size reduction, as in rotor
impact mills, but due to their specific breakage mechanism designed to cause
defibration and the fibrillation of fibres (Salmén et al. 1999), they are classified as
“other mills” in the present scheme. Apart from disc refiners, grinding wheels
operating under varying physical conditions are also used for mechanical pulping
(Liimatainen et al. 1999, Sundholm 1999). Since the disc refiners and grinding
wheels used in mechanical pulping have been optimised for the production of
long fibres, their potential for fine grinding is poorly known. A summary of the
classification of fine grinding mills is presented in Table 3.
40
Table 3. Classification of fine grinding mills based on suggestions by Orumwense &
Forssberg (1992) and Yokoyama & Inoue (2007).
Category Technique Mill types/models
Media mills
Case driven Tumbling type, vibration type, planetary type, centrifugal fluidised-
bed type
Agitator driven Tower type, agitation vessel type, tubular type, annular type
Non-media mills
Rotor impact mills High-speed rotation disc type, hammer type, axial flow type, annular
type
Jet mills Target collision type, opposed jet type, attrition type
Roller mills Roller tumbling type, roll type
Other mills Cutting type, grinding wheel type, disc refiners, mortar and pestle
2.3 Impact milling of wood and other lignocelluloses
Impact milling is preferred for the mechanical size reduction of viscoelastic
materials, and there are in principal three impact milling techniques that can be
used for fine grinding purposes: opposed jet mills, high-speed rotor impact mills,
and grinding media mills operated in the impacting mode. The impact events
involved in these techniques are illustrated in Fig. 9.
Fig. 9. Schematic illustration of the impact events involved in a) an opposed jet mill, b)
a high-speed rotor impact mill, and c) an oscillatory ball mill, which is one kind of
vibration mill. The mills are not illustrated to scale with respect to size. Paper II,
published by permission of Elsevier.
One way of distinguishing the breakage mechanisms in milling is to consider the
developments in particle size, shape and cellulose crystallinity that occur during
milling, all of which can be attributed to the mechanical properties of the wood.
Changes in particle size, shape and cellulose crystallinity in Norway spruce wood
subjected to different impact loading intensities are listed in Table 4 in relation to
41
breakage behaviour (see Section 2.1.2). Intensity I in Table 4 represents loading
with stresses that are unable to cause fracturing in any direction by means of a
single stressing event. Intensity II represents a single loading situation in Norway
spruce wood in which interwall and intrawall failures can take place but transwall
failures do not occur. Cracks propagate by means of the energetically most
favoured path, which is along the grain, leaving the particles rather elongated in
shape. The breakage behaviour of the wood particles at Intensity II is rather
similar to the Class I breakage in the classification suggested by Leu & Zhu JY
(2013). Intensity III can cause severe intracellular- and intercellular damage in
early- and latewood independently of the loading direction, which leads to less
elongated shapes than with Intensity II. Intensity IV represents an impact which is
sufficient for the amorphisation of cellulose. According to Vincent (1990), the
theoretical strength of crystalline cellulose is 25 GPa, which is many magnitudes
higher than the stresses needed for transwall failures in tracheids (see Burgert et
al. 2003, 2005, Eder et al. 2008, 2009). The breakage behaviour of wood particles
at Intensities III and IV is rather similar to Class II breakage in the classification
suggested by Leu & Zhu JY (2013). As the stressed area during particle size
reduction may decrease as the particle size decreases, possibly resulting in higher
local stress, the occurrence of Intensities I–IV in milling is influenced by the
particle size range.
42
Table 4. Possible breakage behaviour due to differences in ultimate strength in
Norway spruce wood when exposed to a single impact of different intensities, and its
influence on the size, shape and relative degree of cellulose crystallinity.
Impact intensity Breakage behaviour Changes in size, shape and cellulose crystallinity
I
(No failures) - No breakage
- Fatigues are possible
- No changes
II
(Intercellular and
intrawall failures)
- Fractures depend on the
orientation of the wood
- Intercellular and intrawall
failures in tracheids
- No transwall failures in
tracheids
- Fatigues
- Particle size decreases but tracheids can remain
1–7 mm in size in a longitudinal direction
- Shape changes but tracheids can remain
elongated
- No changes in relative degree of cellulose
crystallinity
III
(Transwall
failures)
- Fractures independent of the
orientation of the wood
- Intracellular and intercellular
failures in tracheids
- Fatigues
- Particle size decreases
- Shape changes
- No changes in relative degree of cellulose
crystallinity
IV
(Amorphisation
of cellulose)
- Fractures independent of the
orientation of the wood
- Intracellular and intercellular
failures in tracheids
- Amorphisation of cellulose
- Fatigues
- Particle size decreases
- Shape changes
- Relative degree of cellulose crystallinity decreases
2.3.1 Mills involving single impacts
Rotor impact milling
Rotor impact mills can be used to grind wood to a median particle size well over
100 µm (Himmel et al. 1985, Gadoche & López 1989, Schell & Harwood 1994,
Paulrud et al. 2002, Esteban & Carrasco 2006, Zhu JY et al. 2009a, Repellin et al.
2010). Integrated sieves or classifiers are used in rotor impact milling to control
the fineness of the product (Nied 2007), but Schell & Harwood (1994) report that
these are not recommended by hammer mill vendors for the milling of moist
wood chips due to low production rates, excessive heat build-up, screen blinding
43
and equipment damage. Due to these problems in the processing of moist
lignocelluloses, hammer mills are recommended only for the size reduction of
lignocelluloses of a moisture content up to 10–15% on a wet basis (Kratky &
Jirout 2011).
Rotor impact milled wood particles are considered to be more cylinder-like
than spherical in shape (Zhu et al. 2009a). Paulrud et al. (2002) have shown that
the size and shape of the wood particles are affected by the type of rotor impact
mill, but more distinct differences in the properties of wood powders are evident
when rotor impact milled wood is compared with cutting milled wood. Rotor
impact milled wood particles are more elongated than cutting milled particles
(Paulrud et al. 2002), but less elongated than those milled with a disc refiner with
or without steam preheating (Schell & Harwood 1994).
There is no information on whether rotor impact milling can provide
sufficient stress intensities to cause a decrease in the relative degree of cellulose
crystallinity, nor is it known whether wood can be ground to a median particle
size below 100 µm, which would involve significant destruction of the cell walls.
Paper I in the present thesis investigates the dry fine grinding of Norway spruce
wood with a high-speed rotor impact mill equipped with an integrated air
classifier and considers the effect of the rotor and classifier speeds on the
properties of the wood powders and specific energy consumption during the
processing. Rotor speed is associated with the energy and intensity of the single
impacts, whereas it is the classifier that controls the time spent in the milling
zone, i.e. the number of impact events. The higher this number, the finer the
product will be if the impact energy is sufficient to cause breakage.
Opposed jet milling
It has been shown for wheat straw that opposed jet milling can be used to produce
very fine particles without any significant decrease in cellulose crystallinity (Silva
et al. 2012). Significant differences in the degree of cellulose crystallinity were
observed between jet milled and grinding media milled samples when the median
particle size of the wheat straw was less than 100 µm (Silva et al. 2012).
There is no information on how opposed jet milling influences the physical
properties of dry wood, especially when ground to a median particle size below
100 µm. This was investigated in Paper II using a fluidised opposed jet mill with
an integrated classifier and varying the grinding pressure in order to obtain
44
different kinetic energies in the impacts and the classifier speed in order to alter
the number of stress events.
2.3.2 Mills involving double impacts
Grinding media milling
By comparison with non-media mills, media mills are known for their ability to
cause efficient destruction of the cell walls, leading to disappearance of the
fibrous structure in the wood (Fukazawa et al. 1982, Maurer & Fengel 1992,
Mikushina et al. 2003, Agarwal et al. 2013). According to Mikushina et al. (2003)
the fibrous structure of air-dried aspen sawdust is destroyed more rapidly in
planetary ball milling than in vibration or tumbling ball milling, where the latter is
the slowest technique for this purpose. Besides efficient destruction of the fibrous
structure, media mills are well known for their ability to reduce the cellulose
crystallinity of the particles in order to obtain total amorphisation of the cellulose
when milling wood and other lignocellulosic substances with a low moisture
content (Pew & Weyna 1962, Millett et al. 1979, Rivers & Emert 1987, Hon
1987, Maurer & Fengel 1992, Stubičar et al. 1998, Kobayashi et al. 2007, da
Silva et al. 2010, Zhang Q et al. 2011, Silva et al. 2012). Some authors have
reported that a low moisture content in the wood is extremely important when it is
necessary to reduce the relative degree of crystallinity of cellulose in grinding
media milling (Millett et al. 1976, Kobayashi et al. 2007). Grinding media
milling can also influence the macromolecular structure of the wood components,
which can be seen as an increase in the water-soluble oligomer content, the
formation of mechanoradicals and reductions in the degree of polymerisation of
cellulose and lignin (Chang H et al. 1975, Hon & Glasser 1979, Hon 1987,
Mikushina et al. 2002, Ikeda et al. 2002, Guerra et al. 2006). Mechanoradicals are
formed on account of the cleavage of covalent bonds in lignin and cellulose (Hon
1987, Guerra et al. 2006).
