synthesis of nanoparticles and nanomaterials · 2017-05-08 · 4.2.4 synthesis of indium (iii)...

Zhypargul Abdullaeva

Synthesis of Nanoparticles and NanomaterialsBiological Approaches

Synthesis of Nanoparticles and Nanomaterials

Zhypargul Abdullaeva

Synthesis of Nanoparticlesand Nanomaterials

Biological Approaches

Zhypargul AbdullaevaDepartment of Materials Science and EngineeringKumamoto UniversityJapan

ISBN 978-3-319-54074-0 ISBN 978-3-319-54075-7 (eBook)DOI 10.1007/978-3-319-54075-7

Library of Congress Control Number: 2017933952

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Contents

Part I Conventional Approaches for Nanoparticlesand Nanomaterials Synthesis

1 General Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

1.1 Introduction to Nanoparticles and Nanomaterials . . . . . . . . . . . . . 3

1.2 Nanomaterials Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

1.2.1 Physical Properties of Nanomaterials . . . . . . . . . . . . . . . . 4

1.2.2 Physico-Chemical Properties of Nanomaterials . . . . . . . . . 7

1.2.3 Chemical Properties of Nanomaterials . . . . . . . . . . . . . . . 9

1.2.4 Biological Properties of Nanomaterials . . . . . . . . . . . . . . . 12

1.3 Nanomaterials Morphology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

1.3.1 Size Parameters and Size Distributions . . . . . . . . . . . . . . . 13

1.3.2 Shape Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

1.4 Overview of General Approaches for Nanoparticles

and Nanomaterials Synthesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

Part II Biological Approaches for Nanoparticlesand Nanomaterials Synthesis

2 Synthesis of Nanomaterials by Prokaryotes . . . . . . . . . . . . . . . . . . . 25

2.1 Synthesis of Nanoparticles by Bacteria . . . . . . . . . . . . . . . . . . . . 25

2.1.1 Synthesis of Gold Nanoparticles . . . . . . . . . . . . . . . . . . . . 25

2.1.2 Synthesis of Iron Based Magnetic Nanoparticles . . . . . . . . 27

2.1.3 Synthesis of Silver Nanoparticles . . . . . . . . . . . . . . . . . . . 35

2.1.4 Theoretical Aspects of Bacterial Cell Cultivation . . . . . . . 39

2.2 Synthesis of Nanoparticles By Viruses . . . . . . . . . . . . . . . . . . . . . 42

2.2.1 Synthesis of Fe Based Nanocomposite

by T4 Bacteriophage Virus . . . . . . . . . . . . . . . . . . . . . . . 44

v

2.2.2 Synthesis of Pt, Au, or Ag Nanoparticles

by Tobacco Mosaic Virus . . . . . . . . . . . . . . . . . . . . . . . . 44

2.2.3 Synthesis of Gold NPs by Virus Mediated Reduction . . . . 46

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

3 Eukaryotic Synthesis of Nanomaterials . . . . . . . . . . . . . . . . . . . . . . . 55

3.1 Synthesis of Nanoparticles by Algae . . . . . . . . . . . . . . . . . . . . . . 56

3.1.1 Gold Nanoplates Synthesized in the Algal Extract . . . . . . . 57


3.2 Synthesis of Nanoparticles by Fungi . . . . . . . . . . . . . . . . . . . . . . 61

3.2.1 Synthesis of Gold NPs by Cell-Free Fungi Extract . . . . . . 61


3.2.3 Synthesis of CdS Nanoparticles . . . . . . . . . . . . . . . . . . . . 68

3.3 Synthesis of Nanoparticles by Yeast . . . . . . . . . . . . . . . . . . . . . . 70

3.3.1 Synthesis of Silver NPs . . . . . . . . . . . . . . . . . . . . . . . . . . 70

3.3.2 Synthesis of Iron Containing Magnetic NPs . . . . . . . . . . . 72

3.3.3 Biosynthesis of Copper NPs by the Yeast

Rhodotorula Mucilaginosa . . . . . . . . . . . . . . . . . . . . . . . . 73

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77

4 Phyto-Synthesis of Nanomaterials . . . . . . . . . . . . . . . . . . . . . . . . . . . 79

4.1 Green Chemistry or Phytonanotechnology . . . . . . . . . . . . . . . . . . 80

4.2 Synthesis of Nanoparticles by Plants and Plant Extracts . . . . . . . . 82

4.2.1 Synthesis of Gold Nanoparticles . . . . . . . . . . . . . . . . . . . . 84


4.2.3 Synthesis of Copper Nanoparticles . . . . . . . . . . . . . . . . . . 93

4.2.4 Synthesis of Indium (III) Oxide (In2O3) Nanoparticles . . . . 93

4.3 Factors Affecting Synthesis of NPs by Plant Extracts . . . . . . . . . . 93

4.4 Theoretical Aspects in Nanoparticles Post-synthetic

