nano materials powder

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Advanced nanomaterials

Cours support

This text is also partially used for the cours

“Introduction to Nanomaterial”

H.Hofmann

Powder Technology Laboratory

IMX

EPFL

Version 1 Sept 2009


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Contents

1 INTRODUCTION 6

1.1 WHAT ARE NANOMATERIALS? 6

1.1.1 CLASSIFICATION OF NANOSTRUCTURED MATERIALS 6

1.1.2 WHY SO MUCH INTEREST IN NANOMATERIALS? 8

1.1.3 INFLUENCE ON PROPERTIES BY "NANO-STRUCTURE INDUCED EFFECTS" 9

1.2 SOME PRESENT AND FUTURE APPLICATIONS OF NANOMATERIALS 10

1.3 WHAT ARE THE FUNDAMENTAL ISSUES IN NANOMATERIALS? 13

2 ATOMS, CLUSTERS AND NANOMATERIALS 15

3 NANOCOMPOSITES SYNTHESIS AND PROCESSING 19

3.1 INTRODUCTION 19

3.2 INORGANIC NANOTUBES 20

3.2.1 INTRODUCTION 20

3.2.2 GENERAL SYNTHETIC STRATEGIES 26

3.3 FUNCTIONAL MATERIALS BASED ON SELF-ASSEMBLY OF POLYMERIC SUPRAMOLECULES 28

3.4 MOLECULAR BIOMIMETICS: NANOTECHNOLOGY THROUGH BIOLOGY 32

3.4.1 SELECTION OF INORGANIC-BINDING PROTEINS THROUGH DISPLAY TECHNOLOGIES 34

3.4.2 CHEMICAL SPECIFICITY OF INORGANIC-BINDING POLYPEPTIDES 36

3.4.3 PHYSICAL SPECIFICITY OF PEPTIDE BINDING 37

3.4.4 PEPTIDE-MEDIATED NANOPARTICLE ASSEMBLY 38

3.5 REFERENCES 40

4 MECHANICAL PROPERTIES 41

4.1 INTRODUCTION 41

4.2 METALS 41

4.2.1 GRAIN SIZE EFFECTS IN PLASTICITY AND CREEP 42

4.2.2 METAL PLASTIC DEFORMATION: A COMPARISON BETWEEN CU AND NI NANOPHASE SAMPLES

49 4.2.3 HARDNESS 53


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4.3 CERAMICS / NANOCOMPOSITES 56

4.3.1 DENSITY 56

4.3.2 FRACTURE STRENGTH 56

4.3.3 STRENGTHENING AND TOUGHENING MECHANISMS 58

4.3.4 REDUCTION IN PROCESSING FLAW SIZE 60

4.3.5 CRACK HEALING (ANNEALING TREATMENT) 60

4.3.6 TOUGHENING (K -MECHANISMS) 61

4.3.7 GRAIN BOUNDARY STRENGTHENING MECHANISMS 63

4.3.8 THERMAL EXPANSION MISMATCH (SELSING MODEL) 63

4.3.9 AVERAGE INTERNAL STRESSES 64

4.3.10 LOCAL STRESS DISTRIBUTION 67

4.4 FINAL REMARKS ON STRENGTHENING AND TOUGHENING MECHANISMS 67

4.5 REFERENCES 69

5 THERMAL CONDUCTIVITY IN NANOSTRUCTURED MATERIAL 70

5.1 THERMAL CONDUCTIVITY OF THERMAL BARRIER COATINGS 70

5.1.1 THERMAL CONDUCTIVITY 70

5.1.2 LATTICE WAVES 71

5.1.3 INTERACTION PROCESSES 72

5.2 HIGH-TEMPERATURE THERMAL CONDUCTIVITY OF POROUS AL2O3 NANOSTRUCTURES 76

5.2.1 THEORY 76

5.2.2 EXPERIMENT 82

5.2.3 RESULTS AND DISCUSSION 83

5.3 REFERENCES 88

6 THERMODYNAMIC 89

6.1 NANOTHERMODYNAMICS 89

6.1.1 HILL’S THEORY 90

6.1.2 TSALLIS’ GENERALIZATION OF ORDINARY BOLTZMANN-GIBBS THERMOSTATICS 96

6.1.3 THERMODYNAMICS OF METASTABLE PHASE NUCLEATION ON NANOSCALE 100

6.1.4 NANOTHERMODYNAMIC ANALYSES OF CVD DIAMOND NUCLEATION 112

6.2 THERMODYNAMICS OF MELTING AND FREEZING IN SMALL PARTICLES 117

6.2.1 THEORY – VANFLEET AND AL. MODEL 117

6.3 PHASE DIAGRAMS 128 6.3.1 GOVERNING EQUATIONS 128


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6.3.2 MATHEMATICAL DESCRIPTION FOR NANO-PHASES OF SN-BI ALLOYS 130

6.3.3 PHASE DIAGRAM FOR ISOLATED NANO-PHASES OF SN-BI ALLOYS 133

6.4 CRYSTAL-LATTICE INHOMOGENEOUS STATE 135

6.5 CONCENTRATIONAL INHOMOGENEITY 137

6.6 REFERENCES 140

7 ELECTRONIC AND OPTICAL PROPERTIES OF NANOMATERIALS 141

7.1 INTRODUCTION 141

7.2 METALS 143


7.2.2 ELECTRICAL CONDUCTIVITY 154

7.2.3 SURFACE PLASMONS 162

7.3 CARBON NANOTUBES 171

7.3.1 ELECTRONIC STRUCTURE 172

7.3.2 QUANTUM TRANSPORT PROPERTIES 174

7.3.3 NANOTUBE JUNCTIONS AND DEVICES 178

7.4 SEMICONDUCTOR 181


7.4.2 BAND GAP MODIFICATION 185

7.4.3 ELECTRICAL PROPERTIES 190

7.4.4 OPTICAL PROPERTIES 212

7.5 REFERENCES 217

8 MAGNETISM 219

8.1 INTRODUCTION 219

8.1.1 CONCEPT 219

8.1.2 PHENOMENA 220

8.2 MAGNETIC PROPERTIES OF SMALL ATOMIC CLUSTERS 222


8.2.2 SIZE DEPENDENCE 223

8.2.3 THERMAL BEHAVIOUR 225

8.2.4 RARE EARTH CLUSTERS 226

8.3 SMALL PARTICLE MAGNETISM 226

8.3.1 CLASSIFICATIONS OF MAGNETIC NANOMATERIAL 226 8.3.2 ANISOTROPY 230


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8.3.3 SINGLE DOMAIN PARTICLES 232

8.3.4 SUPERPARAMAGNETISM 239

8.4 MAGNETOELECTRONICS SPINS 252

8.4.1 SPIN-POLARIZED TRANSPORT AND MAGNETORISISTIVE EFFECTS 252

8.4.2 SPIN INJECTION 256

8.4.3 SPIN POLARIZATION 257

8.5 GIANT MAGNETORESISTANCE (GMR) 259

8.6 STORAGE DEVICES 264

8.6.1 MAGNETIC DATA STORAGE : 264

8.6.2 SENSORS: 265

8.7 REFERENCES 266

9 APPLICATIONS 267


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Figure 1-2 : Classification schema for nanomaterials according to their chemical composition and the

dimensionality (shape)of the crystallites (structural elements) forming the nanomaterial. The boundary

regions of the first and second family of nanomaterials are indicated in black to emphasize the

different atomic arrangements in the crystallites and in the boundaries. The chemical composition of

the (black) boundary regions and the crystallites is identical in the first family. In the second family, the

(black) boundaries are the regions where two crystals of different chemical composition are joined

together causing a steep concentration gradient.

The latter three categories can be further grouped into four families as shown in

Figure 1-2.

• In the most simple case (first family in the Figure 1-2), all grains and interfacial

regions have the same chemical composition. Eg. Semicrystalline polymers

(consisting of stacked lamellae separated by non-crystalline region),

multilayers of thin film crystallites separated by an amorphous layer (a-

Si:N:H/nc-Si)iietc.

• As the second case, we classify materials with different chemical composition

of grains. Possibly quantum well structures are the best example of this family.

• In the third family includes all materials that have a different chemical

composition of its forming matter (including different interfaces) eg. Ceramic of

alumina with Ga in its interface.iii


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• The fourth family includes all nanomaterials formed by nanometer sized grains

(layers, rods or equiaxed crystallites) dispersed in a matrix of different

chemical composition. Precipitation hardened alloys typically belong to this

family. Eg. Nanometer sized Ni3Al precipitates dispersed in a nickel matrix-

generated by annealing a supersaturated Ni-Al solid solution- are an example

of such alloys. Most high-temperature materials used in modern jet engines

are based on precipitation-hardened Ni3Al/Ni alloys.

