Iron nanoparticles by inert gas condensation
Xing, Lijuan
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Iron nanoparticles by inert gas
condensation
Structure and magnetic characterization
The work described in this thesis was performed in the research group Nonostructured Materials and Interfaces of the Zernike Institute for Advanced Materials at University of Groningen, the Netherlands. This work is supported by the China Scholarship Council and the Zernike Institute for Advanced Materials.
Zernike Institute for Advanced Materials PhD thesis series 2018-22 ISSN: 1570-1530
ISBN: 978-94-034-0707-4
ISBN: 978-94-034-0708-1 (electronic version) Cover design: Xiaotian Zhu & Lijuan Xing Printed by Gildprint, Enschede
Iron nanoparticles by inert gas
condensation
Structure and magnetic characterization
PhD thesis
to obtain the degree of PhD at the University of Groningen
on the authority of the Rector Magnificus Prof. E. Sterken
and in accordance with the decision by the College of Deans. This thesis will be defended in public on
Monday 11 June 2018 at 12.45 hours
by
Lijuan Xing
born on 9 December 1987 in Shandong, China
Prof. B. J. Kooi Assessment Committee Prof. K. Loos Prof. M. Stöhr Prof. H. Zandvliet
Table of Contents
1.Introduction ... 1 1.1 Magnetic Nanoparticles ... 2 1.1.1 Finite-Size Effects ... 2 1.1.2 Iron Nanoparticles ... 51.1.3 Applications of Iron Nanoparticles ... 6
1.2 Wulff Construction ... 7
1.3 Kirkendall Effect ... 8
1.4 Motivation and Thesis Outline ... 11
References ... 13
2. Nanoparticle Synthesis and Characterization ... 17
2.1 Gas-Phase Synthesis of Nanoparticles ... 18
2.1.1 History ... 18
2.1.2 Inert-Gas Condensation (IGC)... 18
2.1.3 Inert Gas Condensation with Magnetron Cluster Source ... 22
2.2 Transmission Electron Microscopy ... 24
2.2.1 Beam Interactions with Specimen ... 24
2.2.2 Basic Operation Modes ... 26
2.2.3 Electron Energy Loss Spectroscopy (EELS) ... 27
2.3 Scanning Probe Microscopy ... 28
2.3.1 Atomic Force Microscopy ... 29
2.3.2 Magnetic Force Microscopy ... 35
3. Synthesis and Morphology of Iron-Iron Oxide Core-Shell Nanoparticles 43
3.1 Introduction ... 44
3.2 Experimental Methods ... 46
3.3 Results and Discussion ... 47
3.3.1 NP Size Distributions ... 47 3.3.2 NP Structure ... 49 3.3.3 NP Crystal Morphology ... 52 3.4 Conclusion ... 56 Appendix ... 58 References ... 64
4. Preparation of Tunable-sized Iron Nanoparticles Based on Magnetic Manipulation ... 69
4.1 Introduction ... 70
4.2 Experimental Methods ... 71
4.3 Results and Discussion ... 72
4.4 Conclusion ... 78
References ... 80
5. Magnetic Force Microscopy Determination of Iron Nanoparticles Magneti-zation... 83
5.1 Introduction ... 84
5.2 Experimental Section ... 85
5.3 Results and Discussion ... 86
5.4 Comparison with Theory ... 88
5.5 Conclusions ... 93
Appendix ... 95
References ... 97 Summary ... 101 Samenvatting ... 103 Acknowledgements ... 107 List of Publications ... 111 Curriculum Vitae ... 113
Chapter 1
Introduction
T
his Chapter presents a brief introduction of magnetic
nanoparticles. The finite‐size effects, which dominate the
magnetic behavior of individual nanoparticles, are discussed to
illustrate the evolution of magnetic structure and property with
particle size variation. Furthermore, an introduction of iron
nanoparticles and the applications is given briefly. Wulff
constructions based on a minimized energy solution can help to
determine the stable shape for nanocrystals. At the end, we
introduce the Kirkendall effect to illustrate the post‐fabrication
evolution of nanoparticles.