Kobayashi et al. (2008) used vibration milling to reduce Norway spruce
wood to a median particle size of 24 µm, producing rounded broken fibres with
smooth surfaces and a significant decrease in the relative degree of cellulose
crystallinity. According to Schwanninger et al. (2004) the decrease in cellulose
crystallinity achieved during the vibration milling of Norway spruce wood is
mainly due to the mechanical treatment, whereas temperature and chemical
45
effects are of only minor importance. The cell corners and CML of Norway
spruce wood are the most resistant elements in vibration milling, while in the
secondary cell wall layer it is the S1 layer that is particularly sensitive and is
loosened at an early stage, whereas the S2 layer is split into lamellae of varying
diameters from 10 nm to 500 nm (Maurer & Fengel 1992). Maurer & Fengel
(1992) observed the presence of globular particles in powdered Norway spruce
wood that tended to aggregate during vibration milling and increased in number
with the prolongation of milling. In view of the proposal put forward by Nichols
et al. (2002), the term “agglomeration” is used rather than “aggregation” for an
assemblage of powder particles in this work. This agglomeration of globular
particles may be the reason why Kobayashi et al. (2008) found that a prolongation
of vibration milling from 30 min to 120 min increased the median particle size of
ground Norway spruce wood from 30 µm to 45 µm.
The agglomeration that takes place in Norway spruce wood during vibration
milling means that there is a certain median particle size range that imposes
limitations on particle size reduction. This has not been confirmed, however, and
it is not clear whether higher stress energies will help to reduce the particle size
any further or will merely intensify the agglomeration. This was investigated in
Paper III, where dried Norway spruce wood was pulverised with a simple
vibration mill in which double impacts played an important role. The stress
energy was varied by changing the mass of the grinding ball or its oscillation
frequency. Milling time and oscillation frequency were used to adjust the number
of stress events. It also remains unknown how high the moisture content can be
without exercising any significant influence on the crystallinity of cellulose in
grinding media milling. This was studied in Paper IV.
2.3.3 Pretreatments and milling conditions
There are various chemical, enzymatic and thermal pretreatments that have been
applied prior to the mechanical size reduction of wood (Lindholm & Kurdin
1999, Kenealy & Jeffries 2003, Rapp et al. 2006, Laxman & Lachke 2009, Zhu
JY et al. 2009a, 2009b, 2010a, Zhu JY & Pan 2010b, Zhu W et al. 2010). Thermal
pretreatment temperatures from 50°C to 150°C are considered to lead to non-
reactive drying, in which lignocelluloses lose moisture and shrink (Tumuluru et
al. 2011). This dehydration can cause defects and cracks in the wood (Repellin et
al. 2010). Temperature range from 150°C to 200°C is considered as the reactive
drying range, which results in structural damage due to cell wall collapse, and
46
correspondingly temperatures from 200°C to 300°C are considered to constitute a
destructive drying range, involving depolymerisation and devolatilisation
(Tumuluru et al. 2011). Drying also affects cellulose crystallinity (Esteves &
Pereira 2009, Leppänen et al. 2011). In terms of changes in Norway spruce wood
at the cellular level, drying in a reduced oxygen atmosphere at temperatures up to
220°C has been found to cause deformation in the earlywood and tangential
intracellular cracks in the latewood (Welzbacher et al. 2011).
Torrefaction is a thermal pretreatment applied at temperatures in the range
from 200°C to 300°C in an inert atmosphere that alters the physical and chemical
composition of a lignocellulose (Tumuluru et al. 2011, van der Stelt et al. 2011,
Acharya et al. 2012, Broström et al. 2012). It has been shown that torrefaction
can be used to reduce the specific energy requirement in the grinding of wood
with various designs of mill in order to obtain the desired particle size (Arias et
al. 2008, Repellin et al. 2010, Almendros et al. 2011, Phanphanich & Mani 2011,
Chen W-H et al. 2011, Kokko et al. 2012, van Essendelft et al. 2013). The
decrease in energy consumption correlates with the anhydrous weight loss due to
torrefaction (Repellin et al. 2010, Kokko et al. 2012). The reason for this
behaviour has been said to lie in the increased brittleness of the lignocellulose
during torrefaction (Tumuluru et al. 2011, Acharya et al. 2012), but we have no
information on whether torrefaction actually has any influence on grindability and
cellulose crystallinity in grinding media milling to a median particle size below
100 µm. Another important question is whether torrefaction pretreatment weakens
the structure so as to allow smaller particle sizes to be achieved. This was studied
in Paper V using impact-based grinding media mill.
In the case of viscoelastic materials cryogenic grinding is considered to be a
more effective method for fine grinding purposes (Wilczek et al. 2004). In
addition, cooling affects the movements of the molecules, so that plastic
deformation by viscous flows is reduced (Wilczek et al. 2004). Cryogenic
grinding conditions have been employed in the grinding media milling of wood
(Hon & Glasser 1979, Hon 1987, Maurer & Fengel 1992), leading Maurer &
Fengel (1992) to conclude that these conditions have no appreciable influence on
milling intensity by comparison with atmospheric conditions. However, a
reduction in temperature down to -196°C will promote a decrease in the ultimate
strength of wood (Gerhards 1982, Jiang et al. 2014). Moisture content is also
important, because a higher moisture content provides greater changes in ultimate
strength when lowering the temperature (Gerhards 1982). On the other hand,
when considering material with a high moisture content the use of processing
47
temperatures that are below the glass transition point of hemicelluloses will
prevent softening of these (Jääskeläinen & Sundqvist 2007: 127–130). The
moisture content of living trees is around 40–50%, and brittle behaviour is
typically observed at temperatures below -40°C (Jääskeläinen & Sundqvist 2007:
16, 127–130). We have no information on how the size, shape and crystallinity of
particles are affected by cryogenic processing conditions in fine grinding of wood
samples of varying moisture content. This was studied in Paper IV for moisture
content values between 1% and 50% on a wet basis. The fine grinding was
performed with an impact-based grinding media mill that was tailored for
cryogenic grinding.
48
49
3 Aims of the study
Wood powders have many interesting possible applications, but due to a lack of
knowledge about the processes involved, their industrial production is looked on
as ecologically unfeasible. The technology needed for dry fine grinding already
exists, but we do not know how the properties of the wood develop during fine
grinding and how the processing should be optimised to minimise the specific
energy consumption. The general aim was to obtain information on how the
physical properties of Norway spruce (Picea abies) wood develop during dry fine
grinding with impact-based mills under varying sets of grinding conditions and
what influence these have on energy consumption. The specific aims were to gain
an understanding of:
1. developments in the size and shape of dried wood particles in fine grinding
with impact mills (Papers I–III),
2. the influence of grinding conditions on specific energy consumption in the
fine grinding of dried wood with impact mills (Papers I–III),
3. the influence of cryogenic milling conditions and the drying of fresh wood on
the size, shape and cellulose crystallinity of wood particles in fine grinding
with double impact mills (Paper IV), and
4. the influence of mild torrefaction on the grindability, particle shape and
cellulose crystallinity of dried wood in fine grinding with double impact mills
(Paper V).
50
51
4 Materials and methods
4.1 Raw material
Norway spruce Picea abies (L.) H. Karst trees were harvested mainly from the
southern parts of Finland. The harvested trees were debarked and processed with
a circular saw at the Seikun Saha sawmill (Pori, Finland). The fresh sawdust was
gathered from the circular saw process and sent to the University of Oulu, where
it was stored in a freezer prior to the fine grinding experiments.
4.2 Pretreatments prior to fine grinding
The sawdust was screened and usually dried before the fine grinding experiments.
Fresh sawdust was used only in the experiments presented in Paper IV. Drying
took place in a large oven at non-reactive drying temperatures of 80°C (Papers III
and IV) and 105°C (Papers I, II, V). The dry matter content after drying was
measured with an MA100 moisture analyser (Sartorius AG, Germany). The
moisture content values listed in Table 5 were calculated by deducting the
measured dry matter content from 100%, and therefore represent the moisture
content on a wet basis. Screening was performed with a vibratory sieve equipped
with a screen having 4 mm circular holes. The particle size distribution of the
screened and dried sawdust was measured with an Analysette 3 (Fritsch,
Germany) vibratory sieve shaker in Paper I and with an e200LS (Hosokawa
Alpine, Germany) air jet sieve in Paper III. The median particle size was between
1 mm and 2 mm, and less than 4% of the particles by weight passed through a
sieve with an aperture of 250 µm in both cases. In Paper II the dried and screened
Norway spruce was preground with the same air classifier mill as was used for the
fine grinding in Paper I. This was a high-speed rotor impact mill 50 ZPS
(Hosokawa Alpine, Germany) integrated in a closed grinding circuit with a 50
ATP air classifier (Hosokawa Alpine, Germany). After pregrinding, the finest
particles were removed with the 50 ATP air classifier and the coarser particles
were used as a feed in the fine grinding experiments. For Paper V several samples
of dried and screened Norway spruce sawdust were torrefied in a nitrogen
atmosphere at temperatures below 230°C before fine grinding.
52
Table 5. Drying temperatures and moisture content after drying.