A large part of this definition has been described in an article by Gleiter.iv,v

1.1.2 Why so much interest in nanomaterials?

These materials have created a high interest in recent years by virtue of their

unusual mechanical, electrical, optical and magnetic properties. Some examples

are given below:

• Nanophase ceramics are of particular interest because they are more ductile

at elevated temperatures as compared to the coarse-grained ceramics.

• Nanostructured semiconductors are known to show various non-linear optical

properties. Semiconductor Q-particles also show quantum confinement effectswhich may lead to special properties, like the luminescence in silicon powders

and silicon germanium quantum dots as infrared optoelectronic devices.

Nanostructured semiconductors are used as window layers in solar cells.

• Nanosized metallic powders have been used for the production of gas tight

materials, dense parts and porous coatings. Cold welding properties combined

with the ductility make them suitable for metal-metal bonding especially in the

electronic industry.

• Single nanosized magnetic particles are mono-domains and one expects that

also in magnetic nanophase materials the grains correspond with domains,

while boundaries on the contrary to disordered walls. Very small particles have

special atomic structures with discrete electronic states, which give rise to

special properties in addition to the super-paramagnetism behaviour. Magnetic

nano-composites have been used for mechanical force transfer (ferrofluids),

for high density information storage and magnetic refrigeration.


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• Nanostructured metal clusters and colloids of mono- or plurimetallic

composition have a special impact in catalytic applications. They may serve as

precursors for new type of heterogeneous catalysts (Cortex-catalysts) and

have been shown to offer substantial advantages concerning activity,

selectivity and lifetime in chemical transformations and electrocatalysis (fuel

cells). Enantioselective catalysis were also achieved using chiral modifiers on

the surface of nanoscale metal particles.

• Nanostructured metal-oxide thin films are receiving a growing attention for the

realisation of gas sensors (NOx, CO, CO2, CH4 and aromatic hydrocarbons)

with enhanced sensitivity and selectivity. Nanostructured metal-oxide (MnO2)

find application for rechargeable batteries for cars or consumer goods. Nano-crystalline silicon films for highly transparent contacts in thin film solar cell and

nano-structured titanium oxide porous films for its high transmission and

significant surface area enhancement leading to strong absorption in dye

sensitized solar cells.

• Polymer based composites with a high content of inorganic particles leading to

a high dielectric constant are interesting materials for photonic band gap

structure produced by the LIGA.

1.1.3 Influence on properties by "nano-structure induced effects"

For the synthesis of nanosized particles and for the fabrication of

nanostructured materials, laser or plasma driven gas phase reactions, evaporation-

condensation mechanisms, sol-gel-methods or other wet chemical routes like inverse

micelle preparation of inorganic clusters have been used, that will be discussed later.

Most of these methods result in very fine particles which are more or lessagglomerated. The powders are amorphous, crystalline or show a metastable or an

unexpected phase, the reasons for which is far from being clear. Due to the small

sizes any surface coating of the nano-particles strongly influences the properties of

the particles as a whole. Studies have shown that the crystallisation behaviour of

nano-scaled silicon particles is quite different from micron-sized powders or thin films.

It was observed that tiny polycrystallites are formed in every nano-particle, even at

moderately high temperatures.Roughly two kinds of "nano-structure induced effects " can be distinguished:


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• First the size effect , in particular the quantum size effects where the normal

bulk electronic structure is replaced by a series of discrete electronic levels,

• and second the surface or interface induced effect , which is important because

of the enormously increased specific surface in particle systems.

While the size effect is mainly considered to describe physical properties, the

surface or interface induced effect , plays an eminent role for chemical processing, in

particular in connection with heterogeneous catalysis. Experimental evidence of the

quantum size effect in small particles has been provided by different methods, while

the surface induced effect could be evidenced by measurement of thermodynamic

properties like vapour pressure, specific heat, thermal conductivity and melting point

of small metallic particles. Both types of size effects have also been clearly separated

in the optical properties of metal cluster composites. Very small semiconductor (


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Bulk

Single magnetic domain

Small mean free path of electrons in a solid

Size smaller than wavelength

High & selective optical absorption of metal particles

Formation of ultra fine pores due to

superfine agglomeration of particles

Uniform mixture of different kinds of superfine particles

Grain size too small for stable dislocation

Magnetic recording

Special conductors

Light or heat absorption, Scattering

Colours, filters, solar absorbers,

photovoltaics, photographic

material, phototropic material

Molecular Filters

R&D of New Materials

High strength and hardness of

metallic materials

Surface/ Interface

Large specific surface area Catalysis, sensors

Large surface area, small heat capacity Heat-exchange materials

Combustion Catalysts

Lower sintering temperature

Specific interface area, large boundary area

Superplastic behaviour of ceramics

Cluster coating and metallization

Multi-shell particles

Sintering accelerators

Nano-structured materials

ductile ceramics

Special resistors, temperature sensors

Chemical activity of catalystsTailored Optical elements


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Table 1-2 : Some examples of present and potential applications with significant technological

impact:vi

Technology Present Impact Potential Impact

Dispersions and

Coatings

Thermal barriers

Optical (visible and UV) barriers

Imaging enhancement

Ink-jet materials

Coated abrasive slurries

Information-recording layers

Enhanced thermal barriers

Multifunctional nanocoatings

Fine particle structure

Super absorbant materials (Ilford

paper)

Higher efficiency and lower

contamination

Higher density information storage

High Surface

Area

Molecular sieves

Drug delivery

Tailored catalysts

Absorption/desorption materials

Molecule-specific sensors

Particle induced delivery

Energy storage (fuel cells, batteries)

Grätzel-type solar cells, Gas sensors

Consolidated

Materials

Low-loss soft magnetic materials

High hardness, tough WC/Co

cutting tools

Nanocomposite cements

Superplastic forming of ceramics

Materials

Ultrahigh-strength, tough structural

materials

Magnetic refrigerants

Nanofilled polymer composites

Ductile cements

Bio-medicalaspects

Functionalised nanoparticles Cell labelling by fluorescentnanoparticles

Local heating by magnetic

nanoparticles

Nanodevices GMR read heads Terabit memory and microprocessing

Single molecule DNA sizing and

sequencing

Biomedical sensors

Low noise, low threshold lasers


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Nanotubes for high brightness displays

1.3 What are the fundamental issues in nanomaterials?

The fundamental issues in this domain of nanomaterials are:

(1) ability to control the scale (size) of the system,

(2) ability to obtain the required composition -

not just the average composition - but details such as defects, concentration

gradients, etc.,

(3) ability to control the modulation dimensionality,

(4) during the assembly of the nano-sized building blocks, one should be able to

control the extent of the interaction between the building blocks as well as thearchitecture of the material itself.

More specifically the following issues have to be considered for the future

development of nanomaterials:

• Development of synthesis and/or fabrication methods for raw materials

(powders) as well as for the nanostructured materials.

• Better understanding of the influence of the size of building blocks in nano

structured materials as well as the influence of microstructure on the physical,

chemical and mechanical properties of this material.

• Better understanding of the influence of interfaces on the properties of nano-

structured material.

• Development of concepts for nanostructured materials and in particular their

elaboration.• Investigation of catalytic applications of mono- and plurimetallic nanomaterials

• Transfer of developed technologies into industrial applications including the

development of the industrial scale of synthesis methods of nanomaterials and

nanostructured systems.

In the following chapters we will review the various developments that have been

revolutionising the application of nanomaterials. We will attempt to correlate the


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improvements in the material properties that are achieved due to the fine

microstructures arising from the size of the grains and/or dimensionality.


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2 ATOMS, CLUSTERS AND NANOMATERIALS

atoms

?

?

?

?

?

?

??

?

?

??

molecules cluster nanocrystallites

Figure 2-1 : Schematic representation of various states of matter

At the beginning of last century, increasing attention was focused on the physical

chemistry of colloidal suspensions. By referring to them as "the world of neglected

dimensions", Oswald was the first to realize that nanoscale particles should display

novel and interesting properties largely dependant on their size and shape. vii

However, it is only in the last two decades that significant interest has been devoted

to inorganic particles consisting of a few hundred or a few dozen atoms, called

clusters. This interest has been extended to a large variety of metals and

semiconductors and is due to the special properties exhibited by these nanometer-

sized particles, which differ greatly from those of the corresponding macrocrystalline

material.

Matter that is constituted of atoms and molecules as such, has been widely classified

and satisfactorily explained. However, an ensemble of atoms, or molecules forming

the so-called ‘Clusters’ are far from being properly understood. Elemental clusters

are held together by various forces depending on the nature of the constitutingatoms:

Inert gas clusters are weakly held together by van-der-waals interactions, eg. (He)n

Semiconductor clusters are held with strong directional covalent bonds, eg. (Si)n

Metallic clusters are fairly strongly held together by delocalised non-directional

bonding, eg. (Na)n


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No. Of Shells 1 2 3 4 5

No. of atoms M13 M55 M147 M309 M561

Percentage of

atoms

92% 76% 63% 52% 45%

Figure 2-2 : Idealized representation of hexagonal close packed full-shell ‘magic number’ clusters.viii

Note that as the number of atoms increases, the percentage of surface atoms decreases.