Characterizations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100

5 Zoosynthesis of Nanomaterials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103

5.1 Synthesis of Nanoparticles by Marine Sponges . . . . . . . . . . . . . . 104

5.1.1 Biosynthesis of Gold NPs Using Marine Sponges . . . . . . . 105

5.1.2 Synthesis of Silver NPs Using Marine Sponges . . . . . . . . . 107

5.2 Synthesis of Nanoparticles by Oyster Shells . . . . . . . . . . . . . . . . . 111

5.3 Biosynthesis of Silver Nanoparticles by Marine

Invertebrate (Polychaete) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112

5.4 Synthesis of CaCO3 Nanoparticles by Cockle Shell . . . . . . . . . . . 115

5.5 Synthesis of Nanoparticles Using Scallop Shells . . . . . . . . . . . . . 116

5.6 Synthesis of Nanoparticles by Abalone Shells . . . . . . . . . . . . . . . 118

5.7 Synthesis of Nanoparticles from Fish Waste . . . . . . . . . . . . . . . . 122

5.8 Synthesis of Nanoparticles Using Insects . . . . . . . . . . . . . . . . . . . 122

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127

vi Contents

6 Separation of Nanomaterials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129

6.1 Separation of Nanoparticles . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129

6.1.1 Physical Separation Methods for Nanoparticles . . . . . . . . . 130

6.1.2 Sedimentation of Nanoparticles . . . . . . . . . . . . . . . . . . . . 130

6.1.3 Filtration of Nanoparticles . . . . . . . . . . . . . . . . . . . . . . . . 131

6.1.4 Magnetic Field Separation of Nanoparticles . . . . . . . . . . . 134

6.1.5 Evaporation and Crystallization of Nanoparticles . . . . . . . 137

6.1.6 Distillation and Sublimation of Nanoparticles . . . . . . . . . . 138

6.1.7 Chromatographic Separation of Nanoparticles . . . . . . . . . . 141

6.1.8 Centrifugal Separation of Nanoparticles . . . . . . . . . . . . . . 142

6.1.9 Extraction of Nanoparticles . . . . . . . . . . . . . . . . . . . . . . . 145

6.2 Chemical Methods for Nanoparticles Separation . . . . . . . . . . . . . 145

6.2.1 Electrophoresis of Nanoparticles . . . . . . . . . . . . . . . . . . . 145

6.2.2 Selective Precipitation of Nanoparticles . . . . . . . . . . . . . . 148

6.2.3 Acid-Wash Treatment Separation of Nanoparticles . . . . . . 150

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157

7 Purification on Nanomaterials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159

7.1 Purification of Nanomaterials . . . . . . . . . . . . . . . . . . . . . . . . . . . 159

7.1.1 Purification of Gold Nanoparticles . . . . . . . . . . . . . . . . . . 160

7.1.2 Purification of Silver Nanoparticles . . . . . . . . . . . . . . . . . 166

7.1.3 Purification of Colloidal CdTe Nanoparticles . . . . . . . . . . 166

7.1.4 Purification of Colloidal ZnO Nanoparticles . . . . . . . . . . . 169

7.2 Comparison of Purification Methods . . . . . . . . . . . . . . . . . . . . . . 169

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175

8 Characterization of Nanoparticles After Biological Synthesis . . . . . . 177

8.1 Phase Characterization of Nanoparticles . . . . . . . . . . . . . . . . . . . 178

8.1.1 X-ray Diffraction of Synthesized NPs . . . . . . . . . . . . . . . . 178

8.1.2 X-ray Photoelectron Spectroscopy (XPS)

of Synthesized NPs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180

8.1.3 Electron Probe Microanalysis (EPMA)

of Synthesized NPs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181

8.2 Morphological Characterization of Synthesized NPs . . . . . . . . . . . 182

8.2.1 Transmission Electron Microscopy (TEM)

and High Resolution Transmission Electron

Microscopy (HRTEM) Characterizations . . . . . . . . . . . . . 183

8.2.2 Brunauer, Emmett, and Teller Method (BET) . . . . . . . . . . 186

8.3 Spectroscopical Characterization of Synthesized NPs . . . . . . . . . . 187

8.3.1 Fourier Transformed Infra-Red (FT-IR)

Spectroscopy of Au and Ag Nanoparticles . . . . . . . . . . . . 187

8.3.2 UV-Vis. Absorption Spectroscopy

of Au and Ag NPs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193

Copyright Permissions for Acknowledgement . . . . . . . . . . . . . . . . . . . . 197