1.1 Magnetic Nanoparticles
Magnetic nanoparticles are developing into one of the most vital and fast growing topics in the field of nanotechnology due to their wide range of applications, including catalysis1,2, data storage3,4, environmental/groundwater remediation5–7, and biomedicine8–14 ( e.g. contrast enhancement in magnetic resonance imaging (MRI), drug delivery, and hyperthermia). It is well established that magnetic properties of nanoparticles, e.g. magnetic anisotropy, specific magnetic moment, Curie temperature, and coercivity, normally differ from those of the corresponding bulk materials15. As the dimension of materials is downscaled, the ratio of the surface area to the volume increases, leading to more atoms resident on the surface. For nanoparticles with a size of 1-100 nm, the significantly large surface-to-volume ratio can lead to novel physical and chemical properties compared to their bulk counterparts. In ultrafine magnetic nanostructures, the magnetization configuration might be different due to the discreteness of the crystalline lattice16. In the near surface region, the magnetic moment per atom changes dramatically with the distance from the surface owing to the discreteness resulting from reduced coordination at the surface, which therefore leads to an improved moment of NPs17.
1.1.1 Finite-Size Effects
Two features dominate the magnetic properties of nanoparticles: finite-size effects and surface effects. Finite-size effects result from, for instance, the quantum confinement of the electrons, whereas surface effects are typically related to the symmetry breaking of the crystal structure at the boundary of each particle8. Size effects, which dominate the magnetic behavior of individual nanoparticles, will be discussed briefly herein to illustrate the size dependence of magnetic structure and properties. As the particle size decreases, two limits can be defined, single-domain limit (DC) and superparamagnetic limit (DS), at which point the magnetic structures and properties of nanoparticles experience a significant change. Figure 1.1 schematically illustrates the variation of domain structures with particle size, and the coercivity evolution is also indicated qualitatively. In general, the coercivity of the superparamagnetic nanoparticles is zero above the blocking temperature. As the particle size increases beyond the superparamagnetic limit, the coercivity starts to increase dramatically until supersaturated at the single domain limit, and then gradually drops to the bulk value in the multi-domain region. The blocking temperature of superparamagnetic nanoparticles, at which point the transition between superparamagnetism and blocked state occurs, is proportional to the
nanoparticle volume and the magnetic anisotropy energy density of the nanoparticle material8,18, where the latter is a measure of the magnetic ‘hardness’ of the nanoparticle material.
Figure 1.1 Schematic illustration of the domain structure variation with particle size,
indicating the single‐domain limit, superparamagnetic limit, and the change of coercivity18.
1.1.1.1 Single-domain limit
Bulk ferromagnetic materials or large magnetic particles are composed of small regions of uniform magnetization, i.e. magnetic domains, separated by domain walls. The presence of these domains can be attributed to the balance between two energy terms: the magnetostatic energy, which increases proportionally to the volume of the material, and the domain-wall energy, which increases proportionally to the interface area between domains. In 1930, Frenkel and Dorfman first predicted that a particle of ferromagnetic materials with a size below a critical dimension would possess a single-domain structure, within which the magnetic moments of free electrons are aligned parallel and contribute to a large net magnetization18. Since then, great efforts have been devoted to the study of magnetism at the nanoscale. Results have shown that the decrease of the dimensions of the ferromagnetic materials can indeed generate the transformation from multi-domain to single-domain behavior along with an increase in coercivity19–21. As the particle size is reduced to a critical volume where it takes
more energy to generate a domain wall than to support the external magnetostatic energy (stray field) of the single domain state, the spins of free electrons within the nanoparticle will be aligned by ferromagnetic coupling into one direction acting as a single-domain magnet. The critical diameter for a spherical nanoparticle, Dc, below which the single-domain state can be established, is given by18
2 0 36 S C M AK D (1.1)
where A is the exchange constant, K is the effective anisotropy constant that measures the energy per unit volume required to flip the magnetization direction, μ0 is the vacuum permeability, and MS is the saturation magnetization. It was found that ferromagnetic crystals have a critical size of a few tens of nanometers, which depends on the material with the additional influence from various anisotropy energy terms8.