1

10

100

1000

10000

100000

0 10 20 30Cluster size (nm)

T o t a l n o . o f a t o m s

(1)

0

20

40

60

80

100

120

0 5 10 15 20 25Size of cluster (nm)

S u r f a c e a t o m s ( % )

(2)

Figure 2-3 : (1) Total Number of atoms with size of the cluster. (2) Number of surface atoms for a

hypothetical model sphere of diameter 0.5 nm and density 1000 Kgm -3 with a mass of 6.5 10-26 Kg

occupying a volume of about 6.5 x 10-29 m3 with a geometrical cross-section of 2 x 10-19 m2 (in terms of

atomic mass the sphere is considered to have a mass of 40 amu, where 1 amu = 1.67 x 10 -27 Kg).

Calculated by (a) considering dense structures (Square), ix and (b) method suggested by Preining (dark

circle).

x

Either elemental clusters or a mixture of clusters of different elements constitute the

vast expanding field of materials sciences called ‘nanomaterials’. One has to be clear

right at this stage that clusters are not a fifth state of matter, as sometimes believed,

but they are simply intermediate between atoms on one hand, and solid or liquid

state of matter on the other, with widely varying physical and chemical properties.

Depending on the number of atoms forming the cluster determines the percentage of

atoms that are exposed on the surface of the cluster. An example of such anensemble of metal atoms show the decreasing number of surface atoms with


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increasing size of the cluster as shown in fig: . When an ensemble of atoms add up to

form a few nanometer sized clusters, they form what we call ‘nanoparticles’, since

only a few atoms forming clusters are called ‘molecular clusters’. Agglomeration of a

few atoms have been studied in great details by physicists working with molecular

beams. Today, the mystery related to larger ensemble of atoms (in other words

‘nanomaterial’) are getting clearer due to active research being carried over across

the world over the last decade or two.

Table 2-1 : Idealized representation of the variation of cross section, total mass, number of molecules

and the effective surface atoms in clusters. Note (a) considering dense structures (Square), ix and (b)

method suggested by Preining (dark circle).x

Size Cross

section

Mass No. Of

molecules

Fraction of molecules at surface

(%)

(nm) (10-18 m2) (10-25 Kg) a b

0,5 0,2 0,65 1

1 0,8 5,2 8 100 99

2 3,2 42 64 90 80

5 20 650 1000 50 40

10 80 5200 8000 25 20

20 320 42000 64000 12

In the table, we see that the smaller particles contain only a few atoms, practically all

at the surface. As the particle size increases from 1-10 nm, cross-section increases

by a factor of 100 and the mass number of molecules by a factor of 1000. Meanwhile,

the proportion of molecules at the surface falls from 100% to just 25%. For particles

of 20nm size, a little more than 10% of the atoms are on the surface.

Of course this is an idealized hypothetical case. If particles are formed by macro

molecules (that are larger than the present example), number of molecules per

particle will decrease and their surface fraction increase. The electronic properties of

these ensemble of atoms or molecules will be the result of their mutual interactions

so that the overall chemical behaviour of the particles will be entirely different from

the individual atoms or molecules that they are constituted of. They will also be

different from their macroscopic bulk state of the substance in question under the

same conditions of temperature and pressure.

Table 2-2 : Particle size, surface area and surface energy of CaCo3.xi (the surface energy of bulk

CacO3 (calcite) is 0.23 Jm-2.)


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Size

(nm)

Surface area

(m2 mol-1)

Surface energy

(J mol-1)

1 1.11 x 109 2.55 x 104

2 5.07 x 108 1.17 x 104

5 2.21 x 108 5.09 x 103

10 1.11 x 108 2.55 x 103

20 5.07 x 107 1.17 x 103

102 1.11 x 107 2.55 x 102

103 (1 µ m) 1.11 x 106 2.55 x 10

The idea of tailoring properly designed atoms into agglomerates has brought in new

fundamental work in the search for novel materials with uncharacteristic properties.Among various types of nanomaterials, cluster assembled materials represent an

original class of nanostructured solids with specific structures and properties. In

terms of structure they could be classified in between amorphous and crystalline

materials. In fact, in such materials the short-range order is controlled by the grain

size and no long-range order exists due to the random stacking of nanograins

characteristic of cluster assembled materials. In terms of properties, they are

generally controlled by the intrinsic properties of the nanograins themselves and by

the interactions between adjacent grains. Cluster assembled films are formed by the

deposition of these clusters onto a solid substrate and are generally highly porous

with densities as low as about one half of the corresponding bulk materials densities

and both the characteristic nanostructured morphology and a possible memory effect

of the original free cluster structures are at the origin of their specific properties.xii

From recent developments in the cluster source technologies (thermal, laser

vaporisation and sputtering),xiii,xiv it is now possible to produce intense cluster beams

of any materials, even the most refractory or complex systems (bimetallic,xv oxides

and so on), for a wide range of size from a few atoms to a few thousands of atoms.


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3.2 Inorganic Nanotubesxxi

3.2.1 Introduction

In 1991, Iijima observed some unusual structures of carbon under the transmission

electron microscope wherein the graphene sheets had rolled and folded onto

themselves to form hollow structures. Iijima called them nanotubes of carbon which

consisted of several concentric cylinders of grapheme sheets. Graphene sheets are

hexagonal networks of carbon and these layers get stacked one above the other in

the c -direction to form bulk graphite. Following the initial discovery, intense research

has been carried out on carbon nanotubes (CNTs). The nanotubes can be open-

ended or closed by caps containing five-membered rings. They can be multi-(MWNTs) or singlewalled (SWNTs). We show a typical high-resolution electron

microscope (HREM) image of a multi-walled nanotube in Figure 3-1.

Figure 3-1 : A typical TEM image of a closed, multi-walled carbon nanotube. The separation

between the graphite layers is 0.34 nm. [C.N.R. Rao, M. Nath, Inorganic nanotubes, Dalton Trans.,

2003, p.p. 1-24]

Depending on the way the graphene sheets fold, nanotubes are classified as

armchair, zigzag or chiral as shown in Figure 3-2. The electrical conductivity of the

nanotubes depends on the nature of folding.


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Figure 3-2 : Schematic representation of the folding of a graphene sheet into (a) zigzag, (b)

armchair and (c) chiral nanotubes. [C.N.R. Rao, M. Nath, Inorganic nanotubes, Dalton Trans., 2003,

p.p. 1-24]

Several layered inorganic compounds possess structures comparable to the structure

of graphite, the metal dichalcogenides being important examples. The metal

dichalcogenides, MX2 (M = Mo, W, Nb, Hf; X = S, Se) contain a metal layer

sandwiched between two chalcogen layers with the metal in a trigonal pyramidal or

octahedral coordination mode. The MX2 layers are stacked along the c -direction in

ABAB fashion. The MX2 layers are analogous to the single graphene sheets in the

graphite structure (Figure 3-3).


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Figure 3-3 : Comparison of the structures of (a) graphite and inorganic layered compounds such as

(b) NbS2 /TaS2; (c) MoS2; (d) BN. In the layered dichalcogenides, the metal is in trigonal prismatic

(TaS2) or octahedral coordination (MoS2). [C.N.R. Rao, M. Nath, Inorganic nanotubes, Dalton Trans.,

2003, p.p. 1-24]

When viewed parallel to the c -axis, the layers show the presence of dangling bonds

due to the absence of an X or M atom at the edges. Such unsaturated bonds at the

edges of the layers also occur in graphite. The dichalcogenide layers are unstabletowards bending and have a high propensity to roll into curved structures. Folding in

the layered transition metal chalcogenides (LTMCs) was recognized as early as

1979, well before the discovery of the carbon nanotubes. Rag-like and tubular

structures of MoS2 were reported by Chianelli who studied their usefulness in

catalysis.

The folded sheets appear as crystalline needles in low magnification transmission

electron microscope (TEM) images, and were described as layers that fold ontothemselves (Figure 3-4).


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Figure 3-4 : Low-magnification TEM images of (a) highly folded MoS2 needles and (b) a rolled sheet

of MoS2 folded back on itself. [C.N.R. Rao, M. Nath, Inorganic nanotubes, Dalton Trans., 2003, p.p. 1-

24]

These structures indeed represent those of nanotubes. Tenne et al xxii first

demonstrated that Mo and W dichalcogenides are capable of forming nanotubes

(Figure 3-5 a).

Figure 3-5 : TEM images of (a) a multi-walled nanotube of WS2 and (b) hollow particles (inorganic

fullerenes) of WS2. [C.N.R. Rao, M. Nath, Inorganic nanotubes, Dalton Trans., 2003, p.p. 1-24]

Closed fullerene-type structures (inorganic fullerenes) also formed along with thenanotubes (Figure 3-5 b). The dichalcogenide structures contain concentrically

nested fullerene cylinders, with a less regular structure than in the carbon nanotubes.