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205

Contents vii

About the Author

Zhypargul Abdullaeva is Assistant Professor in the

Department of Materials Science and Engineering at

Kumamoto University in Japan. She obtained her

PhD degree from Kumamoto University in 2013.

Her research is focused on synthesis of carbon,

metal based nanomaterials, their characterizations

and applications. She has obtained a high standard

of teaching skills and has contributed to improvement

of teaching methods. Professor Abdullaeva has

authored a number of scientific publications and has

received the gold, silver, and bronze Diploma

Awards in the Chemistry Olympiads. She is also a

member of the Japanese Ceramics Society, Materials

Research Society (MRS), and American Association for the Advancement of

Science (AAAS).

ix

Abbreviations

AFM Atomic force microscope

BET Brunauer, Emmett, and Teller

CTAB Cetyl trimethyl ammonium bromide

EDS Electron diffraction spectroscopy

FESEM Field emission scanning electron microscope

FT-IR Fourier transform infra-red

HRTEM High resolution transmission electron microscope

NPs Nanoparticles

NRs Nanorods

PDDAC Poly diallyl dimethyl ammonium chloride

SEM Scanning electron microscope

STEM Scanning transmission electron microscope

TEM Transmission electron microscope

UV-Vis. Ultraviolet-visual

XPS X-ray photoelectron spectroscope

XRD X-ray diffraction

xi

Part I

Conventional Approachesfor Nanoparticles and Nanomaterials

Synthesis

Chapter 1

General Introduction

This chapter presents a brief introduction on the physical, physico-chemical,

chemical, and biological properties of nanoparticles and nanomaterials, as well as

their morphology including size parameters, size distribution, and shape character-

istics. Methods for the determination of particle size and diameter are explained

using fundamental equations. The general techniques for the synthesis of

nanomaterials and nanopowders are described briefly in Scheme 1.1.

1.1 Introduction to Nanoparticles and Nanomaterials

The terms nanoparticle and nanomaterial are derived from the ancient Greek word

(νᾶνoς, nanos), which means small, dwarf or dwarfish. Usually, objects that are

considered to be nanoparticles are 1–100 nm in size. A Nanomaterial has particlesor constituents of nanoscale dimensions, or it may be produced by nanotechnology

(Oxford Dictionary 2016). “Nanoparticles may be produced in modern synthesis

laboratories using specialized equipment, but they have also existed in nature for a

long time and can be traced back to ancient times” (Heiligtag and Niederberger

2013).

Nanoparticles and nanomaterials have applications in sensors and diagnostics

(Tuantranont 2013), biology and medicine (Salata 2004), aerospace

(Gopalakrishnan 2014), and the industrial sector—electronics, healthcare, chemi-

cal, cosmetics, composites, and energy (Santos et al. 2015). “One of the most

promising and well developed environmental applications of nanotechnology is

water remediation and treatment, in which nanomaterials purify water by various

mechanisms, including adsorption of heavy toxic metals, harmful compounds and

other pollutants, removal and inactivation of pathogens, and transformation of toxic

materials into less toxic compounds” (Ghasemzadeh et al. 2014).

© Springer International Publishing AG 2017

Z. Abdullaeva, Synthesis of Nanoparticles and Nanomaterials,DOI 10.1007/978-3-319-54075-7_1

3

1.2 Nanomaterials Properties

1.2.1 Physical Properties of Nanomaterials

Physical properties of nanomaterials depend on phase, color, thickness, boiling withmelting points, and radioactivity. Mechanical properties of nanomaterials relate to

electrical, optical, magnetic, and thermal parameters (Petrunin 2014). Size affects

both physical and mechanical properties of nanomaterials. Table 1.1 depicts the

physical properties of nanomaterials based on size distribution parameters.