For multi-domain nanoparticles, the alignment of the magnetization direction within each domain is controlled by both the domain wall motion and the anisotropy energy KV (where V describes the domain volume). For single-domain nanoparticles, where domain walls are absent, the reversal of the spin orientation is realized by spin rotation instead of domain wall motion. The latter contributes to the very high coercivity observed for small nanoparticles22. Shape anisotropy also influences the critical dimension of the single-domain limit. The spherical particles, in principle, have a smaller critical size compared to their counterparts with a higher shape anisotropy.
1.1.1.2 Superparamangetic limit
As the particle size decreases further below the single-domain limit, the energy barrier KV continues to reduce due to a decreasing volume, generally at a disadvantage in the competition with thermal energy kBT (kB is the Boltzmann constant, and T is the temperature). As manifested in Figure 1.1, the decrease of the particle size below the single-domain limit is accompanied by the reduction of coercivity23,24. When a critical size D
S is reached, where kBT overtakes KV , the thermal excitations helps to overcome the single-energy barrier so that the total magnetization behaves as a super-spin inside each particle25 showing a high saturation magnetization (MS) close to the value of their larger ferromagnetic counterparts with no coercivity.
The magnetization reversal behavior of magnetic nanoparticles is sensitive to temperature. The characteristic time of the thermal fluctuation of the particle magnetization τN is given by Néel relaxation time18
0exp N B KV k T (1.2)
where τ0 is a pre-factor constant approximately 10-9 s18. The measurement time scale is defined as τM which is around 100 s for a typical laboratory experimental condition. If the relaxation time τN is shorter than the measurement time τM, the rapid fluctuations of the particle moments mimics superparamagnetism. While in the opposite situation, where the relaxation time τN is larger than τM, thermal fluctuations do not allow the accomplishment of the magnetization reversal resulting in a so-called “blocked” state18,25. The temperature at which τ
M = τN is defined by the blocking temperature TB, which is given by18
0 ln M B B k KV T . (1.3)
The blocking temperature thus depends on the effective anisotropy constant, the particle size, the applied magnetic field, and the measurement time.
1.1.2 Iron Nanoparticles
Iron is the fourth most plentiful element in the earth’s crust and the most ubiquitous one of the transition metals. Nowadays, much effort has been devoted to the study of magnetic materials and applications, and iron is among the most attractive candidates. As a ferromagnetic material, iron has a high saturation magnetization (σS=222 Am2kg-1 at 0 K, and σS=218 Am2kg-1 at 293 K). The latter combined with a high enough Curie temperature (TC=1043 K) allows the majority applications to be at room temperature26. Moreover, iron is a very soft magnetic material with a low magnetocrystalline anisotropy. As for all magnetic nanoparticles, a sufficiently small size results in the superparamagnetic behavior of iron nanoparticles. Due to its low magnetocrystalline anisotropy, the critical size for the superparamagnetic limit is larger than cobalt, which has the second-highest room temperature saturation magnetization only to iron. Therefore, larger-size superparamagnetic
iron nanoparticles can be prepared with a higher moment that is not possible to be realized by any of the other magnetic metals26.
1.1.3 Applications of Iron Nanoparticles
Iron nanoparticles can be used in a variety of fields, e.g. magnetic recording media, catalysis, as well as biomedical applications including magnetic labels for highly efficient bioseparation/drug delivery, highly sensitive biodetection, and hyperthermia treatment27. The implementable customization makes iron a competitive candidate as a magnetic material. Iron nanoparticles have been commercially used as magnetic recording media26, where high-aspect-ratio iron particles behave as very hard permanent magnets with large shape anisotropy, contributing to a high-capacity and reliable data storage methods26. The application of iron as a catalyst starts with its functioning in the Fischer-Tropsch synthesis28,29, followed by the further study of alternative iron nanoparticles that have a catalytic activity several times that of a conventional material30.
The potential biomedical applications of iron nanoparticles will be discussed to explore what advantages the zero-valent state can potentially offer as compared to the typically used iron oxides31–33. For drug delivery, a magnetic gradient is applied to afford a directed force on the particles26. Since the exerted force is proportional to the magnetization, the high-moment nanoparticles are favorable. Iron nanoparticles, as compared with any of its oxides, can maintain superparamagnetism at a larger size, therefore offering higher particle moments that contributes to better functioning in directed drug delivery.