Accordingly, MX2 nanotubes have varying wall thickness and contain some

amorphous material on the exterior of the tubes. Nearly defect-free MX2 nanotubes

are rigid as a consequence of their structure and do not permit plastic deformation.

The folding of a MS2 layer in the process of forming a nanotube is shown in the

schematic in Figure 3-6.


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Figure 3-6 : Schematic illustration of the bending of a MoS2 layer. [C.N.R. Rao, M. Nath, Inorganic

nanotubes, Dalton Trans., 2003, p.p. 1-24]

Considerable progress has been made in the synthesis of the nanotubes of Mo andW dichalcogenides in the last few years (Table 3-1 and Table 3-2).

Table 3-1 : Synthetic strategies for various chalcogenide nanotubes [C.N.R. Rao, M. Nath,

Inorganic nanotubes, Dalton Trans., 2003, p.p. 1-24]

Table 3-2 : Synthetic strategies for various chalcogenide nanotubes [C.N.R. Rao, M. Nath,

Inorganic nanotubes, Dalton Trans., 2003, p.p. 1-24]


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There has been some speculation on the cause of folding and curvature in the

LTMCs. Stoichiometric LTMC chains and layers such as those of TiS2 possess an

inherent ability to bend and fold, as observed in intercalation reactions.

The existence of alternate coordination and therefore of stoichiometry in the LTMCs

may also cause folding. Lastly, a change in the stoichiometry within the material

would give rise to closed rings.

Transition metal chalcogenides possess a wide range of interesting physical

properties. They are widely used in catalysis and as lubricants. They have both

semiconducting and superconducting properties (see paragraph 7). With the

synthesis and characterization of the fullerenes and nanotubes of MoS2 and WS2, a

wide field of research has opened up enabling the successful synthesis of nanotubes

of other metal chalcogenides. It may be recalled that the dichalcogenides of many ofthe Group 4 and 5 metals have layered structures suitable for forming nanotubes.

Curved structures are not only limited to carbon and the dichalcogenides of Mo and

W. Perhaps the most well-known example of a tube-like structure with diameters in

the nm range is formed by the asbestos mineral (chrysotil) whose fibrous

characteristics are determined by the tubular structure of the fused tetrahedral and

octahedral layers. The synthesis of mesoporous silica with well-defined pores in the

2–20 nm range was reported by Beck and Kresgexxiii

. The synthetic strategy involvedthe self-assembly of liquid crystalline templates. The pore size in zeolitic and other


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inorganic porous solids is varied by a suitable choice of the template. However, in

contrast to the synthesis of porous compounds, the synthesis of nanotubes is

somewhat more difficult.

Nanotubes of oxides of several transition metals as well as of other metals have been

synthesized employing different methodologies. Silica nanotubes were first produced

as a spin-off product during the synthesis of spherical silica particles by the

hydrolysis of tetraethylorthosilicate (TEOS) in a mixture of water, ammonia, ethanol

and D,L-tartaric acid. Since selfassembly reactions are not straightforward with

respect to the desired product, particularly its morphology, templated reactions have

been employed using carbon nanotubes to obtain nanotube structures of metal

oxides. Oxides such as V2O5 have good catalytic activity in the bulk phase. Redox

catalytic activity is also retained in the nanotubular structure. There have been efforts

to prepare V2O5 nanotubes by chemical methods as well.

Boron nitride (BN) crystallizes in a graphite-like structure and can be simply viewed

as replacing a C–C pair in the graphene sheet with the iso-electronic B–N pair. It can,

therefore, be considered as an ideal precursor for the formation of BN nanotubes.

Replacement of the C–C pairs partly or entirely by the B–N pairs in the hexagonal

network of graphite leads to the formation of a wide array of two-dimensional phases

that can form hollow cage structures and nanotubes. The possibility of replacing C–C

pairs by B–N pairs in the hollow cage structure of C60 was predicted and verified

experimentally. BN-doped carbon nanotubes have been prepared. Pure BN

nanotubes have been generated by employing several procedures, yielding

nanotubes with varying wall thickness and morphology. It is therefore quite possible

that nanotube structures of other layered materials can be prepared as well. For

example, many metal halides (e.g., NiCl2), oxides (GeO2) and nitrides (GaN)

crystallize in layered structures. There is considerable interest at present to prepareexotic nanotubes and to study their properties.

3.2.2 General synthetic strategies

Several strategies have been employed for the synthesis of carbon nanotubes. They

are generally made by the arc evaporation of graphite or by the pyrolysis of

hydrocarbons such as acetylene or benzene over metal nanoparticles in a reducing

atmosphere. Pyrolysis of organometallic precursors provides a one-step synthetic


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method of making carbon nanotubes. In addition to the above methods, carbon

nanotubes have been prepared by laser ablation of graphite or electron-beam

evaporation. Electrochemical synthesis of nanotubes as well as growth inside the

pores of alumina membranes have also been reported. The above methods broadly

fall under two categories. Methods such as the arc evaporation of graphite employ

processes which are far from equilibrium. The chemical routes are generally closer to

equilibrium conditions. Nanotubes of metal chalcogenides and boron nitride are also

prepared by employing techniques similar to those of carbon nanotubes, although

there is an inherent difference in that the nanotubes of inorganic materials such as

MoS2 or BN would require reactions involving the component elements or

compounds containing the elements. Decomposition of precursor compounds

containing the elements is another possible route.

Nanotubes of dichalcogenides such as MoS2, MoSe2 and WS2 are also obtained by

employing processes far from equilibrium such as arc discharge and laser ablation.

By far the most successful routes employ appropriate chemical reactions. Thus,

MoS2 and WS2 nanotubes are conveniently prepared starting with the stable oxides,

MoO3 and WO3. The oxides are first heated at high temperatures in a reducing

atmosphere and then reacted with H2S. Reaction with H2Se is used to obtain the

selenides. Recognizing that the trisulfides MoS3 and WS3 are likely to be the

intermediates in the formation of the disulfide nanotubes, the trisulfides have been

directly decomposed to obtain the disulfide nanotubes. Diselenide nanotubes have

been obtained from the metal triselenides. The trisulfide route is indeed found to

provide a general route for the synthesis of the nanotubes of many metal disulfides

such as NbS2 and HfS2. In the case of Mo and W dichalcogenides, it is possible to

use the decomposition of the precursor ammonium salt, such as (NH4)2MX4 (X = S,

Se; M = Mo, W) as a means of preparing the nanotubes. Other methods employedfor the synthesis of dichalcogenide nanotubes include hydrothermal methods where

the organic amine is taken as one of the components in the reaction mixture (Table

3-1 and Table 3-2).

The hydrothermal route has been used for synthesizing nanotubes and related

structures of a variety of other inorganic materials as well. Thus, nanotubes of

several metal oxides (e.g., SiO2, V2O5, ZnO) have been produced hydrothermally.

Nanotubes of oxides such as V2O5 are also conveniently prepared from a suitablemetal oxide precursor in the presence of an organic amine or a surfactant.


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Surfactant-assisted synthesis of CdSe and CdS nanotubes has been reported. Here

the metal oxide reacts with the sulfidizing/selenidizing agent in the presence of a

surfactant such as TritonX.

Sol–gel chemistry is widely used in the synthesis of metal oxide nanotubes, a good

example being that of silica and TiO2. Oxide gels in the presence of surfactants or

suitable templates form nanotubes. For example, by coating carbon nanotubes

(CNTs) with oxide gels and then burning off the carbon, one obtains nanotubes and

nanowires of a variety of metal oxides including ZrO2, SiO2 and MoO3. Sol–gel

synthesis of oxide nanotubes is also possible in the pores of alumina membranes. It

should be noted that MoS2 nanotubes are also prepared by the decomposition of a

precursor in the pores of an alumina membrane.

Boron nitride nanotubes have been obtained by striking an electric arc between HfB2

electrodes in a N2 atmosphere. BCN and BC nanotubes are obtained by arcing

between B/C electrodes in an appropriate atmosphere. A greater effort has gone into

the synthesis of BN nanotubes starting with different precursor molecules containing

B and N. Decomposition of borazine in the presence of transition metal nanoparticles

and the decomposition of the 1 : 2 melamine–boric acid addition compound yield BN

nanotubes. Reaction of boric acid or B2O3 with N2 or NH3 at high temperature in the

presence of activated carbon, carbon nanotubes or catalytic metal particles has been

employed to synthesize BN nanotubes.

3.3 Functional Materials Based on Self-Assembly of

Polymeric Supramoleculesxxiv

Here, we describe some possibilities for preparing functional polymeric materials

using the "bottom-up" route, based on self-assembly of polymeric supramolecules.