Paper Drying temperature (°C) Moisture content (%)
I 105 < 2
II 105 < 4
III 80 < 3
IV 80 1–50
V 105 < 1
4.3 Fine grinding experiments
The fine grinding equipment, operational parameters, milling conditions and
pretreatments used in the work reported in Papers I–V are listed in Table 6, and
the differences in the impact angles used in the air classifier milling are illustrated
in Fig. 10. The fine grinding experiments were performed under ambient milling
conditions unless otherwise stated. Detailed experimental plans are presented in
the original Papers I–V. For Paper I the air classifier mill was used for fine
grinding and its specific energy consumption was calculated from the overall
electricity consumption as presented in Paper I. For Paper II a fluidised bed
opposed jet mill, 100 AFG (Hosokawa Alpine, Germany), and an oscillatory ball
mill, Cryomill (Retsch, Germany), were used for fine grinding purposes. Like the
air classifier mill, the jet mill was also integrated into a closed grinding circuit
with the 50 ATP air classifier (Hosokawa Alpine, Germany).
The work done in compressing the grinding air in the jet milling experiments
was calculated on the assumption that air behaves as an ideal gas and that
compression is an isothermal process. The air was compressed by means of a
GA11FF screw compressor (Atlas Copco, Italy), but for the purpose of the
calculations the compression work was regarded as quasistatic and isothermal
work done by a piston ΔWP and calculated using the equation
=
=Δ
UC
C
air
gUC
C
UCgP lnln
p
p
M
TRV
V
VTnRW
ρ , (1)
where n is the amount of the substance (air), Rg the gas constant (8.314 J mol-1 K-
1), T the air temperature, V the volume of air, Mair the molar mass of air, ρ the
density of air and p the pressure of air. The subscript “C” in Equation 1 stands for
the compressed air and “UC” for the uncompressed air.
The 100 AFG fluidised bed opposed jet mill contains built-in devices for
measuring the classifier speed, pressure of the grinding air and total air flow rate,
53
data on which were collected during milling. The volume of the grinding air was
measured with an SS 30.301 thermal inline flow sensor (Schmidt technology,
Germany) connected to the pipe used to transfer the grinding air from the
compressor to the jet mill. The temperature during the fine grinding experiments
was approximately 293 K. The air volume in the SS 30.301 sensor was displayed
and recorded as a normal volume (Nm3) which in this particular device is the
volume at 20°C and 101,325 Pa according to the manufacturer. The dry mass of
product, mP,dry, was calculated by subtracting the dry mass of the wood that did
not get past the classifier from the input dry mass. The specific energy
consumption in jet milling SECJET was calculated as
P,dry
PJET SEC
m
WΔ= , (2)
Further information on the experiments is provided in Paper II.
In Paper III the fine grinding was studied with the oscillatory ball mill. For
calculation of specific energy consumption in oscillatory ball milling there was
estimated the total available impact energy of a single grinding ball ET (see Paper
III). The total available impact energy was calculated as
keT SN EE ⋅= , (3)
where
tf ⋅⋅= 2SN e, (4)
and
22ballk 8 fAmE ⋅⋅≈ , (5)
where in Equations 4 and 5 f is oscillation frequency, t milling time, mball the mass
of the grinding ball and A the end-to-end amplitude of the oscillation. The specific
energy in oscillatory ball milling SECOSC was calculated as
m
ETOSC SEC = , (6)
where m is the mass of the feed.
For the work described in Paper IV, fine grinding of screened Norway spruce
sawdust samples of varying moisture content was performed using the oscillatory
ball mill operated under ambient and cryogenic grinding conditions, using
nitrogen liquid (boiling point -196°C) as a coolant. Similarly, the fine grinding of
54
dried, screened and torrefied Norway spruce sawdust reported in Paper V took
place in the oscillatory ball mill. Torrefaction was performed in a nitrogen
atmosphere and the mass losses due to torrefaction (ML) were evaluated according
to Almeida et al. (2010), the result being used to represent the intensity of
torrefaction. The specific energy consumption as indicated in Paper V was
calculated using Equation 6. .
Table 6. Milling equipment and studied operational parameters, milling conditions and
pretreatments.
Paper Milling equipment Mill type(s) Studied operational parameters,
milling conditions and pretreatments
I Air classifier mill: a Rotor impact mill 50
ZPS integrated with an air classifier 50
ATP (Hosokawa Alpine, Germany)
High-speed
rotation disc type
Rotor/mill speed (50 ZPS), classifier
speed (50 ATP), impact angle (50
ZPS)
II Air classifier mill, a fluidised bed opposed
jet mill 100 AFG integrated with the air
classifier 50 ATP (Hosokawa Alpine,
Germany) and an oscillatory ball mill
CryoMill (Retsch, Germany)
High-speed
rotation disc type,
opposed jet type
and vibration type
Grinding pressure (100 AFG),
classifier speed (50 ATP)
III Oscillatory ball mill CryoMill (Retsch,
Germany)
Vibration type Grinding ball mass, mass of the
feed, oscillation frequency, milling
time
IV Oscillatory ball mill CryoMill (Retsch,
Germany)
Vibration type Cryogenic milling conditions,
Moisture content of the feed
V Oscillatory ball mill CryoMill (Retsch,
Germany)
Vibration type Torrefaction
Fig. 10. Impact angles studied in the air classifier milling experiments, referred to as
“long edge” or I(long) and “short edge” or I(short). The black arrow indicates the
rotation direction of the rotor.
55
The fine grinding experiments were replicated in most cases in order to obtain
information about the uncertainty affecting the processing and analysing. In these
cases the mean values were used for plotting and error bars were used to represent
95% confidence intervals when assuming a normal distribution. In the tables
presented in Chapter 5 the results are expressed in the following form: mean
value ± confidence interval.
4.4 Wood powder sampling and analyses
The measured properties of the pulverised Norway spruce wood samples as
indicated in Papers I–V are listed in Table 7. Since their X-ray diffraction (XRD)
profiles were measured in order to evaluate the crystallinity index, the measured
XRD profiles are not shown in Papers I, II and V.
Table 7. Properties of the wood powders as measured for Papers I–V
Measured property Paper
I II III IV V
Particle size distribution x x x x x
Aspect ratio distribution x x x x x
XRD-profile and crystallinity index x x x x
4.4.1 Sampling
The wood powders produced with the air classifier mill and fluidised bed opposed
jet mill as described in Papers I and II were sampled with a PT-type sample
divider (Retsch, Germany) to obtain representative samples for analyses.
4.4.2 Analyses performed on diluted wood powder samples
Preparation of diluted wood powder samples
The diluted wood powder samples were prepared as described in Papers I–V.
Particle size distribution
The volumetric particle size distribution of diluted wood powder samples was
measured with an LS 13320 laser diffraction-based particle size analyser
56
(Beckmann Coulter, U.S.A). The median size, d50, was used to represent the
particle size and the dimensionless parameter Δ* to represent the width of particle
size distribution. The latter was calculated as
µm 10* 1090 dd −=Δ , (7)
where d90 and d10 are the particle sizes in micrometres corresponding to the 90%
and 10% values in the cumulative size distribution, respectively. The size ratios
(d90-d10)/d50 and (d90-d10)/(2 d50) are more commonly used to provide information
about the width of particle size distribution (Nakach et al. 2004, Adi et al. 2007,
Palaniandy & Azizli 2009, Toraman 2011, Kotake et al. 2012) but these ratios
depend on the median particle size of the product. To make comparison between
samples with different median particle size easier the divider in the size ratios was
replaced by a constant value of 10 µm.
Aspect ratio distribution
Aspect ratio distributions were measured from photos taken with a charged
coupled device (CCD) as described in Papers I–V. The minimum aspect ratio (=1)
represents a perfect filled circle. In the case of wood particles, a higher aspect
ratio typically represents a more elongated shape. The cumulative aspect ratio
distribution was used to calculate the median aspect ratio AR50 and the width of
the aspect ratio distribution ΔAR, the latter being defined as the difference between
the aspect ratios corresponding to the 90% and 10% values in the distribution. An
Ultra Plus field emission scanning electron microscope (Carl Zeiss, Germany)
was used for the imaging of the finest particles to gain insight of their shape, but
these images were not used to calculate the aspect ratio distribution.
4.4.3 Analyses performed on dry wood powder samples
Preparation of the dry wood powder samples
The wood powders produced as described in Papers I–II and V were used for the
measurement of XRD profiles without drying, but all those produced for Paper IV
were vacuum-dried before measuring the XRD profile.
57
XRD profile and crystallinity index
Tablets were prepared from the dry wood powders using a hydraulic press and X-
ray diffraction profiles were measured with a D5000 diffractometer (Siemens,
Germany) as described in Papers I, II, IV and V. The degree of crystallinity of the
cellulose in terms of the crystallinity index (CrI) was calculated from the XRD
profile in each case by the method proposed by Segal et al. (1959).
4.5 Modelling
Empirical models for specific energy consumption (SEC) and various wood
powder properties were developed as a function of the operational parameters in
Paper I. A Modde 7.0.0.1 software (Umetrics, Sweden) was used in the statistical
analyses of the experimental data. In these statistical analyses, responses such as
SEC and the various wood powder properties were modified with a mathematical
operator to gain normally distributed data and good statistical significance for the
models. The effects can be derived unambiguously from the coefficients of the
empirical models and are therefore used as synonyms for them in the discussion.
In Paper III the total available impact energy of the grinding ball in oscillatory
ball milling was estimated (Eq. 3) and used to model the effects of the grinding
ball mass, oscillation frequency and milling time on the properties of the wood
powders and to estimate the specific energy consumption in fine grinding.