In magnetic resonance imaging (MRI), superparamagnetic iron oxide particles are now commercially used as contrast enhancers, and the applied high magnetic field results in the saturation of the adopted superparamagnetic nanoparticles. Zero-valent iron, which exhibits a saturated magnetization double that of its magnetic oxides, can therefore provide higher image contrasts34–36.
Hyperthermia37,38 treatment is based upon the idea of localized and selective heating of diseased tissue, which can be realized by employing magnetic nanoparticles within an alternating magnetic field of suitable amplitude and frequency. Superparamagnetic nanoparticles, with a high saturation magnetization combined with low anisotropy, can serve as an ideal option for efficient heating mediators. Note that since for biomedical applications iron particles are present in aqueous, salt-containing systems, a probable drawback of iron is its reactivity. As a result, a protective coating is necessary to provide an effective barrier against oxygen and other oxidizing agents26.
1.2 Wulff Construction
The formation of a nanoparticle shape can be explained by the minimum energy solution, i.e. the stable shapes always possess the lowest surface energy. The analysis of nanocrystals, compared to liquid droplets or amorphous nanoparticles, is more complicated due to the various stabilities of different facets resulting from the different densities of surface atoms, charges, and ligands. Provided that all the facets of a crystal are indistinctive and equally favored, a spherical shape will be preferred because of its lowest surface to volume ratio as is shown in Figure 1.2. The other extreme situation is a sharp-edged polyhedron which is preferred with only one stable facet, e.g. cubes with {100} facets or octahedrons with {111} facets (see Figure 1.2). However, most of the nanocrystals lie in between these two extremes, and the lowest energy shape depends on the relative stability of the facets. Nanocrystals will adopt a truncated shape, gradually close to spherical, when the diversity in the facets stability is reduced.
Figure 1.2 The lowest energy structure of a nanocrystal exhibits dependence on the relative
stability of its facets39.
The total surface energy of a system is the sum of each facet area weighted by the corresponding surface energy. The latter is given by39
i i
A
G
(1.4)where γ is the surface energy of a facet and gives the corresponding surface area. The standard process to create the Wulff shape is to plot the surface energy as a
function of the relative angles the normals of the surface planes make and then take the inner envelope formed by these planes. Figure 1.3 illustrates the simplified situation where the three dimensional (3D) structure can be represented by two dimensional (2D) projection (here for Figure 1.3 (a) along the [110] direction) such that only the {100} and {111} planes present on the surface and then from the cubic symmetry of the structure still the overall 3D nanoparticle shape can be reconstructed as shown by Figure 1.3 (b). In principle, if high index planes would be present, this will result in increasing complexity of the overall particle shape.
Figure 1.3 Illustration of the Wulff construction for a cubic crystal structure where {100}
and {111} planes dominate: (a) [110] projection of the particle; (b) the corresponding 3D structure, with green denoted the {100} facets, and yellow the {111} facets40.
1.3 Kirkendall Effect
The transformation of nanoparticles to hollow or porous structures through nanoscale Kirkendall effect was first reported in 200441, and the void formation during oxidation was attributed to the difference in diffusion rates between two components in a diffusion couple. We show in Figure 1.4 (b) the formation of voids at the metal-oxide interface observed after 40-month exposure to ambient air, together with an overview image of the as-deposited nanoparticles shown in Figure 1.4 (a). A close-up of the particle morphology is shown in the right column of Figure 1.4 (b) where the voids are labeled with arrows.
The Kirkendall effect is a classical phenomenon in metallurgy42, which describes the nonequilibrium mutual diffusion process through an interface of two metals with the occurrence of vacancy diffusions to compensate for the unequality of material flow. Figure 1.5 schematically illustrates the process of the Kirkendall effect in the bulk phase diffusion couple A-B. As indicated, there is a difference between the diffusion rates of the two materials, resulting in an unequal transport of A and B to the other side, which is then accompanied by vacancy formation and diffusion. This effect can give rise to the concentration of voids located near the bond interface within material showing faster-diffusion43–45.
