particale properties notes

7/27/2019 Particale properties notes

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Chapter 1

Characterization Of Individual Particles

Cedric Briens April 16, 2010


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1. Introduction

1.The design of any operation involvingparticles requires precise information on

their properties2.The most important properties are density,

size and shape

3.This chapter defines these properties andreviews the techniques for theirmeasurement


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Outline

1 Introduction

2 Particle density

3 Particle size

4 Particle shape

5 Adhesion of particles6 Dustiness


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2. Particle density

Skeletal density

Apparent particle density

Bulk density


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What is the Skeletal density?

Density of the material from which particles

are formed: rsk

non-porouss

non-porouss


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What is the

apparent particle density?

non-porouss

p

mass of particle

volume of particle (including pores)r

non-porouss


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Relationship between rpand rsk

p

p sk

1 1

r rvolume of solid material volume of pores

solid mass

volume of solid material volume of pores

solid mass solid mass


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What is the bulk density?

Density of the bulk

powder: includes the voids in-

between the particles


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Relationship between rb= rp

b p 1r r

: voidage or volume fraction of bulk powder

occupied byvoids.

mass of solid mass of solid volume of bed volume of voids

volume of bed volume of particles volume of bed


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Example:

fluidized cracking catalyst

rsk= 2500 kg/m3

p= 0.50x10-3m3/kg

rp= 1100 kg/m3

rb= 500 kg/m

3


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Bulk density measurement

The bulk density depends on how the powder

is packed

Two extremes:

Loose or aerated bulk density

Compact or tapped bulk density


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Bulk density measurement


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Loose or aerated bulk density


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Compact or tapped bulk density


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Skeletal density measurement

Two pycnometry measurement techniques

may be used:

1) liquid pycnometry: inaccurate

2) gas pycnometry: elaborate but accurate


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Liquid pycnometry


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Liquid pycnometry

weighing mass of added water volume of added water

volume of flask volume of added water volume of solids material


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Liquid pycnometry


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Liquid pycnometry

Porous particles:

The liquid may

not fill allthe

pores


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Gas pycnometry


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Particle density measurement

1) Mercury pycnometry: assume that

mercury does not penetrate into the pores(Mercury is sometimes replaced bysilicone oil).Inaccurate

2) Caking detection: caking occurs whenthe pores are filled with liquid.Inaccurate

3) Gas adsorption isotherms


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Outline

1 Introduction

2 Particle density

3 Particle size

4 Particle shape

5 Adhesion of particles

6 Dustiness


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FCC


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FCC

tertiarycyclone

catch


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Talcumpowder


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Polymer C


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Polymer W


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Polymer E


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Characterizing the size of a

particle with a complex shape

Volume-equivalent particle diameter: diameter of

the sphere which has the same volume as the particle

Others:

Aerodynamic diameter: diameter of the sphere with a density of

1000 kg/m3

which falls at the same speed as the particle in ambientair

Sieve diameter

Diameters based on projected area


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Particle size cuts

Size cut i contains

the particles with a

diameter between

dpi- Ddpi/2

and

dpi+ Ddpi/2

particle diameter (dp), m

0 50 100 150 200 250 300 350 400 450 500 550 600

fraction

ofparticles

in

size

cut(x i)

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

0.18

ximay be based on:weight

volume

area

number


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Mean diameters

pam i pi i

i i

plm i pi

i

i

i

i

psm pi

: d x d (note : x 1)

: ln d x ln d

For the arithmetic and log mean diameters, x may be any type of fracti

arithmetic mean

geometric or log mean

Sauter me

on

For the , x be the volume fracmu tist on :

1 x

an

d d

diameter

i

S di d


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Sauter-mean diameter and

specific area

p psm

p psm

mean specific surface (a):

particle surface in 1 kg of mixed size solids

6spherical particles: a

d

6non-spherical particles: a

d

r

r


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Median particle diameter

Diameter such that 50% of particles are

larger than this diameter and 50% aresmaller

The median diameter depends on the type of

fraction xi


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Comparison of various mean diameters for a typical size distribution

arithmetic mean diameter, m 221

from log-mean or geometric mean diameter, m 168

volume % harmonic or Sauter mean diameter, m 99

median diameter, m 192

arithmetic mean diameter, m 1.3

from log-mean or geometric mean diameter, m 1.0

number % harmonic mean diameter, m 0.9

median diameter, m 0.8


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Cumulative distribution


0 100 200 300 400 500 600

weigh

t%

withadiametersmallerthandp

0

10

20

30

40

50

60

70

80

90

100


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Differential distribution


0 100 200 300 400 500 600

derivative,wt%

/m

0.0

0.1

0.2

0.3


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Relationship between number and

weight distributions

Use Excel (or FBMODX)