Heat capacity properties for metallic nanoclusters with FFC of structure are

described below. “The heat capacity and behavior of nanomaterials should be taken

into account upon application. Nanostructures of nickel nanoclusters with a diam-

eter of 10 nm had their heat capacity increased 1.5–2 times compared to their bulk

analogs using the fast neutron scattering method”. Fig. 1.1 depicts the melting point

of copper and nickel nanoparticles as a function of size. “The solid lines demon-

strate the calculated dependence of the melting points Тm for copper and nickel

nanoclusters on their diameter D. The dashed lines show melting points of the

macroscopic metallic samples. As seen in Fig. 1.1, the maximum decreases in the

melting points of Cu and Ni clusters are 599 and 818 K, while the minimum

decreases are 175 and 256 K, respectively. A significant decrease in the melting

point (to several 100�) was also found for Sn, Ga, Hg, and colloidal CdS

nanoparticles with diameters of 2–8 nm.

Fig. 1.2 depicts an increase in the heat capacity for Ni and Cu nanoparticles with

an increase of the temperature close to the linear law. It was noted that, at

Т ¼ 200 K, the rise in the heat capacity of the copper nanocluster with D ¼ 6 nm

over its value characteristic of the bulk state was only 10%; for the nickel

nanocluster of the same diameter, it was 13%. Our simulation data for copper

nanoparticles with D ¼ 8 nm at Т ¼ 200 K exceeded the experimental values by

approximately 1.8%”.

The X-ray diffraction (XRD) method is used to identify the phase of

nanomaterials. “Crystalline size and strain are based on calculation of the average

nanocrystalline size using the Debye-Scherer’s formula (Mote et al. 2012):

Scheme 1.1 Basic methods for obtaining nanomaterials (According to Baloyan et al. (2007))

4 1 General Introduction

D ¼ Kλ

βhklcosθð1:1Þ

where, D is crystalline size, K is shape factor (0.9), and λ is wavelength of Cuαradiation. The strain induced in powders due to crystal imperfection and distortion

was calculated using the formula:

ε ¼ βhkl4tanθ

ð1:2Þ

From Eqs. (1.1) and (1.2), it can be confirmed that the peak width from crystallite

size varies as 1/cosθ and strain varies as tanθ. Assuming that the particle size and

strain contributions to line broadening are independent of each other and both have

a Cauchy-like profile, the observed line breadth is simply the sum of Eqs. (1.1) and

(1.2):

Table 1.1 Size dependency of nanomaterials physical properties (Kovtun and Verevkin 2010)

Properties Materials response to the size decrease of a structural element

Phase

changes

Decrease in phase change temperatures including melting

temperature

Kinetic Significantly higher anomalous coefficient values for diffusion, heat capacity and

decrease in thermal conductivity

Electrical Increase in electrical resistance, growing in dialectical

conductivity

Magnetic Growth in coercive force, magnetic resistance, appearance of

superparamagnetism

Mechanical Rise in yield strength, hardness, toughness, wear resistance, manifestation of

superplasticity at higher temperatures

Fig. 1.1 Melting point as a function of the diameter of Cu and Ni clusters (Gafner et al. 2015,

reproduced with permission of Springer)

1.2 Nanomaterials Properties 5

βhkl ¼Kλ

Dcosθþ 4ε tanθ ð1:3Þ

The generalized Hooke’s law refers to the strain, keeping only the linear

proportionality between the stress and strain, i.e., σ ¼ E. Here, the stress is

proportional to the strain, where the constant of proportionality, E, is the modulus

of elasticity or Young’s modulus. In this approach, theWilliamson-Hall equation ismodified by substituting the value of ε in the rearranged Eq. (1.3), and we get Ehkl

— a Young’s modulus in the direction perpendicular to the set of the crystal lattice

plane (hkl)”:

βhklcosθ ¼ Kλ

Dþ 4sinθσ=Ehkl ð1:4Þ

Nanocrystalline materials are characterized by a “microstructural length or grainsize of up to about 100 nm. When the grain size is below a critical value

(~10–20 nm), more than 50 vol.% of atoms are associated with grain boundaries

or interfacial boundaries. Grain growth is also a crucial factor for thermal stability

of nanocrystalline solids, which is in most cases determined as a function of

temperature (Tjong and Chen 2004):

d1=n � d1=n0 ¼ kt ð1:5Þ

where, n is the grain growth exponent (typically n�0.5), k is sensitive to the

temperature of annealing and can be expressed by an Arrhenius type” Eq. (1.6):