58
59
5 Results and discussion
5.1 Fine grinding of dried Norway spruce wood in impact mills
5.1.1 Air classifier mill
The SECs and the properties of the wood powders obtained from the air classifier
mill are listed in Table 8, which indicates that the wood was ground to a median
particle size of around 23 µm with a Δ* of over 5. The finest powders had AR50
2.3 and ΔAR 3.3 or higher (Table 8). To provide an insight into the shapes of the
particles, CCD photos of sample ZPS 17 are presented in Fig. 11. The largest
particles shown in Fig. 11a can be described as elongated and rectangular in shape
rather than roundish, while the finest ones (Fig. 11c) resemble roundish particles
but it is difficult to distinguish their shapes accurately because the pixel resolution
of the CCD photos is around 1.6 µm. The FESEM image shown in Fig. 11d
nevertheless suggests that they, too, are rectangular rather than roundish. The
lowest CrI (approximately 41%) was obtained at the highest classifier and mill
speeds, whereas reducing the mill speed from 20,000 min-1 to 8000 min-1 seemed
to increase CrI. This means that air classifier milling had only a minor influence
on the CrI of the wood by comparison with grinding media milling, where total
amorphisation has proved possible (see Section 2.3.2). There were large
variations in cellulose crystallinity between samples ground with similar
processing parameters (see Table 8), possibly due to uneven drying conditions.
Thermal treatment (Esteves & Pereira 2009), and also air-drying (Leppänen et al.
2011), may affect the cellulose crystallinity of wood. In this case drying was
performed in large containers without any mixing, and therefore there were local
variations in drying conditions depending on the position of the wood in the
container.
60
Table 8. Specific energy consumption (SEC) in air classifier milling and the properties
of the resulting wood powders. ‘Short’ and ‘long’ impact angles refers to the rotational
direction of the rotor towards the short or long edge. Experiments ZPS10–ZPS18 are
replicates for ZPS1–ZPS9. Modified from Paper I, published by permission of Elsevier.
Experiment (run
order)
Mill speed
(min-1)
Classifier
speed (min-1)
Impact
angle
SEC
(kWh t-1)
d50
(µm)
∆* AR50 ∆AR CrI (%)
ZPS1 (4) 8000 2000 Short 2505 208.5 76.8 2.8 6.3 47.2
ZPS2 (14)1 8000 8000 Short 30,994 32.8 11.9 2.5 4.7 44.8
ZPS3 (11) 20,000 2000 Short 1712 223.0 70.7 3.5 6.6 49.6
ZPS4 (8)1 20,000 8000 Short 4098 25.4 7.0 2.3 3.4 41.8
ZPS5 (5) 8000 2000 Long 2991 189.6 70.0 2.8 6.0 43.4
ZPS6 (3) 8000 8000 Long 38,160 33.0 12.1 2.5 4.7 45.9
ZPS7 (10) 20,000 2000 Long 1664 207.6 68.3 3.4 6.6 49.6
ZPS8 (1)1 20,000 8000 Long 7879 25.9 7.5 2.4 3.7 41.2
ZPS9 (6) 14,000 5000 Short 2593 49.1 15.8 2.8 5.2 43.0
ZPS10 (2) 8000 2000 Short 2549 198.4 71.7 2.8 6.3 49.3
ZPS11 (15) 8000 8000 Short 17,589 32.7 12.3 2.4 4.8 45.5
ZPS12 (9) 20,000 2000 Short 1723 249.5 80.0 3.5 6.6 50.2
ZPS13 (13)1 20,000 8000 Short 6648 23.0 5.6 2.3 3.3 41.5
ZPS14 (18) 8000 2000 Long 2431 189.9 69.6 2.7 5.9 48.2
ZPS15 (17) 8000 8000 Long 17,496 31.6 11.8 2.4 4.6 46.3
ZPS16 (7) 20,000 2000 Long 1844 232.9 72.8 3.5 6.8 48.0
ZPS17 (16) 20,000 8000 Long 4310 23.8 6.2 2.3 3.4 44.5
ZPS18 (12) 14,000 5000 Short 2588 44.6 14.5 2.7 4.8 45.7
ZPS19 (19) 20,000 8000 Long 4245 - - - - -
1 Grinding time was less than 40 min
61
Fig. 11. Three CCD photos showing some of the a) largest b) intermediate-sized, c)
finest observable wood particles, and d) FESEM image showing some small
rectangular-shaped particles in the rotor impact milled sample ZPS17.
Development of wood powder properties
The results of experiments ZPS1–ZPS18 (Table 8) were used for modelling of the
wood powder properties as a function of the processing parameters. The
coefficients used in these empirical models for the wood powder properties are
shown in Fig. 12 and the main statistical parameters for the models in Table 9.
The high values for R2, R2(Adj.), Q2 and reproducibility in Table 9 indicate that
the empirical models are statistically valid and the results reproducible, except in
the case of the crystallinity index. The model validity is over 0.25 for all the
properties studied (see Table 9) and therefore there is no lack of fit in the models.
In the case of ΔAR the low model validity can be considered an artefact, since the
other statistical parameters are well over 0.9 (see Table 9). The reason for poor
statistical values in empirical model for CrI was the large variations in CrI values,
62
even when similar processing parameters were used (Table 8). The reason for the
poor statistical values in the empirical model for CrI lay in the large variations in
CrI values even when similar processing parameters were used (Table 8).
According to Fig. 12, the classifier speed, mill speed and their interaction had a
significant influence on the wood powder properties, but the choice between long
and short edges had a negligible influence, because the respective coefficients
with error bars cross the zero line (Fig. 12). The classifier speed alone had the
most significant effect on the properties of the wood powders (Fig. 12). Contour
plots for the empirical models for wood powder properties as a function of mill
and classifier speeds in the speed ranges studied here are shown in Fig. 13. The
effect of the impact angle is ignored in the models due its insignificant influence
on the properties of the wood. Fig. 13 suggests that there is a certain classifier
speed for every wood powder property at which changes in mill speed do not
influence the property and above which the influence of mill speed is the reverse
of what it was below that speed.
Fig. 12. Scaled and centred coefficients in the empirical models for the development
of wood powder properties in air classifier milling. The empirical models depict
responses that have been modified with the mathematical operator mentioned on the
y-axis. Modified from Paper I, published by permission of Elsevier.
63
Table 9. Main statistical parameters of the empirical models for the wood powder
properties (95% confidence level and normal distribution). Modified from Paper I,
published by permission of Elsevier.
Property R2 R2 (Adj.) Q2 Model validity Reproducibility Cond. no.
d50 0.998 0.997 0.995 0.857 0.997 6.214
∆* 0.996 0.994 0.991 0.853 0.994 6.214
AR50 0.986 0.982 0.976 0.912 0.979 1.118
∆AR 0.985 0.980 0.973 0.442 0.987 1.118
CrI 0.728 0.644 0.480 0.750 0.666 1.118
Fig. 13. Contour-plotted empirical models for given wood powder properties as a
function of the classifier and mill speeds. The effect of the impact angle is ignored.
Modified from Paper I, published by permission of Elsevier.
Specific energy consumption
An SEC of over 5.8 kJ g-1 (1600 kWh t-1) was needed to obtain a d50 of around
190 µm in the fine grinding of Norway spruce wood, and over 15.5 kJ g-1 (4300
kWh t-1) to obtain a d50 of around 23 µm (Table 8). When a low mill speed was
used with the highest classifier speed, d50 was approximately 10 µm higher and
the specific energy consumption more than doubled relative to processing at a
high mill speed (Table 8). The increased specific energy consumption indicates
that a mill speed of 8000 min-1 provides insufficient stress energy when grinding
64
wood to a median particle size range of around 30 µm, so that higher mill speeds
should be used for fine grinding purposes.
The results shown in Table 8 were used for modelling SEC as a function of
the processing parameters. The specific energy consumption figures obtained in
experiments ZPS2, ZPS4, ZPS8 and ZPS13 were not included in the modelling
because the grinding time was less than 40 minutes, which will have had a
significant influence on the SEC (see Paper I for details). The coefficients in the
empirical model for the specific energy consumption in which the response is the
inverse value of SEC are shown in Fig. 14, as also are the main statistical
parameters of the empirical model. The high values for R2, R2(Adj.), Q2 and
reproducibility in Fig. 14 indicate that the model is statistically valid and the
results are reproducible. Since the validity of the model is above 0.25, the error in
the model is in the same range as pure error. Fig. 14 also shows that the classifier
speed and mill speed had an influence on the average specific energy
consumption in fine grinding, the classifier speed being the most significant
single factor (Fig. 14). The use of a higher classifier speed led to a higher specific
energy consumption, because the classifier wheel needed more power from the
motor to revolve faster. Another reason is that as the classifier speed increases the
particles need to be finer to get past the classifier and therefore their residence
time in the grinding and classifying section increases. This reduces the production
rate and increases the energy demand of the rotor in the grinding zone. The
specific energy consumption in air classifier milling can be reduced by using a
higher rotor speed (Figs. 14 and 15). The choice between the long and short
impact edge had a negligible effect, since their coefficients with error bars cross
the zero line (Fig. 14). A contour plot of the modelled specific energy
consumption as a function of the classifier and mill speeds in the speed ranges
studied here is shown in Fig. 15. Since the start-up of the process is inefficient in
terms of energy and the feeding speed was not optimised, the specific energy
consumption can be expected to be lower in an industrial process that is
continuous and well optimised.
65
Fig. 14. Scaled and centred coefficients of the operational parameters in the empirical
model for average specific energy consumption. The symbols for the coefficients are
explained in Fig. 12. Modified from Paper I, published by permission of Elsevier.