Directed assembly leads to the control of structure at several length scales and

anisotropic properties. The physical bonds within the supramolecules allow controlled

cleavage of selected constituents. The techniques constitute a general platform for

constructing materials that combine several properties that can be tuned separately.

To achieve enhanced functionalities, the principal periodicity is at ~10 to 2000 Å.

There are established ways to accomplish this by using various architectures of block

copolymers, in which the structure formation is based on self-organization, that is, on

the repulsion between the chemically connected blocks. Depending on the


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architecture, block length, and temperature, it is possible to obtain lamellar,

cylindrical, spherical, gyroid, or more complicated structures in the 100 to 2000 Å

range. Also, rodlike moieties within the block copolymers can be used to further tailor

the structures in terms of shape persistency. However, self-organization renders only

the local structures. To fully realize the opportunities offered by the symmetry of the

self-organized structures to prepare materials with a strongly directional variation of

properties, additional mechanisms and interactions have to be invoked to obtain

macroscale order. This may be achieved by flow, by electric or magnetic fields, or by

using topographically patterned surfaces. One can further extend the structural

complexity by mixing block copolymers with additional polymers and inorganic

additives, thereby increasing the self-organization periods into the photonic band gap

regime. Block copolymers have also been used as templates for the synthesis of

inorganic materials, even allowing the creation of separate ceramic nano-objects.

To achieve even greater structural complexity and functionality, we can combine

recognition with self-organization. Lehn elaborated on the concept of recognition in

synthetic materials, whereby two molecules with molecularly matching

complementary interactions and shapes recognize each other and form a receptor-

substrate supramolecule. To achieve sufficient bonding, synergism of several

physical interactions is often required. Homopolymerlike supramolecules have been

constructed based on a combination of four hydrogen bonds and through

coordination. Supramolecules can spontaneously assemble or self-organize to form

larger structures.

A general framework for forming complex functional materials emerges. Molecules

are constructed that recognize each other in a designed way. The subsequent

supramolecules in turn form assemblies or self-organize, possibly even forming

hierarchies. The overall alignment of the local structures can be additionally improvedby electric or magnetic fields, by flow, or by patterned surfaces.

To illustrate recognition-driven supramolecule formation in polymers and the

subsequent self-organization and preparation of functional materials and nano-

objects, we focus on the comb-shaped architecture (Figure 3-7) encouraged by the

enhanced solubility of socalled hairy-rod polymers.


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Figure 3-7 : Comb-shaped supramolecules and their hierarchical self-organization, showing primary

and secondary structures. Similar schemes can, in principle, be used both for flexible and rodlike

polymers. In the first case, simple hydrogen bonds can be sufficient, but in the latter case a synergistic

combination of bondings (recognition) is generally required to oppose macrophase separation

tendency. In (A through C), the self-organized structures allow enhanced processibility due to

plastization, and solid films can be obtained after the side chains are cleaved (D). Self-organization of

supramolecules obtained by connecting amphiphiles to one of the blocks of a diblock copolymer (E)

results in hierarchically structured materials. Functionalizable nanoporous materials (G) are obtained

by cleaving the side chains from a lamellae-within-cylinders structure (F). Disk-like objects (H) may beprepared from the same structure by crosslinking slices within the cylinders, whereas nano rods (I)


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result from cleaving the side chains from a cylinder-within-lamellae structure. Without loss of

generality, (A) is shown as a flexible polymer, whereas (B) and (C) are shown as rodlike chains. [O.

Ikkala, G.T. Brinke, Functional Materials Based on Self-assembly of polymeric supramolecules,

Science, New Series, Vol. 295, No. 5564 (Mar. 29, 2002), pp. 2407-2409]

The simplest case is a flexible polymer having bonding sites along its backbone

(Figure 3-7 A). Therefore, the backbone is typically polar, and repulsive nonpolar side

groups can be connected by complementary bonds, leading to comb-shaped

supramolecules, which in turn self-organize. We have extensively used hydrogen

bonding or coordination to bond side chains to the polymer backbone. Antonietti et

al.xxv have used ionic interactions in polyelectrolyte-surfactant complexes to form

comb-shaped polyelectrolyte surfactant complexes. The resulting self-organized

multidomain structures may be aligned, using, for example, flow, in order to approachmonodomains. One can also tune the properties by tailoring the nature of the side

chains. For example, if the side chains are partly fluorinated, low surface energy

results, which allows for applications that lead to reduced friction. In another case,

the backbone consists of the double helix of DNA, and self-organization is achieved

by ionically bonding cationic liposomes or cationic surfactants to the anionic

phosphate sites. This allows for materials design beyond the traditional scope of

biochemical applications. For example, dyes can be intercalated into the helices,suppressing their aggregation tendency and leading to promising properties as

templates for photonic applications. In such a structure, the polymer backbone may

contain two or even more kinds of binding sites where different additives can be

bonded (Figure 3-7 B). Side chains can also have two separate functions. For

example, in addition to providing a repulsive side chain required for self-organization,

the side chains may contain an acidic group that acts as a dopant for a conjugated

polymer such as polyaniline, which leads to electronic conductivity. To introducefurther degrees of freedom in tailoring the self-organized phases and their

processing, polyaniline may first be doped by a substance such as camphor

sulphonic acid and subsequently connected to hexyl resorcinol molecules using their

two hydrogen bonds (Figure 3-7 C). The alkyl chains of the hydrogen-bonded hexyl

resorcinol molecules act as plasticizers, leading to thermoplastic processibility of the

otherwise infusible polymer. They enforce self-organization where camphor sulfonic

acid-doped polyaniline chains are confined in nanoscale conducting cylinders,

leading to increased conductivity. The concept can be applied even to rodlike


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polymers, such as polypyridine, which consists of para-coupled heteroaromatic rings.

Its optical properties can be tuned based on camphor sulphonic acid. Subsequent

hydrogen bonding with alkyl resorcinol creates comb-shaped supramolecules, which

self-organize in lamellae in such a way that the material is fluid even without

additional solvents. Such a fluid state incorporating rigid polymeric rods is uncommon

and allows processing toward monodomains where the rods are aligned. Ultimately,

the plasticizing hydrogen-bonded alkyl resorcinol molecules can be removed by

evaporation in a vacuum oven, thus interlocking the chains in solid stable films

(Figure 3-7 D). In this way, efficient polarized luminance has been achieved.

To increase complexity, one can incorporate structural hierarchies. This can be

accomplished by applying within a single material different self-organization and

recognition mechanisms operating at different length scales. For example, block

copolymeric self-organization at the 100 to 2000 Å length scale and polymer-

amphiphile self-organization at the 10 to 60 Å length scale can be combined (Figure

3-7 E). After selective doping of one block, conductivity can be switched based on a

sequence of phase transitions.

3.4 Molecular biomimetics: Nanotechnology through

biologyxxvi

Molecular biomimetics. This is the marriage of materials science engineering and

molecular biology for development of functional hybrid systems, composed of

inorganics and inorganic-binding proteins. The new approach takes advantage of

DNA-based design, recognition,and self-assembly characteristics of biomolecules.

Traditional materials science engineering produces materials (for example, medium-

carbon steels depicted in the bright- and dark-field TEM images), that have been

successfully used over the last century. Molecular biology focuses on structure–

function relations in biomacromolecules, for example, proteins.


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Figure 3-8 : In molecular biomimetics, inorganic-binding proteins could potentially be used as (i)

linkers for nanoparticle immobilization; (ii) functional molecules assembled on specific substrates; and

(iii) heterobifunctional linkers involving two (or more) binding proteins linking several nanoinorganic

units. (I1: inorganic-1,I2: Inorganic-2, P1 and P2: inorganic specific proteins, LP:linker protein, FP:

fusion protein). [Sarikaya, C. Tamerler, A.K.Y. Jen, K. Schulten F. Baneyx, Molecular biomimetics:

nanotechnology through biology, Nature Materials, vol 2, 2003, p.p. 577-585]

In molecular biomimetics, a marriage of the physical and biological fields, hybrid

materials could potentially be assembled from the molecular level using the

recognition properties of proteins (Figure 3-8) under the premise that inorganic

surface-specific polypeptides could be used as binding agents to control the

organization and specific functions of materials.Molecular biomimetics simultaneously

offers three solutions to the development of heterofunctional nanostructures.

• The first is that protein templates are designed at the molecular level through

genetics. This ensures complete control over the molecular structure of the

protein template (that is, DNA-based technology).

• The second is that surface-specific proteins can be used as linkers to bind

synthetic entities, including nanoparticles, functional polymers, or other

nanostructures onto molecular templates (molecular and nanoscale

recognition).

• The third solution harnesses the ability of biological molecules to self- and co-

assemble into ordered nanostructures. This ensures a robust assembly


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process for achieving complex nano-, and possibly hierarchical structures,

similar to those found in nature (self-assembly).