Fig. 1.2 Temperature dependence of the molar heat capacity for copper and nickel nanoclusters

(Gafner et al. 2015, reproduced with permission of Springer)


k ¼ k0 exp � Q

RT

� �ð1:6Þ

1.2.2 Physico-Chemical Properties of Nanomaterials

Nanoparticles form colloidal solutions, dispersions, and aggregates related to their

physico-chemical properties. A stable dispersion of nanoparticles in a liquid is

called a colloidal system or colloidal dispersion. A “colloidal dispersion or a sol is

one phase (the solid) homogeneously distributed in another phase (the water).

Dispersion has to be strictly separated from the process of dissolution. The term

colloid applies to particles or other suspended material in the 1 nm–1 μm size range.

In colloid chemistry, a stabilized dispersion (kinetically stable when dispersed overa long time but still thermodynamically unstable) describes a liquid where the

particles may collide by Brownian motion or shear flow. A colloidal dispersion

always tends to aggregate and separate; however, the process may be slow (hours-

days), so that the dispersion appears to be virtually stable. The particle–particle

collisions originate from three fundamental processes: Brownian motion of parti-

cles leading to perikinetic aggregation; particles traveling at different velocities in a

shear flow experience orthokinetic (shear) aggregation; and particles of different

size or density undergo differential settling. The nanoparticles in the dispersion

diffuse by Brownian motion; temperature and the particle number concentration

(e.g., number of particles 1�1) determine the particle–particle collision frequency.

For spherical particles and collisions between particles and aggregates that are not

too different in size the resulting perikinetic aggregation can be described by the

Smoluchowski equation (Handy et al. 2008):

dNT

dt¼ �kaN

2T with ka ¼ 4kBT

3ηð1:7Þ

where, NT – total number concentration of primary particles and aggregates, ka –rate constant, kB – the Boltzmann constant, T – temperature, η – the dynamic

viscosity, and t – time.

However, this simplification does not take into account effects which stabilize

colliding particles, resulting in a collision efficiency <1. The stabilization origi-

nates from forces between the particles (Fig. 1.3 a, b). The particles affect each

other by attractive and repulsive forces that act on different length scales (fractions

of nanometers to several nanometers). The forces usually accounted for are Borne

repulsion, diffuse double layer potential, and van der Waals forces.

These forces behave in line with the DLVO theory. The DLVO theory, devel-

oped and named by Derjaguin and Landau (1941) and Verwey and Overbeek

(1948), balances the attractive and repulsive forces acting on two closely adjacent

particles” (Handy et al. 2008).


“DLVO theory is based on the assumption of unstable lyophobic sols, and that

their persistence is kinetic in nature. Stability in this case can be interpreted

practically as a zero rate coagulation” (Derjaguin et al. 1987).

Fig. 1.3 (a) schematic diagram showing the electrical double layer (EDL) on the surface of a

particle, with the different potentials to be considered and the Debye length 1/j which is the length

where the potential has fallen to a value of 1/e of the Stern potential. An increased ionic strength

(addition of salt ions) will cause additional charge screening of the surface and effectively

compress the EDL. The Debye length can range between fractions of a nm (seawater) and nearly

1 μm (ultrapure water) (Handy et al. 2008, reproduced with permission of Springer). (b) Simplified

graph summarizing the DLVO interaction energies and the resulting sum function. The top graphshows a situation where the repulsive forces (e.g., electrostatic charge repulsion) work against the

attractive forces (van der Waals) and an activation energy is required to achieve particle–particle

attachment in either the secondary or primary minimum. The bottom graph shows three possible

situations: fully stabilized system, a system having secondary and primary minimum, and a fully

destabilized system where the energy barrier for attachment in the primary minimum has vanished.

Attachment in the primary or secondary minimum has certain consequences for the reversibility of

attachment: escape from the secondary minimum can be achieved by slight energy input (e.g.,

ultrasonic power) or reduction in ionic strength, escape from primary minimum is often impossible

or can be achieved by charge reversal if attachment was due to opposite charge of particles.

Abbreviations: zeta potential (f), electrostatic potential (w), electrostatic potential at the stern (k).