Fig. 15. Contour plot of the modelled average specific energy consumption in kWh t-1
when fine grinding lasts for 40 minutes. The effect of the impact angle is ignored.
Paper I, published by permission of Elsevier.
5.1.2 Fluidised bed opposed jet mill
As seen in Fig. 16, dried Norway spruce wood was ground in an opposed jet mill
to a median particle size of around 18 µm, giving a Δ* of around 5. The finest
powders produced had AR50 2.5 and ΔAR 3.6 or higher. The aspect ratios were
slightly higher than those for the finest powders produced with the air classifier
mill (see Table 8 and Fig. 16), and therefore the jet milled particles are smaller
and more elongated. This difference may, however, be due to the removal of
66
finest particles after pregrinding rather than to the different milling technique. To
provide an insight into the shapes of the particles, CCD photos of particles in jet
milled sample AFG-P8, with a median particle size of around 20 µm, are shown
in Fig. 17 (see Paper II for detailed information on the sample). The largest and
intermediate-sized wood particles, shown in Fig. 17a, can be described as
elongated, while the finest particles resemble roundish ones, as in air classifier
sample ZPS 17 (Figs 11c and 17c). When a grinding pressure of 10 bar was
applied at a classifier speed of 20,000 min-1 CrI was reduced from 47.5% to
around 44%, which means that opposed jet milling had only a minor influence on
CrI.
Fig. 16. Development of (a) d50, (b) ∆*, (c) AR50, (d) ∆AR and (e) CrI as a function of
classifier speed in opposed jet milling. Low GP stands for the grinding pressure
approximately 6 bar and High GP stands for the grinding pressure approximately 10
bar.
67
Fig. 17. Three CCD photos showing some of the a) largest b) intermediate-sized, c)
finest observable wood particles, and d) FESEM image showing some small
rectangular-shaped particles in opposed jet milled sample AFG-P8.
Development of wood powder properties
According to Fig. 16 the grinding pressure had substantial influence on particle
size and shape when the classifier speed was around 8000 min-1. This effect may
be due to the higher air flow rate in the case of a higher grinding pressure (see
Table 10), thus causing larger particles to pass through the classifier than with a
lower flow rate at a similar classifier speed. The air flow exerts a drag force on
the particles, driving them past the classifier wheel and into the product container
(see Benz et al. 1996). This drag force will depend on the particle size, with a
higher air flow rate increasing the particle size of the product. The increase in
aspect ratio is probably connected with the increased particle size. The influence
of the air flow rate on the particle properties became negligible at a classifier
speed of 20,000 min-1 (Fig. 16), even though a significant decrease in cellulose
crystallinity still took place at this classifier speed when a high grinding pressure
68
was used (Fig. 16). This means that a grinding pressure of approximately 10 bar
(overpressure) was enough to cause reduced cellulose crystallinity when d50 was
less than 70 µm (Fig. 16), whereas the use of a low grinding pressure caused a
very small or negligible decrease in CrI even though the wood was ground down
to a median particle size of 20 µm (Fig. 16).
Table 10. Averaged processing parameters, specific energy consumption and product
information on the jet milling experiments.
Experiment Classifier Grinding air Total air Feed or Product Energy
Speed
(min-1)
Pressure1
(bar)
Volume
(Nm3)
Compression
work2 (MJ)
Flow
rate
(Nm3 h-1)
Dry mass
mP,dry (g)
Median size3
(µm)
SECJET
(kJ g-1)
FEED - - - - - - 199 ± 6 -
AFG-P1 8040 5.92 7.23 1.42 86.18 25.92 52.1 54.71
AFG-P2 20,010 5.93 7.00 1.37 85.65 13.34 18.2 103.00
AFG-P3 8040 9.89 11.63 2.81 96.64 59.02 69.2 47.67
AFG-P4 19,980 9.88 11.38 2.75 94.70 29.71 20.0 92.66
AFG-P5 8010 5.93 7.20 1.41 86.37 40.05 48.2 32.28
AFG-P6 20,010 5.93 6.99 1.37 85.50 12.82 18.4 106.93
AFG-P7 8040 9.89 11.58 2.80 96.34 59.97 67.4 46.73
AFG-P8 20,010 9.83 11.87 2.87 95.98 32.34 19.9 88.59
1 Excess pressure compared with normal air pressure (NTP), 2 Compression work calculated using
Equation 2 with Mair = 28.96 g mol-1, pUC = 101,325 Pa, ρ = 1204 g m-3, T = 293.15 K and the averaged
pressure of the grinding air. 3 Measured in wood powder collected from the container after the classifier,
thus not including particles conducted to the filtering stage.
Specific energy consumption
Since most of the energy needed for processing in a jet mill is consumed in
compressing the pressurised air, it was the work needed for this purpose that was
considered here. The averaged processing parameters for the fine grinding of
dried Norway spruce wood in a fluidised bed opposed jet mill are listed in Table
10. Only dry air was considered when calculating the compression work. An
increase in classifier speed reduced the median particle size and the dry mass of
the product (Table 10), while an increase in grinding pressure increased the
median size and mass of the product, i.e. the production rate (Table 10). A small
decrease in the total average flow rate of air was observed on every occasion
when a higher classifier speed was used rather than a lower one, given that the
grinding pressure was kept constant (Table 10). On the other hand, when the
69
classifier speed was kept constant the total average flow rate of air, the volume of
the grinding air and the work needed for compressing the grinding air increased
on every occasion when the grinding pressure was increased (Table 10). The
specific energy consumption in milling was mainly affected by the classifier
speed (Table 10). At high classifier speeds the use of a higher grinding pressure
reduced the specific energy consumption but increased the median particle size of
the product (Table 10). As seen in Table 10, over 32 kJ g-1 (approx. 9 MWh t-1)
but less than 55 kJ g-1 (approx. 15 MWh t-1) was needed to obtain wood powders
with a median particle size between 48.2 µm and 69.2 µm from a feed with d50 =
199 µm (±6 µm), and over 88 kJ g-1 (approx. 25 MWh t-1) to obtain a median
particle size of around 20 µm (Table 10). Although the compression work
considers the ideal minimum work needed for compression, the fine grinding was
not fully optimised because the feeding rate was kept constant. The experiments
also involved an energy inefficient start-up period. Thus the energy consumption
may be even lower in an optimised continuous process.
5.1.3 Oscillatory ball mill
Dried Norway spruce wood was ground to a median particle size of less than 18
µm with a Δ* of around 5 with the oscillatory ball mill, and the finest powders
produced had AR50 and ΔAR significantly lower than 2.0 (Fig. 18). These values
are much lower than for the finest powders produced with the air classifier mill or
the opposed jet mill (see Table 8 and Fig. 16), and therefore oscillatory ball
milling can be said to produce particles that are smaller and rounder than in either
of the above. To provide an insight into the shapes of the particles, CCD photos of
the powder produced in the oscillatory ball mill, with a median particle size of
around 20 µm, are presented in Fig. 19. All of the wood particles shown in this
figure can be described as rectangular or roundish. FESEM images of some of the
finest particles obtained by this method are shown in Fig. 20. It was also possible
to produce wood powders by oscillatory ball milling that had a median particle
size over 100 µm with an AR50 of less than 1.8 and a ΔAR less than 2.4 (Fig. 18).
70
Fig. 18. Effect of grinding ball mass and oscillation frequency on the a) d50, b) ∆*, c)
AR50, d) ∆AR and e) temperature change as a function of the total available impact
energy of the grinding ball, ET. The mass of the feed in each setup was 1 g. Data
points containing an open space indicate the large end cut in the particle size
distribution. Modified from Paper III, published by permission of Elsevier.
71
Fig. 19. Three CCD photos showing some of the a) largest, b) intermediate-sized and
c) finest observable wood particles in an oscillatory ball milled sample with d50 = 21.5
µm, ∆* = 5.8, AR50 = 1.6 and ∆AR = 1.5.
Fig. 20. Eight different FESEM images a)-h) taken from one oscillatory ball milled
wood powder sample. Modified from Paper II, published by permission of Elsevier.
72
Development of wood powder properties
According to Fig. 18, the total kinetic energy of the grinding ball ET (see Paper
III) predicts the development in the size and shape properties of dried Norway
spruce wood in oscillatory ball milling upon a change in the mass of the grinding
ball or its oscillation frequency. It is therefore proposed that the mathematical
model evaluated here (Eq. 3) can be applied as a simplified mill based stressing
model to oscillatory ball milling in impact mode (for further information about
the impact mode, see Chen Y et al. 2004) for predicting milling behaviour when
changing the oscillation frequency, mass of the grinding ball (but not its volume)
and milling time. In this model the stressing energy is Ek (Eq. 4), the stress
number is SNe (Eq. 5) and stressing type is double impact (see Section 2.2.2). The
median particle size was inversely linearly dependent on ET in the ET range
considered before achieving a median particle size of 20 µm (Fig. 18a). The
mathematical model plotted in Fig. 18a is the same as Rittinger’s model, which is
commonly used in mineral processing to model the energy consumption when
considering particle sizes in the range 10–1000 µm (Lowrison 1974: 54–55).
Rittinger’s model has also been found to apply to the fine grinding behaviour of
α-lactose monohydrate in oscillatory ball milling in impact mode (Chen Y et al.