The current knowledge of protein-folding predictions and surface-binding chemistries

does not provide sufficiently detailed information to perform rational design of

proteins. To circumvent this problem, massive libraries of randomly generated

peptides can be screened for binding activity to inorganic surfaces using phage and

cell-surface display techniques. It may ultimately be possible to construct a

‘molecular erector’ set, in which different types of proteins, each designed to bind to a

specific inorganic surface, could assemble into intricate, hybrid structures composed

of inorganics and proteins. This would be a significant leap towards realizing

molecularly designed, genetically engineered technological materials.

3.4.1 Selection of inorganic-binding proteins through display

technologies

There are several possible ways of obtaining polypeptide sequences with specific

affinity to inorganics. A number of proteins may fortuitously bind to inorganics,

although they are rarely tested for this purpose. Inorganic-binding peptides may be

designed using a theoretical molecular approach similar to that used forpharmaceutical drugs. This is currently impractical because it is time consuming and

expensive. Another possibility would be to extract biomineralizing proteins from hard

tissues followed by their isolation, purification and cloning. Several such proteins

have been used as nucleators, growth modifiers, or enzymes in the synthesis of

certain inorganics. One of the major limitations of this approach is that a given hard

tissue usually contains many proteins, not just one, all differently active in

biomineralization and each distributed spatially and temporally in complex ways.

Furthermore, tissue-extracted proteins may only be used for the regeneration of the

inorganics that they are originally associated with, and would be of limited practical

use. The preferred route, therefore, is to use combinatorial biology techniques. Here,

a large random library of peptides with the same number of amino acids, but of

different sequences, is used to mine specific sequences that strongly bind to a

chosen inorganic surface.

Since their inception, well-established in vivo combinatorial biology protocols (for

example, phage display (PD) and cell-surface display (CSD)) have been used to


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identify biological ligands and to map the epitope (molecular recognition site) of

antibodies. Libraries have also been screened for various biological activities, such

as catalytic properties or altered affinity and specificity to target molecules in many

applications including the design of new drugs, enzymes, antibodies, DNA-binding

proteins and diagnostic agents. The power of display technologies relies on the fact

that an a priori knowledge of the desired amino acid sequence is not necessary, as it

can simply be selected and enriched if a large enough population of random

sequences is available. In vitro methods, such as ribosomal and messenger RNA

display technologies, have been developed for increased library size (1015) compared

to those of in vivo systems (107–10).

Combinatorial biology protocols can be followed in molecular biomimetics to select

polypeptide sequences that preferentially bind to the surfaces of inorganic

compounds chosen for their unique physical properties in nano- and biotechnology.

Libraries are generated by inserting randomized oligonucleotides within certain

genes encoded on phage genomes or on bacterial plasmids (step 1 in Figure 3-9).

Figure 3-9 : Phage display and cell-surface display. Principles of the protocols used for selecting

polypeptide sequences that have binding affinity to given inorganic substrates. [Sarikaya, C. Tamerler,

A.K.Y. Jen, K. Schulten F. Baneyx, Molecular biomimetics: nanotechnology through biology, Nature

Materials, vol 2, 2003, p.p. 577-585]


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This leads to the incorporation of a random polypeptide sequence within a protein

residing on the surface of the organism (for example, the coat protein of a phage or

an outer membrane or flagellar protein of a cell; step 2). The eventual result is that

each phage or cell produces and displays a different, but random peptide (step 3). At

this stage, a heterogeneous mixture of recombinant cells or phages are contacted

with the inorganic substrate (step 4).Several washing cycles of the phages or the

cells eliminate non-binders by disrupting weak interactions with the substrate (step

5). Bound phages or cells are next eluted from the surfaces (step 6). In PD, the

eluted phages are amplified by reinfecting the host (step 7). Similarly in CSD, cells

are allowed to grow (steps 7, 8). This step completes a round of biopanning.

Generally, three to five cycles of biopanning are repeated to enrich for tight binders.

Finally, individual clones are sequenced (step 9) to obtain the amino acid sequence

of the polypeptides binding to the target substrate material.

3.4.2 Chemical specificity of inorganic-binding polypeptides

A genetically engineered polypeptide for inorganics (GEPI) defines a sequence of

amino acids that specifically and selectively binds to an inorganic surface. The

surface could be well defined, such as a single crystal or a nanostructure. It might

also be rough, or totally non-descriptive, such as a powder. Researchers have

focused on using materials that can be synthesized in aqueous environments under

physiological conditions (biocompatible) and that exhibit fairly stable surface

structures and compositions. These include noble metals (Pt and Pd) as well as

oxide semiconductors (Cu2O and ZnO) that were biopanned using either PD or

flagellar display (both studies unpublished). Some of the identified binders as well as

sequences selected by other researchers are listed in Table 3-3.

Table 3-3 : Examples of polypeptide sequences exhibiting affinity for various inorganics.

[Sarikaya, C. Tamerler, A.K.Y. Jen, K. Schulten F. Baneyx, Molecular biomimetics: nanotechnology

through biology, Nature Materials, vol 2, 2003, p.p. 577-585]


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3.4.3 Physical specificity of peptide binding

Ideally, selection of sequences should be performed using an inorganic material of

specific morphology, size, crystallography or surface stereochemistry. In practice,

however, powders of various sizes and morphologies have been used for selection.

The sequence space should be largest for powders, as peptides can attach to


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d) e)

Figure 3-10 : Effect of GEPI on nanocrystal morphology. a–c, One of the two mutants (RP1) from a

library of goldbinding GEPIs were tested in the formation of flat gold particles, shown in a, similar to

those formed under acidic (b) or boiling (c) conditions. Particles formed in the presence of vector-

encoded alkaline phosphatase and neutral conditions do not result in morphological change of gold

particles (not shown). d-e, The atomic force microscope images show quantum (GaInAs) dots

assembled on GaAs substrate; d, through high-vacuum (molecular beam epitaxy) strain-induced self-

assembly, and e, through 7-repeat GBP1. f, Schematic illustration of e. PS: polystyrene substrate, GA:

glutaraldehyde, GBP: 7- repeat GBP1, and gold: 12-nm-diameter colloidal gold particles. [Sarikaya, C.

Tamerler, A.K.Y. Jen, K. Schulten F. Baneyx, Molecular biomimetics: nanotechnology through biology,

Nature Materials, vol 2, 2003, p.p. 577-585]

For example, quantum dots can be produced using vacuum techniques, such as

molecular beam epitaxy, shown in Figure 3-10 d for the GaInAs/GaAs system.

However, this can only be accomplished under stringent conditions of high

temperature, very low pressures and a toxic environment. A desirable alternative

would be not only to synthesize inorganic nanodots under mild conditions, but also to

immobilize/self-assemble them. Inorganic particles have been functionalized with

synthetic molecules, including thiols and citrates, and with biological molecules, such

as lipids, amino acids, polypeptides and ligand-functionalized DNA. Using the

recognition properties of the coupling agents, novel materials have been generatedand controlled growth has been achieved. These molecules, however, do not exhibit

specificity for a given material. For example, thiols couple gold as well as silver

nanoparticles in similar ways. Likewise, citrate ions cap noble metals indiscriminately.

A desirable next step would be to use GEPIs that specifically recognize inorganics for

nanoparticle assembly. An advantage of this approach is that GEPI can be

genetically or synthetically fused to other functional biomolecular units or ligands to

produce heterobifunctional (or multifunctional) molecular entities. Figure 3-10 e and fshows the assembly of nanogold particles on GBP1-coated flat polystyrene surfaces,

which resembles the distribution of quantum dots obtained by high-vacuum

deposition techniques (Figure 3-10 d). The homogenous decoration of the surface

with nanogold suggests that proteins may be useful in the production of tailored

nanostructures under ambient conditions and aqueous solutions. Furthermore, the

recognition activity of the protein could provide an ability to control the particle

distribution, and particle preparation conditions could allow size control. Thisapproach makes it possible to pattern inorganic-binding polypeptides into desirable


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arrays to produce inorganic particles through templating using, for example, dip-pen

lithography.

3.5 References

Sarikaya, C. Tamerler, A.K.Y. Jen, K. Schulten F. Baneyx, Molecular biomimetics:

nanotechnology through biology, Nature Materials, vol 2, 2003, p.p. 577-585

O. Ikkala, G.T. Brinke, Functional Materials Based on Self-assembly of polymeric

supramolecules, Science, New Series, Vol. 295, No. 5564 (Mar. 29, 2002), pp. 2407-

2409

C.N.R. Rao, M. Nath, Inorganic nanotubes, Dalton Trans., 2003, p.p. 1-24


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4 MECHANICAL PROPERTIES

4.1 IntroductionOne of the very basic results of the physics and chemistry of solids is the insight that

most properties of solids depend on the microstructure, i.e. the chemical composition,

the arrangement of the atoms (the atomic structure) and the size of a solid in one,

two or three dimensions. In other words, if one changes one or several of these

parameters, the properties of a solid vary. The most well-known example of the

correlation between the atomic structure and the properties of a bulk material is

probably the spectacular variation in the hardness of carbon when it transforms fromdiamond to graphite. The important aspects related to structure are:

• atomic defects, dislocations and strains

• grain boundaries and interfaces

• porosity

• connectivity and percolation

• short range order

Defects are usually absent in either metallic or ceramic clusters of

nanoparticles because dislocations are basically unstable or mobile. The stress field

around a dislocation (or the electrostatic potential around charges and currents)

have to satisfy the Laplace equation: ∇2Φ = 0. This sets up an image dislocation

which pulls the defect out of the particle.