X is a distance from the surface, Xs is the distance where ions and molecules are mobile and can be

sheared off (shear plane), and potential here is measured as the zeta potential. The diffusion layer

is an unstirred layer of water adjacent to the surface, and the bulk solution is the free moving water

(e.g., seawater, freshwater) (Handy et al. (2008), reproduced with permission of Springer)


1.2.3 Chemical Properties of Nanomaterials

Chemical properties of nanomaterials are determined by their chemical reactivity,

oxidation, surface modification ability, and catalytic effects.

Chemical reactivity is the tendency of a substance to undergo chemical reaction,

either by itself or with other materials, and to release energy (Mc Nutt 1999). The

chemical reactivities of two magnesium nanopowders with different sizes were

studied using nitridation, hydrogenation, and Grignard reactions (Zhang et al.

2001). According to this study, chemical reactivity was proportional to specific

surface area or reciprocal particle diameters, and a summary of obtained results is

given in Table 1.2.Oxidation is a process in which a chemical substance changes because of the

addition of oxygen (Harper Collins Dict. 2016). The “strain-mediated ionic trans-

port method performs strain analysis at the atomic level to obtain the oxidation

mechanism of nanoparticles. It was revealed that strain gradients induced in the

confined oxide shell by the nanoparticle geometry enhance the transport of diffus-

ing species, ultimately driving oxide domain formation and the shape evolution of

the particle” (Pratt et al. 2014). The oxidation behavior of nano-Fe0 particles in an

anoxic environment was determined, and it was found that the presence of contam-

inants enhances oxidation of nano-Fe0 (Kumar et al. 2014).

Surface modification is related to “objectives controlled by means of the strength

of the interaction between the modifier and the substrate surface, which is in turn

controlled by the surface bonding chemistry” (Mc Creery and Bergren 2012). The

ability of nanoparticles to modify their surface can be observed using surfactants

that react with nanoparticles by attachment of functional groups. Fig. 1.4 depicts

surface functionalization of gold nanoparticles (Au NPs) by cethyl trimethyl ammo-

nium bromide (CTAB). Fig. 1.4a–d presents “gold nanoparticles and nanorods

Table 1.2 Magnesium powders of different particle sizes and their chemical reactivities (Zhang

et al. 2001)

Mg

powder

Average

particle

size

Specific

surface

area (m2/g)

Nitridation-

conversion

of Mg to

Mg3N2

in 22 h (%)a

Hydrogenation-

conversion of

Mg to MgH2

in 20 h (%)b

Grignard reaction-

conversion of conversion

of chlorobenzene to

Grignard reagent

in 45 min (%)c

Mg* 76 nm 54 73 30 96.7

Mg# 266 nm 16 26 8.1 29.3

Mg♦ 155 μm 0.022d ~0 ~0 ~0

Nitridation: 0.1 MPaN2, 450 �C. Hydrogenation: 0.1 MPa H2, 230 �C. Grignard reaction:

magnesium/chlorobenzene ¼ 3/1 mole ratio, solvent: THF, 60 �CaCalculated from the amount of nitrogen uptakebCalculated from the amount of dihydrogen uptakecCalculated from the data of GC analysis after hydrolysisdCalculated by taking the commercial magnesium powder as a spherical particle with an average

diameter of 155 μm


(NRs) with various morphologies at 100 nm scale, E depicts UV-absorption spectra

after surface modification of Au NRs by CTAB surfactant” (Jiang et al. 2012).

“Zeta potential as a function of particles surface properties (e.g., surface

functionalization) can be predicted from theoretical models. Large zeta potentials

of like signs maximize the electrostatic repulsive force and, therefore, minimize

aggregation” (Dougherty et al. 2007). The electrophoretic mobility is related to the

Fig. 1.4 Characterization of Au NRs. TEM images of CTAB-coated Au NRs with different ARs

(a) CTAB-1, (b) CTAB-2, (c) CTAB-3, and (d) CTAB-4. (e) Representative UV–vis–NIR

absorption spectra. (f) The relationship between longitudinal plasmonic maximum and calculated

ARs (based on TEM images). The straight line is a linear regression of data points. The inset is

the photograph of the Au NRs suspensions with the order of CTAB-1, CTAB-2, CTAB-3, and

CTAB-4. The scale bar ¼ 100 nm (Qiu et al. 2010, reproduced with permission of Elsevier)


zeta potential ζ by the Helmholtz-Smoluchowski equation (Smoluchowski 1921;

Hunter 2012):

νE ¼ εrεoζ

ηð1:8Þ

and:

νE ¼ 4πεrεoζ

6πμ1þ krð Þ ð1:9Þ

where, εo is the relative dielectric permittivity of free space, εr is the dielectric

constant of the medium, η and μ are the fluid viscosity, r is the particle radius, andk is the Debye–Hückel parameter equal to:

k ¼ 2n0z2e2=εrεokBT

� �1=2 ð1:10Þ

in which, n0 is the bulk ionic concentration, z is the valence of the ion, e is the

change of an electron, kB is the Boltzmann constant, and T is the absolute temper-

ature. “The significance of the ζ-potential for many applications in science and

engineering has led to the development of measuring techniques based on three

electrokinetic effects: electrophoresis, electroosmosis, and the streaming potential”

(Sze et al. 2003).

The catalytic effect of nanoparticles refers to Oswald’s definition stating that

“catalysis is a condition of movement of atoms in a molecule of a labile body which

follows the entrance of the energy emitted from one body into another and leads to

the formation of more stable bodies with loss of energy” (Ostwald 1894). A catalystis any substance that changes the rate of a chemical reaction without appearing in

the final products (Ostwald 1901). Fig. 1.5 depicts the “evolution of the catalytic

activity for aerosol and supported Ni nanoparticles starting from unsintered Ni

Fig. 1.5 Temporal

evolution of the catalytic

activity for aerosol and

supported nanoparticles

(Weber et al. 2006,

reproduced with permission

of Springer)


nanoparticle agglomerates with primary particle diameter equal to 2.2 nm. Fig. 1.5

shows that catalytic activity can be increased as a consequence of particle growth

caused by sintering”.

1.2.4 Biological Properties of Nanomaterials

“Interaction of nanomaterials with biomolecules, cells, and organisms is a tremen-

dous vital area of the current research, with applications in nano-enabled diagnos-

tics, imaging agents, therapeutics, and contaminant removal technologies”

(Murphy and Vartanian 2015). The intracellular delivery and in vivo imaging

ability of CdSe-ZnS biocompatible quantum dots (QD) were described by (Biju

et al. 2008). Anti-angiogenic properties of gold nanoparticles were studied by

(Bhattacharya and Mukherjee 2008), refer to Case Study 1.1 in this book chapter.

“Nano-sized zinc compounds with insulin and high molecular substances foster

prolongation of hypoglycemic drug action in contrast with duration of insulin

effect. A nanostructure with amphotericin-В, which is an antifungal drug of sys-

temic action, decreases the nephrotoxic effect of this pharmaceutical” (Bogutska

et al. 2013). “Antibacterial activity of copper nanoparticles against Micrococcusluteus, S. aureus, E. coli, Klebsiella pneumonia, P. aeruginosa, Aspergillus flavus,A. niger, and Candida albicans” was described by (Ramyadevi et al. 2012). Metal

and metal oxide nanoparticles such as alumina (Al2O3), copper oxide (Cu2O and

CuO), titanium oxide (Ti2O), iron (Fe), iron oxide (Fe2O3), and silver (Ag) showed

antibacterial effect against a number of bacterium colonies (Sachindri and

Kalaichelvan 2011). Such biological properties are based on the “interaction of

nanoparticles with proteins, membranes, cells, DNA, and organelles and

establishing a series of nanoparticle/biological interfaces depending on colloidal

forces as well as dynamic biophysicochemical interactions. This leads to the

formation of protein coronas, particle wrapping, intracellular uptake, and biocata-

lytic processes that could have biocompatible or bioadverse outcomes” (Nel et al.

2009).

1.3 Nanomaterials Morphology

Nanomaterials morphology is the study of form comprising shape, size, and

structure, which is important for materials research in general (Sanyal et al.

2002). “Nanomaterials with unique sizes and structures are expected to find various

novel applications and discovery of novel materials, processes, and phenomena at

the micro- and nanoscale, as well as the development of new experimental and

theoretical techniques for research provide fresh opportunities for the development

of innovative nanosystems and nanostructured materials” (Liu et al. 2010).


1.3.1 Size Parameters and Size Distributions

Nanomaterials possess different size parameters which relate to their physical and

mechanical properties. There are several “methods and commercial techniques to

determine the size and distribution of nanoparticles. In general, particle size can be

determined two ways: the first focuses on the inspection of particle size and making

actual measurements of their dimensions (e.g., microscopic methods), and the

second applies particle behavior and size” (Akbari et al. 2011).