2004). When processing was continued after a median particle size of 20 µm had
been obtained, which occurred at ET = 1360 J according to the model derived
here, the resistance of the wood to further size reduction increased considerably
and its particle size properties (d50 and Δ*) flattened out at a certain level or even
increased (Figs. 18a and b). The smallest median particle size was found to be
between 13 µm and 20 µm for all the studied setups (Fig. 18a). In the case of
setups B–D the temperature change increased significantly when the particle size
properties evened out at a certain level (Figs. 18a, b and e). The rise in
temperature and sudden increase in comminution resistance indicate the presence
of viscoelastic behaviour in wood. This viscoelasticity is most likely the main
reason why the size properties of Norway spruce wood evened out at a certain
particle size range even though higher impact energies were used in processing
and pulverisation was continued after the minimum size had been attained. On the
other hand, AR50 and ΔAR did not flatten out at the same point as the median
particle size as a function of ET (Fig. 18a–d). This means that the particles do not
break due to fragmentation, because their volume-based particle size properties
remained unchanged. Presumably there may be a surface breakage mechanism,
attrition, involved. Attrition causes particles to become rounder but has an
73
insignificant effect on their volume-based size properties. In addition, the changes
in aspect ratio may be also due to deformation of the wood particles under
repeated stress that together with temperature change suggests viscoplastic
behaviour of Norway spruce wood once the minimum particle size has been
reached (Fig. 18). This observation suggests the presence of globular-shaped
particles that tend to agglomerate with prolonged milling times, as first described
for Norway spruce wood by Maurer and Fengel (1992). FESEM images of
particles found in an oscillatory ball milled sample are shown in Fig. 20, where
the roundish particles in Figs. 20g and h could be the globular shaped particles
that tend to agglomerate. Fig. 21 shows how varying the mass of the feed (setups
D–G) can affect the development of inverse values for d50 and Δ* as a function of
ET. According to Fig. 21a, median size follows an inverse linear trend as a
function of ET (Rittinger’s model) in the particle size range between 20 µm and
100 µm when the mass of the feed is between 1 g and 3 g. In the case of setup E
the trend is non-linear (Fig. 21a) and therefore cannot be modelled with
Rittinger’s model.
74
Fig. 21. Effect of changes in the amount of feed on the inverse of a) median size and b)
width of the particle size distribution as a function of total available impact energy of
the grinding ball, ET. The black line represents the model for setups B–D introduced in
Fig. 18. Data points containing an open space indicate the large end cut in the particle
size distribution. Modified from Paper III, published by permission of Elsevier.
Specific energy consumption
The specific energy consumption for different amounts of feed is shown in Fig.
22. Setup E is the least energy efficient when the desired median particle size is
less than 100 µm. The reason for the different comminution behaviour in the case
of setup E is probably the low amount of feed, which makes it possible for some
collisions to occur between the grinding ball and the grinding jar with little or no
wood present in the impact zone. According to Fig. 22, dried and screened
Norway spruce sawdust can be pulverised down to d50 = 100 µm with a minimum
specific energy consumption of 0.36 kJ g-1 (100 kWh t-1) and down to d50 = 20 µm
with 1.4 kJ g-1 (380 kWh t-1) when considering the total available impact energy
of the grinding ball in fine grinding. Kobayashi et al. (2008) has reported that 800
75
kWh t-1 was consumed for the whole process when Norway spruce wood chips
were pulverised from 22 mm down to 150 µm with a vibration mill. The specific
energy consumption calculated from the estimated total available impact energy
of the grinding ball (SECOSC) considers only the energy available for particle size
reduction, which is lower than the total electrical energy consumed by the
equipment, due to energy losses in driving the mill and in the electronics. On the
other hand, the theoretical energy needed for the generation of new surfaces can
be considered to be lower than the estimated SECOSC. Only in the ideal case,
where the total available impact energy in the process is applied for the
generation of new surfaces, should the estimated SECOSC be the same as the
theoretical energy needed for the generation of the new surface area. Since this
ideal situation will never exist in practical comminution, the estimated SECOSC
will always be higher than the theoretical energy needed for the generation of new
surfaces. Therefore the estimated SECOSC provides a better practical value for the
energy consumption than can be gained by calculating the theoretical energy for
the generation of new surfaces and can be regarded as a good target for the
optimisation of impact-based mills involving grinding media.
Fig. 22. Effect of the feed amount of feed on median particle size as a function of the
specific energy consumption. The data point containing an open space indicates a
large end cut in the size distribution. Modified from Paper III, published by permission
of Elsevier.
76
5.2 Comparison of impact milling techniques
Influence of double impacts on the development of wood properties in
milling
Figs. 23–25 show the development of Δ*, AR50, ΔAR and CrI in opposed jet
milling and oscillatory ball milling as a function of median particle size. In
oscillatory ball milling Δ* followed a linear trend as a function of d50 in fine
grinding from a d50 of 199 µm (± 6 µm) down to around 20 µm (Fig. 23), while in
the case of the jet milled samples Δ* decreased as a function of d50 and was
approximately identical to the particle size distribution of the oscillatory ball
milled samples when considering a median particle size around 20 µm (Fig. 23).
Median aspect ratio and ΔAR decreased more as a function of d50 in oscillatory
ball milling than in opposed jet milling (Fig. 24). The CCD photos shown in Fig.
26 provide an insight into the differences between the milling techniques in terms
of the aspect ratio distribution when d50 is around 20 µm. Opposed jet milling had
a significantly lower effect on the crystallinity index than did oscillatory ball
milling when the wood was ground down to a d50 around 20 µm (Fig. 25).
Fig. 23. Effect of oscillatory ball milling and opposed jet milling on the development of
the width of the particle size distribution ∆* as a function of the median particle size
d50. High GP and low GP mean average excess pressures of the grinding air of
approximately 10 bar and 6 bar, respectively. Paper II, published by permission of
Elsevier.
77
Fig. 24. Effect of oscillatory ball milling and opposed jet milling on the development of
a) the median aspect ratio AR50 and b) the width of the aspect ratio distribution ∆AR as
a function of the median particle size d50. High GP and low GP are as in Fig. 23.
Modified from Paper II, published by permission of Elsevier.
Fig. 25. Effect of the milling technique on development of the crystallinity index CrI as
a function of the median particle size d50. High GP and low GP are as in Fig. 23. Paper
II, published by permission of Elsevier.
78
Fig. 26. CCD photos showing some of the largest wood particles from a) the feed, b)
the product of opposed jet milling and c) the product of oscillatory ball milling. The jet
milled and oscillatory ball milled particles were of a median size of around 20 µm.
Modified from Paper II, published by permission of Elsevier.
The feed used in the jet milling and oscillatory ball milling experiments was
produced from a similarly treated raw material to that used in the air classifier
milling experiments. Also the feed was preground with the same air classifier mill
as was used in the air classifier milling experiments, but the finest particles were
removed from the feed prior to jet and oscillatory ball milling. Although a d50 of
around 23 µm was obtained in air classifier milling, CrI (%) could not be reduced
below 41% and the minimum AR50 and ΔAR were 2.3 and 3.3, respectively (Table
8). Thus the greatest differences in the properties of the wood powders were
observed between the media and non-media impact mill experiments (Figs. 23–25
and Table 8). In fine grinding of dried Norway spruce wood the presence of
double impacts favoured the production of rounder shaped particles with low
cellulose crystallinity by comparison with single impacts (Figs. 23–25 and Table
8).
Specific energy consumption
When comparing specific energy consumption it is important first to consider the
desired properties of the wood powder. When high cellulose crystallinity and
aspect ratio are required in dried Norway spruce the suitable impact-based fine
grinding techniques would be opposed jet mills and rotor impact mills. In the
present experiments it was possible to reduce Norway spruce wood from a
median particle size between 1 mm and 2 mm down to 23.8 µm with a specific
energy consumption of 15.5 kJ g-1 by air classifier milling (Table 8), whereas
opposed jet milling consumed over 32 kJ g-1 in producing wood powder with a
median particle size of 48.2 µm from a significantly smaller feed than that was
79
used in air classifier milling (Table 10). It should therefore be suggested that an
air classifier mill is more energy efficient technique than a fluidised bed opposed
jet mill for pulverising dried Norway spruce wood. In fact, the electric power
demand in the case of air classifier milling can be even lower in an industrial-
scale production plant. In the case of jet milling, the milling chamber in the
laboratory model has been built by Hosokawa Alpine with a similar architecture
to that of the larger-scale equipment of the AFG product family, so that the use of
compression energy for particle breakage in the laboratory equipment can be
considered to be very close to that observed in an industrial-scale milling plant
with a similar jet mill. It might be possible to optimise both types even further by
increasing the feed rate.
The specific energy consumption in the impact milling of dried Norway
spruce wood with a median particle size between 1 mm to 2 mm with media mills
can be as low as 0.36 kJ g-1 for a targeted d50 of 100 µm and 1.40 kJ g-1 for a d50
of 20 µm (Fig. 22). This specific energy consumption does not consider the
energy losses in driving the machine or any additional equipment, which are
naturally included in the specific energy consumption when considering the
electric energy demand of the mill. It therefore seems possible to obtain a lower
energy consumption with media mills than with an air classifier mill, but this
depends on the consumption of energy that is not directed at the comminution of
particles. This energy is significantly affected by the architecture of a media mill.