When these clusters are assembled under uniaxial pressure into a pellet, for

example, it is found that the individual clusters are packed very tightly into apolycrystalline solid. Cluster-assembled materials often show close to 100% density.

A fully consolidated nanophase material looks very much like a normal, dense

polycrystalline aggregate, but at a far smaller scale.

4.2 Metals

The microstructure of a material is controlled by the processing steps chosen for its

fabrication. Such microstructural design affects the nature of the phases present,their topology (i.e. geometrical distribution and interconnection) and their dispersion


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(described by relevant “size” parameters). The full characterization of these

parameters is the domain of quantitative metallurgy.

Most of these size effects come about because of the microstructural constraint to

which a particular physical mechanism is subjected. Consider the classic case of

strengthening a metallic matrix by particles or grain boundaries: lattice dislocations

are forced, by the microstructural constraint, to bow out or pile up, which requires an

external stress characteristic of a microstructural parameter. The wall thickness

relative to the size of the microstructural inhomogeneity can control the macroscopic

behaviour.

In general, it is therefore the competition or coupling between two different size

dependencies that determines the properties of a material. One thus has to deal with

the interaction of two length scales: (1) is the dimension characteristic of the physical

phenomenon involved, called the characteristic length. (2) is some microstructural

dimension, denoted as the size parameter.

4.2.1 Grain size effects in plasticity and creep

4.2.1.1 Hall-Petch effects.

Strengthening of polycrystalline materials by grain size refinement istechnologically attractive because it generally does not adversely affect ductility

and toughness. The classical effect of grain size on yield stress (τ ) can, among

other possibilities, be explained by a model invoking a pile-up of dislocations

against grain boundaries, which results in a dependence of the hardening

increment kHP on the square root of the grain size D

D

k HP

=τ (4. 1)

Where kHP is a constant. This is the classical Hall-Petch effect.

In Figure 4-1, some of the available data have been plotted in a Hall-

Petch plot.xxvii


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Figure 4-1 : Compilation of yield stress data for several metallic systems. [R.A. Masumura, P.M.

Hazzledine, C.S. Pande, Yield stress of fine grained materials, 1998, Acta-Materialia]

It is seen that the yield stress-grain size exponent for relatively large grains

appears to be very close to -0.5 and generally this trend continues until the very fine

grain regime (~100 nm) is reached. The reported data show three different regions:

1. A region from single crystal to a grain size of about 1 mm where the classical

Hall-Petch description can be used.2. A region for grain sizes ranging from about 1 mm to about 30 nm where the

Hall-Petch relation roughly holds, but deviates from the classical -0.5

exponent to a value near zero (to ascertain such behaviour, a wide range of

grain sizes extending into the ultra-fine grain size regime is required).

3. A region beyond a very small critical grain size where the Hall-Petch slope is

essentially zero, with no increase in strength on decreasing grain size or

where the strength actually decreases with decreasing grain size.

There is universal agreement regarding the first region, i.e. relatively large grain

sizes. Early hardness measurements had already established a distinct increase in

hardness as grain sizes decrease as compared to their annealed coarse grained

counterparts, and this increase follows the Hall-Petch relationship reasonably well.

The trend is less well established for finer grains (Region 2). Some of the deviation

from Hall-Petch strengthening could simply be due to pores in the material (asevidenced by lower densities) leading also to a lower shear stress for the


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deformation mode and lower shear modulus. Indeed, the lower modulus has been

ascribed to a decrease in bulk density. Additional complications arise due to

impurities at the grain boundaries such as oxides and impurities inside the grain

such as trapped or diffused gas. In spite of the above difficulties, once the totality of

the data is taken into consideration, it is fairly safe to conclude that the increase in

strength on grain refinement in the middle region is somewhat less than predicted by

the Hall-Petch relation.

The third region is much more controversial and is going to be discussed later.

4.2.1.2 Limits to Hall-Petch behaviour: dislocation curvature vs. grain size.

Whereas many metallic materials obey such a relationship over several

orders of magnitude in grain size, it is inevitable that the reasoning behind equation

D

k HP=τ (4. 1) must break down for very small grains. A clear limit for the

occurrence of dislocation plasticity in a poly-crystal is given by the condition that at

least one dislocation loop must fit into average grain (Figure 4-2).

Figure 4-2 : Grain size strengthening, as explained by pile-ups of dislocation loops against grain

boundaries (a). this mechanism must break down when the diameter d of the smallest loop no longer

fits into a grain of size D (b). [E. Arzt, Size effects in materials due to microstuctural and dimensional

constraints: A comparative review, 1998, Acta Meteriala]


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The characteristic length, i.e. the loop diameter (τ τ

τ Gb

b

T d d ==

2)( ), must now be

compared with the grain size D as the relevant size parameter

Dd =)(τ (4. 2)

D

Gb

bD

T d ==2

τ (4. 3)

Figure 4-3 illustrates schematically this limit on Hall-Petch behaviour:

“conventional” grain size strengthening can be expected only to the right of the heavy

line which signifies the limiting condition Dd =)(τ (4. 2) D

Gb

bD

T d ==2

τ (4. 3).

Figure 4-3 : The limiting condition is shown as the heavy line where the shear strength τ is plotted

schemetically as a function of grain size D . Hall-Petch behavior can only be found to the right of this

line; abnormal or inverse behavior may result otherwise. The dotted line reflects schematically the

equation 0ln

r

D

D

Gb≈τ

(4. 6). [E. Arzt, Size effects in materials due to microstuctural and

dimensional constraints: A comparative review, 1998, Acta Meteriala]

For Cu, as an example, the critical grain size estimated in this way is about50nm; this value is in reasonable agreement with experimental results, as shown in

Figure 4-4.


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Figure 4-4 : Inverse Hall-Petch behaviour in nanocrystalline Cu (H-H 0 denotes the hardness increment,

D the grain size): the classical behaviour breaks down at a grain size of about 50 nm, in agreement with

an estimate based on the loop diameter [equations Dd =)(τ (4. 2) DGb

bD

T d ==

2τ

(4. 3)].

Replotted after Chokshi et al . xxviii [E. Arzt, Size effects in materials due to microstuctural and

dimensional constraints: A comparative review, 1998, Acta Meteriala]

The plastic behaviour of nanocrystalline materials with grain sizes below the

critical value is not fully clear. It has been argued that because of the viscous

behaviour of amorphous materials (which can be considered the limiting case for grain

refinement) the grain size strengthening effect will have to be reversed once the grain

size D starts to approach the grain-boundary thickness δδδδb. One possible explanation

for such a softening effect comes from a re-consideration of the line tension Td in

equation D

Gb

bD

T d ==2

τ (4. 3). The more refined expression

2

1ln4

²

r

r GbT d

π = (4. 4)

contains a lower (r0) and an upper (r1) cut-off distance for the stress field of the

dislocation. In conventional materials r1 generally lies in the micrometer range and

therefore significantly exceeds r0 (for which values between 2 and 10b are commonly

assumed); this justifies replacing the logarithmic term by a constant. However, in

nanocrystalline materials it is reasonable to equate r1 to the grain size, which now

gives r1 ≈≈≈≈ r0 and makes T sensitive to the value of the grain size D. Therefore, we now

have a case in which the characteristic length (d) is a function of the size parameter(D). The resulting strength increment is given by


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02 r

Dn

D

Gb

π τ = (4. 5)

This expression vanishes rapidly as the grain size D approaches the lower cut-

off distance r0. An even more refined expression has been obtained by Scattergoodand Kochxxix.

The dislocation density ρρρρ scales inversely with grain size D, the obstacle

spacing is L~1/√√√√p~√√√√D, which yields

0

lnr

D

D

Gb≈τ (4. 6)

This expression, which is schematically shown as dotted line in Figure 4-3,

reduces correctly to Hall-Petch behavior for D >>r0. It gives a possible interpretation of

grain-boundary softening behavior in nanocrystalline Cu and Pd.

4.2.1.3 Diffusional creep as a size effect

An alternative explanation of grain-boundary softening in very fine-grained materials

can be based on increasing contributions of diffusional creep. Diffusional processes in

a potential gradient [caused in this case by a normal stress gradient,] exhibit a natural

size effect because the length scale affects the magnitude of the gradient.