The relation between the number of particles (N ) and the mass fraction (x) for

the same particle size or diameter (D) can be calculated by the relation (Gonzalez-

Tello et al. 2010):

N ¼ M

kρs� x

D3ð1:11Þ

where,M is the powder mass, k is the shape factor with regard to the volume, and ρSis the particle density.

For the case of nanoparticle solutions, “the number of gold nanoparticles NGNP

stabilized in citrate solution can be calculated from the ratio of the number of initial

Au(III) atoms NAu(III) (e.g., 55 mL of 1.14 mM HAuCl4 was used for this study)

and the number of gold atoms per gold nanoparticle NAu/GNP dependent on the

particle diameter D, using the following equation (Hinterwirth et al. 2013):

NGNP ¼NAu IIIð ÞN Au

GNP

¼ 1:14� 10�3molL�1 � 0:055 � L � NA

30:89602D3

¼ 1:2221� 1018D�3 ð1:12Þ

where, NA is Avogadro’s constant (equal to 6.02214086 � 1023 mol�1). From

Eq. (1.12), the molar concentration of gold nanoparticles cGNP in solution can be

further calculated by Eq. (1.13):

cGNP ¼ NGNP

V � NA¼ 3:6898 � 10�5D�3 ð1:13Þ

here, V is the volume of the solution. The extinction coefficient ɛλ(max) according to

the Lambert-Beer law can be determined with the calculated gold nanoparticle

(GNP) concentration by measuring the absorption spectrum. Finally, unknown

concentrations of GNP suspension can be calculated by Eq. (1.14) given below

(where d is the path length of the detection cell):

Aλ maxð Þ ¼ ελ maxð Þ � cGNP � d ð1:14Þ

The diameter, size distribution, and shape of gold nanoparticles are calculated

using the asymmetrical-flow field-flow fractionation analysis (AsFFFA) technique,

1.3 Nanomaterials Morphology 13

which is based on the theory of the Stokes–Einstein law. The diffusion coefficients,

and thus, the hydrodynamic diameters dh of particles can be derived from the

residence time tr according to Eq. (1.15) (Hinterwirth et al. 2013; Wahlund 2013):

dh ¼ trt0� 2 � k � T � V0

π � η � ω2 � Fcross

¼ RL � 2 � k � T � V0

π � η � ω2 � Fcross

ð1:15Þ

where, t0 is the void time, RL is retention level, k is the Boltzmann constant, T is the

absolute temperature, V0 is the geometric volume of the channel (void volume), η isthe viscosity of the fluid, w is the height (thickness) of the channel, and Fcross is the

cross flow”.

1.3.2 Shape Characteristics

Nanoparticles exhibit different kinds of shapes, such as: spherical, rod-like, star,

capsules, triangular, tetragonal, bamboo-like, and so on.

Additionally, the “dynamic light scattering (DLS) technique was applied to

measure the hydrodynamic size of silver nanoparticles and determine the agglom-

eration state of the nanoparticles in water and phosphate buffer (pH 7.0). Table 1.3

depicts DLS sizing data of the differently shaped Ag NPs in water and phosphate

buffer. There was no agglomeration of the Ag NPs in Franz cell donor medium, i.e.,

phosphate buffer” can be seen (Tak et al. 2015).

“Nanoparticle shape is an important and decisive factor in diffusion, permeabil-

ity, carrier, and delivery applications. For example, geometry of nanocarriers

particularly of shape, aspect ratio, and ratio of particle dimensions to vessel

diameter directly affect their margination and cellular internalization” (Caldorera-

Moore et al. 2010).

“Nanoindentation is an important method to study morphology of nanomaterials

based on the local precision immersion to several nanometers of the probe on the

specimen surface and continuous registration of kinetic characteristics by ongoing

efforts” (Cherkasova et al. 2013). The Oliver and Pharr method was applied for

nanoindentation hardness determination of silica nanoparticles based on the fol-

lowing relation (Zou and Yang 2006):

H ¼ Pmax

A hcð Þ ð1:16Þ

here, Pmax is the peak indentation load, A(hc) is the contact area at the contact depth,hc, under peak indentation load.

Table 1.4 presents the values of parameters characterizing unloading curves as

observed in nanoindentation experiments with a Berkovich indenter (Oliver and

Pharr 2004).


synthesis of nanoparticles and nanomaterials · 2017-05-08 · 4.2.4 synthesis of indium (iii)...

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