Kobayashi et al. (2012), studying the significance of the architecture of vibration
mills for energy efficient wood powder production, concluded that a multiple tube
vibration mill is more energy efficient than a single tube vibration mill and
estimated the specific energy consumption in the fine grinding of wood to be 1.0
kJ g-1 when using a multiple tube vibration mill. This figure is very close to the
values obtained in the present oscillatory ball milling experiments (Fig. 22), so
that media milling appears to be well suited for wood pulverisation.
80
5.3 Effects of pretreatments and milling conditions on the properties of Norway spruce wood in impact-based media
milling
5.3.1 Drying and cryogenic grinding conditions
Development of d50, Δ*, AR50 and ΔAR under ambient and cryogenic grinding
conditions is shown as a function of moisture content in Fig. 27, which suggests
that while moisture content has a significant influence on wood powder properties
under ambient grinding conditions, these properties are less dependent on
moisture content under cryogenic conditions (Fig. 27). When comparing grinding
conditions given the same moisture content (Fig 27a), it can be seen that a smaller
median particle size was obtainable under cryogenic conditions. When
considering the moisture contents of 1%, 27% and 50% in Fig 27a, increasing the
grinding time from 10 min to 30 min under ambient conditions did not reduce the
median particle size any further than had been obtained by cryogenic grinding for
10 min. It therefore seems that the use of cryogenic grinding conditions rather
than ambient conditions provides better energy efficiency in the fine grinding of
Norway spruce wood. Wood powder with a median particle size of less than 13
µm was obtained only under cryogenic conditions (Fig. 27a), when the finest
wood powder had a median size of 7.4, Δ* = 2.04, AR50 = 1.67 and ΔAR = 1.78. It
has not been possible to produce wood powders with a median particle size
significantly less than 13 µm in any other way (Figs 18, 27 and Tables 8 and 10).
It was possible to produce fine powders with a median particle size below 100 µm
an elongated particle shape (AR50 ≈ 3.0 and ΔAR ≈ 6.0) under ambient
conditions by pulverising Norway spruce wood with a moisture content of 44%
(Fig. 27). The CCD photos and FESEM images of various wood powders in Figs.
28 and 29 illustrate the differences in particle shape between the powders with
different AR50 and ΔAR values obtained by oscillatory ball milling. Vibration mills
are generally regarded in the literature as representing a technique for producing
roundish particles from wood (see Section 2.3.2), but milling moist wood under
ambient conditions does in effect produce elongated particles with AR50 and ΔAR
values very close to those produced with a rotor impact mill and jet mill (Figs. 24,
25, 27 and Table 8). The reason suggested for this is softening of the
hemicelluloses due to the plasticising effect of water at room temperature, which
favours cleavage in the primary and secondary cell wall layers (Jääskeläinen &
Sundqvist 2007: 127–130). Under cryogenic grinding conditions the temperature
81
is too low for any softening of the hemicelluloses and thus the particle shapes are
similar to those obtained from dried wood. In fact, the oscillatory ball milling
experiments with dried Norway spruce wood yielded some particles with a scaly
surface (see Figs. 20h and g), as were also found when wood powders were
milled under cryogenic conditions (Fig. 30).
Fig. 27. The differences between ambient and cryogenic grinding conditions in a) d50,
b) ∆*, c) AR50 and d) ∆AR as a function of moisture content in oscillatory ball milling.
The black data points represent experiments with replicates and the empty data points
indicate a large-end cut in the particle size distribution. Modified from Paper IV,
published by permission of De Gruyter.
82
Fig. 28. CCD photos from three wood powder samples with different aspect ratio
properties. In the figure there is shown three photos from each sample to illustrate
differences in different particle size ranges. Paper IV, published by permission of De
Gruyter.
Fig. 29. FESEM images of two wood powder samples. Paper IV, published by
permission of De Gruyter.
Fig. 30. FESEM images of a wood powder sample milled under cryogenic conditions.
83
The crystallinity indices of oscillatory ball milled samples pulverised under
ambient and cryogenic conditions for different periods of time are listed in Table
11. Segal et al. (1959) developed the method for estimating the relative degree of
cellulose crystallinity in cotton celluloses and therefore one explanation for the
negative CrI values shown in Table 11 can be due the differences in the X-ray
diffraction patterns between cotton cellulose and Norway spruce wood. The CrI
of the fresh feed was 39% and that of the oven-dried feed was also 39%, so there
were no observable changes in CrI due to oven-drying of the wood. It may be
seen from Table 11 that oscillatory ball milling of Norway spruce wood for at
least 10 min lowered the CrI by at least 4%-units. The fine grinding of wood a
with moisture content over 27%, which is slightly above the fibre saturation point
of Norway spruce wood (see Section 2.1.2), under ambient conditions had little
effect on CrI (Table 11), but when considering the milling of feeds with moisture
contents between 1% and 27% under ambient conditions, a lower CrI was
obtained with the samples that had a lower initial moisture content when milling
for 10 min (Table 11). In the case of the feed with a moisture content of 1%, a
longer grinding time reduced the CrI even more (Table 11), but when wood with a
moisture content between 8% and 50% was milled for 10 min under cryogenic
conditions the crystallinity indices varied between 24% and 30% (Table 11).
When samples with an initial moisture content of 1% were milled under
cryogenic conditions for 10 min the CrI was significantly lower than in the other
samples milled under similar conditions (Table 11). Under cryogenic conditions a
longer grinding time reduced CrI when the moisture content was between 1% and
50% (Table 11). Thus cryogenic grinding offers a good way of reducing the
cellulose crystallinity of wood with a moisture content well above the fibre
saturation point, which seems not to be possible under ambient conditions.
Consequently, it seems that the presence of bound, and more especially unbound,
water in Norway spruce wood plays a crucial role in protecting the crystalline
cellulose from destruction when exposed to double impacts. This protective
capability seems to be lost when the water is in a solid state during milling.
84
Table 11. Crystallinity indices of oscillatory ball milled wood samples. Modified from
Paper IV, published by permission of De Gruyter.
Conditions Milling time
(min)
CrI (%) when the moisture content of the feed was
50% 27% 17% 8% 1%
01 39 39
Ambient 10 35 32 20 10 -5
30 34 33 -21
Cryogenic 10 24 21 30 26 10
30 10 -1 -9
1 Milling time of 0 min refers to the feed
Fine grinding of moist Norway spruce wood was also tested with a high-speed
rotor impact mill and a fluidised bed opposed jet mill, but it was found that the
wood agglomerated in front of the feeding screw until it totally obstructed the
feed. Agglomeration was also observed in oscillatory ball milling, where the
samples of wood with a moisture content above 44% formed pancake-shaped
agglomerations at the end wall of the grinding chamber during milling. It was
possible to disperse these agglomerates, however, when preparing diluted samples
for the analyses, but this had to be helped along mechanically with a glass stick
prior to agitation with a magnetic stirrer. Agglomeration of moist wood in dry
grinding have also been reported by Gravelsins (1998) in Szego milling
experiments, where it was observed that moist wood particles of size below 150
µm agglomerated to form larger particles.
5.3.2 Mild torrefaction
The correlations between Δ* and d50 for dried and torrefied samples ground for
different periods of time are shown in Fig. 31. Mild torrefaction had an
insignificant influence on Δ* as a function of d50, and when the mass loss (ML)
was less than 0.2% it had no influence on d50 as a function of ET. Torrefaction
involving an ML over 1.4%, however, reduced the ET needed for obtaining a given
median particle size over 17.4 µm (± 0.2 µm) (Fig. 32). Specific energy
consumptions for the setups REF, TOR B and TOR C are listed in Table 12,
which indicates that a smaller median particle size was obtained with a similar
SECOSC when torrefaction pretreatment was more intensive and the median
particle size was over 17.4 µm. In the TOR C experiments where d50 was similar
or smaller than in the REF experiments the specific energy consumption
decreased by approximately 21–33% following TOR C pretreatment when the
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targeted d50 was between 18.7 µm (± 0.5 µm) and 79 µm (± 3 µm) (Table 12), but
once ET = 3422 J was reached the differences in d50 between the REF, TOR B and
TOR C experiments became insignificant. When ET increased above 3422 J no
significant decreases in d50 were observed (Fig. 32). There is therefore a certain
particle size range in which torrefaction pretreatment cannot improve the energy
efficiency, and this coincides with the smallest particle size range obtained with
dried samples, i.e. 13–20 µm (see Section 5.1.3). Also the minimum median
particle size obtained with torrefied samples, 12.9 µm (± 0.6 µm) (Table 12), is
not significantly lower than the minimum median particle size of 13 µm reported
in Section 5.1.3. The reason for this is thought to be agglomeration of the globular
shaped particles and increased viscoelasticity of the wood when milling down to
d50 values below 20 µm, as reported and discussed in Section 5.1.3. Mild
torrefaction did not influence the median aspect ratio when ET was over 1000 J
(Fig. 33a), but when it was below 1000 J the differences in AR50 between the REF
and torrefied samples were fairly small (Fig. 33a). According to Fig. 33b, the
differences between the REF and torrefied samples were insignificant when
considering ΔAR as a function of d50. Mild torrefaction with an ML up to 2.8% had
a negligible effect on CrI when considering between REF and TOR C results
obtained with similar ET values or milling times (Table 13).
Media milling is considered a good pretreatment of wood for enzymatic
hydrolysis because of its ability to destroy the cell walls and reduce cellulose
crystallinity (see Section 2.3.2). Torrefaction provides a good way of lowering the
energy consumption required for obtaining a certain particle size, although special
care has to be taken not to process the material for longer than is needed to obtain
the limiting particle size, because the energy benefits due to torrefaction can be
lost.