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Combining two particle size

distributions of the same sample

For example, two measurement techniques

may provide the size distribution of asample for 2 different ranges of particle size

The easiest way is to use the cumulative

distribution


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Theoretical size distribution

functions

Useful for smoothing and interpolation

Do notuse for extrapolation


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Normal or gaussian distribution

p

2

pi pam2

d

p pi0

d dexp2

F(d ) d(d )

2


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Log-normal distribution

F d

d

d

d dd

p

pi

plm

g

g

pi

pi

dp( )

expln

ln

ln

( )

2

2

0

2

2


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Rosin-Rammler distribution

s

pp daexp1)d(F


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Weibul distribution

pm

minpp

d

ddX

Xexp1dF p


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Normal paper

If the distribution is gaussian, thecumulative distribution

will plot as a straight line


0 100 200 300 400 500 600

weight%withadiametersmaller

thandp

0.001

0.01

0.1

1

10

30

50

70

90

99

99.9normal probability paper


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Log-normal paper

If the distribution is log-normal, thecumulative distribution

will plot as a straight line.


1 10 100

weight%w

ithadiametersmalle

rthandp

0.001

0.01

0.1

1

10

30

50

70

90

99

99.9log-normal probability paper


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Particle size measurement

Accurate sampling is a crucial operation: moreerrors can be attributed to sampling than to theactual size analysis.

The two "golden rules of sampling" (Allen):

1) "a powder should be sampled while in motion" (toprevent segregation in non- moving powders)

2) "the whole of the stream should be taken for manyshort increments of time in preference to part of the

stream being taken for the whole of the time"(segregation).

With fine particles, sample dispersion is alsoimportant.


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i l i


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i l i


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Various methods:

1) Sieving: usually for dp> 50 m

2) Sedimentation or centrifugation in a liquid

3) Centrifugation in a gas

4) Elutriation

5) Impaction

6) Electrical conductivity7) Light scattering and blockage

8) Image analysis


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Sieving

Si i


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Sieving

Si i


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Sieving

time consuming shaking duration must be long enough to prevent

large errors

cannot be used with solids which attrit oragglomerate easily

if angular particles, does not give volume-equivalent diameter

Sieving results are often reported in terms of meshnumbers: a large mesh number means a small

particle size

Li h i


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Light scattering

The most popular technique

Measures the projected area of the particles and

thus provides the volume-equivalent diameterwhen the measurement cell is designed so as to

present the particles in a random orientation

Measures particle diameters from 0.5 to 3000 m

Both dry and wet measurements


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Dry methods: screening,elutriation,centrifugation in a gas, impaction, light

scattering

A frequent problem with these methods:

Particle-particle agglomeration due to Van der

Waals or electrostatic forces

Prevalent for small particles (high surface/volume)

Additives can help

h d


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Wet methods:sedimentation/centrifugation, electrical

conductivity, light scattering

Particle-particle agglomerates can be broken apartby a combination of surfactant additives and

ultrasonic vibrations

Surfactants may also promote agglomeration

Ultrasonic vibrations may promote agglomeration

or break particles


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Outline

1 Introduction

2 Particle density

3 Particle size

4 Particle shape


6 Dustiness


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4. Particle shape

Introduction

Various shape factors

Shape factors from direct shape characterization

Shape factors from particle-fluid interactions

Shape factors from product quality tests

Measurement of particle shape

P ti l h l


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Particle shape: examples

- inks, paints, cosmetics: flaky particles cover morearea

- abrasives: better if highly angular

- fibers for plastics reinforcement: elongated forgood impact strength.

- rubber grains: must be round for good tensile

strength (otherwise, grains would align along onedirection and eventually tear)

- perfectly spherical particles have a smoother feelattractive for cosmetic applications

Shape factors from direct shape


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Shape factors from direct shape

characterization

Usually from image analysis

Example: for each particle, draw diameters

through its center of gravity, 30 degrees apart,and take the ratio of the smallest to the largestof these diameters

surface area of sphere with the same volume as the particle

actual surface area of the particle

Particle sphericity:


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Shape factors from particle-fluid

interactions

Many shape factors based on measured

particle-fluid interactions

See the chapter on Particulate-Fluid

interactions


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Shape factors from product

quality tests Flakiness index

round particles:

"flaky" particles:

Angularity index: based on Hausner ratio:

Angular particles are more cohesive


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Outline

1 Introduction

2 Particle density

3 Particle size

4 Particle shape


6 Dustiness


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5. Adhesion of particles

Adhesion of particles on other particles or

on a flat surface may be very important forsome processes

There are very few techniques to

characterize such adhesion (e.g. theturntable)


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Outline

1 Introduction

2 Particle density

3 Particle size

4 Particle shape


6 Dustiness


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6. Dustiness

filter

solidssample

suction

dust

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