Figure 4-5 : Diffusional creep is driven by gradients in normal tractions on grain boundaries (a). Fine

arrows delineate the paths for transport of matter. This mechanism ceases to operate (b) once a grain

boundary dislocation loop no longer fits into a grain facet (d > D’). Note the analogy with Figure 4-2 for

lattice dislocations [E. Arzt, Size effects in materials due to microstuctural and dimensional constraints:

A comparative review, 1998, Acta Meteriala]

For maintaining a constant strain rate•

ε by diffusion of atoms from grain boundaries

under compression to those under tension, the following shear stress τ is required


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Ω=

•

v DC

kTD

1

2ε τ (4. 7)

Here Dv is the volume diffusivity, Ω the atomic volume, and C1 a dimensionless

constant of the order of 10. Accounting for grain-boundary diffusion (with diffusivity Db through a grain boundary with thickness δb) gives

Ω=

•

bb DC

kTD

δ

ε τ

2

3

(4. 8)

In addition to this, the triple lines in nanocrystalline materials can also act as fast

diffusion paths. EquationsΩ

=

•

v DC

kTD

1

2ε τ (4. 7) and

Ω=

•

bb DC

kTD

δ

ε τ

2

3

(4. 8) reflect grain

size effects which are opposite in direction and far stronger than those of dislocation

plasticity (Hall-Petch effect). They are due to the increase, with finer grain size, in the

volume fraction of ‘disordered' material which can act as short-circuit diffusion path,

and to the higher density of sinks and sources for matter.

It is still a matter of debate whether grain-boundary softening, which has occasionally

been reported for nanocrystalline materials, can be attributed to these effects at room

temperature.One can note that in very small grains the rate of creep may no longer be controlled

by the diffusion step [as is tacitly assumed in equationsΩ

=

•

v DC

kTD

1

2ε τ (4. 7)

andΩ

=

•

bb DC

kTD

δ

ε τ

2

3

(4. 8)], but by the deposition and removal of atoms at the grain

boundaries. Ashbyxxx have shown that for such ‘interface-controlled’ diffusional creep

the grain size dependence is much weaker

2 / 1

2

1

4

D DC

kTGb

eff

b

Ω=

•

ε τ (4. 9)

This result was obtained by modeling the interface reaction as the climb motion of an

array of grain-boundary dislocations. Here Deff is an effective diffusivity, bb the Burgers

vector of a boundary dislocation and C4 another numerical constant. The


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D1/2-proportionality, which results from the assumption of a stress-dependent

dislocation density, is in better agreement with the data of Chokshi et al. (Figure 4-4).

However, because of the reduced grain size dependence, an even lower activation

energy (about 40 kJ/mol) for diffusion has to be assumed to predict realistic

deformation rates at room temperature.

Also, the motion of grain boundary dislocations is subject to a similar grain size limit as

for lattice dislocations: models based on their presence must break down once an

average grain facet of diameter D' can no longer accommodate a grain-boundary

dislocation loop [Figure 4-5(b)]. The corresponding limiting condition is, in analogy with

equation D

Gb

bD

T d ==2

τ (4. 3), given by

' D

Gbb=τ (4. 10)

The value of bb corresponds to the difference in Burgers vector between two lattice

dislocations and is therefore only a fraction of b. Hence, a stress window will exist in

which plasticity due to lattice dislocations is suppressed or slowed down [at stresses

below that given by equation D

Gb

bD

T d ==2

τ (4. 3)], but diffusion creep operates

because grain-boundary dislocations are still present and mobile.

4.2.2 Metal plastic deformation: A comparison between Cu and Ni

nanophase samples

In the previous paragraph we have studied the relation between yield stress and

grain size. Now two questions are still not answered:

1. Whether the grain boundaries in nanocrystalline materials are unusual orwhether they have the short main structure of most grain boundaries found in

conventional polycrystalline materials

2. What is the influence of the grain size on the plastic deformation mechanism

In this paragraph, we will focus on the question of dislocation activity in two different

materials Cu and Ni. Swygenhoven and al.xxxixxxii worked on molecular dynamics

simulations on nanocrystalline Ni and Cu samples in the grain size range 5-12nm.

They studied the interfaces responsible for the plastic deformation, aiming at


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providing a structural characterization of them. They also present evidence of two

competing mechanism for plastic deformation:

• At the smallest grain sizes all the deformation is accommodated in the

grain boundaries.

• At larger grain sizes lattice dislocation activity is observed.

For both materials, uniaxial deformation at the smallest loads reveals that Young’s

modulus equals the value for a polycrystalline material when the grain size is 10 nm

or higher. At smaller grains sizes a gradual reduction of the modulus is observed.

At high load, after a transient period following the application of the load, the strain

increases almost linearly with time for all the grain sizes.

Figure 4-6 : Strain rate as a function of mean grain size for Cu and Ni. [H. Van Swygenhoven, A.

Caro, D. Farkas, A molecular dynamics study of polycrystalline fcc metals at the nanoscale Grain

boundary structure and its influence on plastic deformation, 2001, Materials Science and Engineering

A.]

Figure 4-6 shows the strain rate versus the inverse of the grain size for the Ni and

Cu samples. The strain rates under these conditions are high compared with actual

experimental values, but for these small sample sizes (10–25 nm) any relativevelocity is still four orders of magnitude smaller than the velocity of sound.

At the smallest grain sizes explored the strain rate for a given applied stress

increases with decreasing grain sizes. This behaviour indicates that the Hall–Petch

slope is negative at these very fine grain sizes. An energy balance indicates that at

these sizes the total amount of grain boundary remains constant during deformation.

These observations suggest an important characteristic of plasticity in nanophase

metals under the present conditions: there is no damage accumulation duringdeformation, similar to the case of superplasticity. Careful examination of the


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samples confirms the absence of intra-grain defects. Swygenhoven and al. [4]

discussed the deformation mechanism in terms of a model based on Grain Boundary

viscosity controlled by a self-diffusion mechanism at the disordered interface,

activated by thermal energy and stress.

When similar load is applied on samples with larger average grain sizes, the

deformation rate is much smaller. These observations indicate a transition to another

deformation mechanism. They analyzed the atomic structure of Ni and Cu samples

with larger grain sizes, deformed at those stress levels that give approximately the

same strain rate as in the sample with the very small grain sizes, and compare the

structures at similar values of plastic deformation. In this way they take into account

the different elastic contribution in very fine-grained samples due to the reduction of

the Young’s modulus.

Figure 4-7 : Slice of the 12 Ni sample, deformed until a plastic deformation level of 1.4%. Open gray

symbols are perfect f.c.c., full gray are good f.c.c., red are h.c.p., green and blue are other 12- and

non-12-coordinated atoms, respectively. [H. Van Swygenhoven, M. Spaczer, A. Caro, Microscopic

description of plasticity in computer generated metallic nanophase samples: A comparison betweenCu and Ni, 1999, Acta Materialia.]

Figure 4-7 shows a section of Ni 12 nm sample, deformed to a total deformation level

of 2.7% which means a plastic deformation level of 1.4% using a tensile load of 2.6

GPa. The stacking fault observed in this section is produced by motion of Shockley

partial dislocations generated and absorbed in opposite grain boundaries. Figure 4-8

shows the Shockley partial in Ni 12 nm just emitted from a triple point.


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Figure 4-8 : Shockley partial dislocation traveling through a grain in the 12 nm Ni sample. Black atoms

are the hcp atoms forming the intrinsic stacking fault in a (1, 1, −1) plane. [H. Van Swygenhoven, A.Caro, D. Farkas, A molecular dynamics study of polycrystalline fcc metals at the nanoscale Grain

boundary structure and its influence on plastic deformation, 2001, Materials Science and Engineering

A.]

Its glide plane is (1, 1, −1); the dislocation line at this time is mainly composed of two

segments, aligned approximately along 0,1,1 − and 011 directions. The Burgers

vector being a/6 1,2,1− ; two possible additional partials could give perfect a/2 011

or a/2 0,1,1 − dislocations. Both segments in the figure are of mixed character. The

dislocation velocity estimated from sections made at different deformation times is 4

A /psec, a tenth of the speed of sound. Due to the orientation of the particular grain

relative to the strain direction, the two slip directions for the perfect dislocations 011

and 0,1,1 − have both a Schmid factor of 0.37, which is the largest possible value in

this grain.

Evidences of stacking faults inside the grains in Ni are observed at a slightly highergrain size (11 nm) compared to Cu (8 nm), probably due to the higher stacking fault

energy. In Cu, Swygenhoven and al. have observed partial dislocations which glide

on slip systems that are not necessarily those favoured by the Schmid factor.

In Ni and Cu a change in deformation mechanism is observed

• At the smallest grain sizes all deformation is accommodated in the grain

boundaries and grain boundary sliding, a process based on mechanical and


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thermally activated single atomic jumps, dominates the contribution to

deformation.

• At large grain

nano materials powder

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