86
Fig. 31. Effect of mild torrefaction on the median particle size d50 as a function of ∆*.
Modified from Paper V, published by permission of De Gruyter.
Fig. 32. Effect of mild torrefaction on the median particle size d50 as a function of the
total available impact energy of the grinding ball, ET. Modified from Paper V, published
by permission of De Gruyter.
Table 12. Specific energy consumption and median particle sizes in the REF, TOR B
and TOR C experiments. Paper V, published by permission of De Gruyter.
SECOSC (kJ g-1) d50 (µm)
REF TOR B TOR C
0.26 - 115 ± 6 79 ± 3
0.34 94.0 ± 1.1 53 ± 8 41 ± 5
0.51 44 ± 3 35 ± 3 32.6 ± 0.6
0.68 30 ± 3 26.6 ± 1.4 24.6 ± 0.7
0.86 23.3 ± 1.1 19.9 ± 0.8 18.7 ± 0.5
1.20 19.8 ± 1.0 17.0 ± 0.2 17.4 ± 0.2
1.71 13.8 ± 0.4 13.6 ± 0.4 12.9 ± 0.6
2.57 16.0 ± 0.0 14.5 ± 1.2 14 ± 2
87
Fig. 33. Effect of mild torrefaction on a) AR50 and b) ∆AR as a function of the total
available impact energy of the grinding ball. Modified from Paper V, published by
permission of De Gruyter.
Table 13. Comparison of CrI and d50 between REF and TOR C pretreated samples when
pulverised for various lengths of time. Paper V, published by permission of De
Gruyter.
Milling time (min) ET (J) REF (ML = 0.0%) TOR C (ML = 2.8%)
CrI (%) d50 (µm) CrI (%) d50 (µm)
0 0 44 ± 2 < 4000a 42.3 ± 0.3 < 4000a
2 684 28 ± 2 94.0 ± 1.1 27 ± 3 41 ± 5
3 1027 17 ± 3 44 ± 3 15.5 ± 1.2 32.6 ± 0.6
5 1711 11 ± 4 23.3 ± 1.1 9 ± 4 18.7 ± 0.5
a Feed was screened with a 4 mm sieve
88
89
6 Conclusions
Fine grinding of dry Norway spruce wood was studied using three types of fine
grinding mills in which particle breakage takes place due powerful impacts: two
types of non-media mill, known as the air classifier mill and the fluidised bed
opposed jet mill, and one vibration-type media mill known as the oscillatory ball
mill. These milling techniques proved capable of reducing the median particle
size of dried Norway spruce wood to below 25 µm.
The impact events occurring in the media mill were capable of producing
very fine wood powders from dried Norway spruce that had a lower cellulose
crystallinity and rounder shaped particles with a more uniform shape distribution
than in dried Norway spruce wood pulverised to a similar particle size range by
impact events occurring in non-media mills. In the case of the air classifier mill
and fluidised bed opposed jet mill the speed of the classifier had the strongest
effect on the physical properties of the resulting wood powders, whereas with the
oscillatory ball mill the amount of feed, the weight of the grinding ball and the
oscillation frequency had a significant influence on the physical properties of the
wood. When Norway spruce wood was ground to a median particle size of less
than 20 µm the use of more energy intensive impacts resulted in agglomeration
and increased the temperature of the wood during further processing. Although
the prolongation of media milling led to no further decrease in particle size, the
wood particles continued to become rounder and more homogeneous in shape.
The classifier speed had the greatest effect on the energy consumption in air
classifier and opposed jet milling, with a higher rotor speed in the air classifier
mill and a higher grinding pressure in the opposed jet mill yielding an increase in
the production rate when all the other operational parameters were kept constant.
In the air classifier mill the specific electrical energy consumption for attaining a
certain median particle size could be lowered by increasing the rotor speed, while
in the opposed jet mill an increase in grinding pressure reduced the specific
energy consumption but increased the eventual fineness when milling to a median
particle size around 20 µm. The energy consumption in oscillatory ball milling
was affected by the amount of feed, in that a very low feed volume resulted in
poor energy efficiency and an alteration in particle size reduction behaviour
during milling. In the fluidised opposed jet mill the energy requirement for
compression of the grinding air was over 32 kJ g-1 (approx. 9000 kWh t-1) when
pulverising dried Norway spruce wood with a median particle size of 199 µm (± 6
µm) down to a size between 48.2 µm and 69.2 µm. In the air classifier mill dried
90
Norway spruce wood with a median particle size between 1 mm and 2 mm was
pulverised down to 23.8 µm with a specific energy consumption of 15.5 kJ g-1
(4310 kWh t-1). Further optimisation would be possible in both mill types. A
practical estimate for the minimum specific energy consumption in the impact-
based media milling of dried Norway spruce wood, ignoring energy losses in
driving the machine and additional equipment, would be that the median particle
size could be reduced from 1–2 mm down to 100 µm with 0.36 kJ g-1 (100 kWh t-
1) and down to 20 µm with 1.4 kJ g-1 (380 kWh t-1). The total energy consumption
in media mills is higher than this, however, due to the consumption of energy that
is not directed at the particles, a source of energy loss that is significantly
influenced by the architecture of the mill.
Cryogenic grinding conditions can be used in impact-based media milling to
obtain different powders from Norway spruce wood from those produced under
ambient grinding conditions. Also, the energy efficiency of fine grinding can be
enhanced by choosing cryogenic instead of ambient grinding conditions. Wood
powders with a median particle size significantly lower than 13 µm were obtained
when milling under cryogenic conditions, whereas this was not possible under
ambient grinding conditions, and the reduction of cellulose crystallinity in an
impact-based media mill exhibits a different behaviour pattern as a function of
milling time under cryogenic in comparison to ambient conditions. On the other
hand, moisture content has a stronger influence on the size and shape of the
resulting particles when grinding is performed under ambient conditions. Thermal
pretreatment by torrefaction can reduce the energy consumption required in
impact-based media mills for attaining a certain particle size, provided that the
targeted median particle size is not below 17.4 µm (± 0.2 µm). The specific
energy consumption was typically reduced by more than 21% when the mass loss
due to torrefaction was 2.8%. The shape of the particles and their cellulose
crystallinity are not significantly affected by torrefaction pretreatment when
considering similar levels of energy consumption and torrefied samples having a
mass loss due to torrefaction of 2.8% or less.
The present findings suggest that the impact-based fine grinding of dried
wood should be divided into media and non-media milling processes, depending
on the final product. Media milling involves double impacts, which favour
lowered cellulose crystallinity and rounder shaped particles by comparison with
non-media mills. On the other hand, media mills can be used to obtain similar
kinds of wood powders as produced with non-media mills, but then the raw
material has to be moist rather than dry, which can cause different problems in
91
processing. These processing problems and the energy consumption required for
drying could be avoided by preferring cryogenic grinding conditions, but this also
has a specific effect on the properties of the product. The fine grinding of Norway
spruce wood with a median particle size in the millimetre region down to around
20 µm should be possible with an energy consumption of several hundred
kilowatt-hours per tonne, but further optimisation work would be needed to
achieve this specific energy consumption on an industrial scale. The fine grinding
of wood to a median particle size below 20 µm should be considered with
extreme caution, because the resistance of Norway spruce wood, for example, to
particle size reduction increases quite suddenly in this particle size region and can
lead to the formation of agglomerations.
92
93
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Original Publications
I Karinkanta P, Illikainen M, Niinimäki J (2012) Pulverisation of dried and screened Norway spruce (Picea abies) sawdust in an air classifier mill. Biomass and Bioenergy 44: 96–106.
II Karinkanta P, Illikainen M, Niinimäki J (2014) Effect of different impact events in fine grinding mills on the development of the physical properties of dried Norway spruce (Picea abies) wood in pulverisation. Powder Technology 253: 352–359.
III Karinkanta P, Illikainen M, Niinimäki J (2013) Impact-based pulverisation of dried and screened Norway spruce (Picea abies) sawdust in an oscillatory ball mill. Powder Technology 233: 286–294.
IV Karinkanta P, Illikainen M, Niinimäki J (2013) Effect of grinding conditions in oscillatory ball milling on the morphology of particles and cellulose crystallinity of Norway spruce (Picea abies). Holzforschung 67(3): 277–283.
V Karinkanta P, Illikainen M, Niinimäki J (2014) Effect of mild torrefaction on pulverization of Norway spruce (Picea abies) by oscillatory ball milling: particle morphology and cellulose crystallinity. Holzforschung 68(3):337–343.
Reprinted with permission from Elsevier (I–III) and De Gruyter (IV–V).
Original publications are not included in the electronic version of this thesis.
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505. Tuovinen, Tommi (2014) Operation of IR-UWB WBAN antennas close to humantissues
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513. Suopajärvi, Hannu (2014) Bioreducer use in blast furnace ironmaking in Finland :techno-economic assessment and CO2 emission reduction potential
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515. Kulju, Timo (2014) Utilization of phenomena-based modeling in unit operationdesign
C516etukansi.kesken.fm Page 2 Tuesday, December 2, 2014 11:22 AM
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DRY FINE GRINDING OF NORWAY SPRUCE (PICEA ABIES) WOOD IN IMPACT-BASED FINE GRINDING MILLS
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