Figure 1.4 Formation of voids at the interface between the iron core and the oxide shell.
(a) Overview image of as‐deposited core‐shell structured iron nanoparticles. (b) Overview image of the same sample after 40‐month exposure to ambient air with a close‐up of particles in the right column showing the formation of voids.
Coming to the nanoscale, the Kirkendall effect can also be observed in nanoscale size compound systems, typically in oxides, sulfides, and nitrides, where oxidation, sulfidation, or nitridation takes place with a faster outward diffusion rate of metal cations through the compound interface46. The difference in the outward diffusion of metal cations and the inward diffusion of anions gives rise to an inward flux of vacancies to balance the diffusivity difference. The process of nanoscale Kirkendall effect is accompanied by the thickening of the compound layer and the loss of the core material density.
Figure 1.5 Schematic illustration of the Kirkendal effect where nonequilibrium lattice
diffusion at the interface takes place. JA, JB and JV represent the diffussion fluxes of metal
A, B, and vacancies, respectively47.
Figure 1.6 shows a general model for the formation of a hollow structure induced by the Kirkendall effect in nanoscale particles. It then holds that A exhibits a faster diffusion flux than B. In the initial stage (Figure 1.6 (a)), the exchange of material through the interface is realized by bulk interdiffusion assisted by the inward diffusion of vacancies. The voids located close to the interface result from the coalescence of the inward diffused vacancies, and grow larger as the interdiffusion proceeds. Further coalescence of voids can form larger ones, as described in Figure 1.6 (b), blocking the connections for lattice diffusion. New bridges have to be established subsequently as fast transport paths for the remaining material A, which can then redistribute itself at the open surface of the compound layer by surface diffusion. As the diffusion continues, A is gradually exhausted with more vacancies generated. Finally smooth and uniform hollow compound nanocrystals can be obtained.
Figure 1.6 Generalized model for the formation of hollow structures based on a
combination of Kirkendall effect with surface diffusion process48.
1.4 Motivation and Thesis Outline
Magnetic nanoparticles are considered promising candidates for applications in magnetic recording, environmental remediation, and biomedicine. Iron, as the fourth most plentiful element with a high saturation magnetization, is among the most attractive magnetic materials. Its low magnetocrystalline anisotropy contributes to lager size superparamagnetic nanoparticles with a higher moment that is not possible to be realized by any of the other materials, making iron nanoparticles more efficient in tumor diagnostic and therapeutic. Iron nanoparticles can be produced by various methods, and the cluster source adopted in our work is a combination of magnetron sputtering and inert gas aggregation technique, giving solvent-free and monodispersed iron nanoparticles with higher diversity of crystal motifs than it is achieved with chemical techniques. The downscaling of nanoparticles results in a sharp increase of atoms resident on the surface, and the variant particle shapes lead to the different crystallographic surfaces that enclose the particle, contributing to different chemical and physical properties.
Magnetic properties of nanoparticles show strong sensitivity to particle size and shape, whereas the standard magnetic characterization techniques, as for example the superconducting quantum interference devices, give only the magnetic properties of nanoparticles as ensemble of the nanostructures or equivalently the macro-performance. In the present thesis, magnetic structures of individual iron nanoparticles are probed with magnetic force microscopy, which provides the possibility for the subsequent determination of the precise single-domain and superparamagnetic limit of iron.
Chapter 2 introduces the experimental techniques employed in this thesis.
Iron nanoparticles with tunable sizes are synthesized by inert gas condensation with a magnetron sputtering source. Transmission electron microscopy is used to determine the nanoparticle size, structure, and composition. Magnetic force microscopy is employed to probe the magnetic structure and the magnetization orientation of iron nanoparticles.
Chapter 3 is a study devoted to the precise structure and constitution of iron
nanoparticles, as well as the particle shape evolution with size variation. The nanoparticles are constituted by a single crystal iron core, as a combined analysis of high resolution transmission electron microscopy (HRTEM) and electron energy loss spectroscopy (EELS) indicate, and a polycrystalline shell (Fe3O4 and/or γ-Fe2O3). The particle size and shape show strong dependence on the gas environment in the cluster source. Based on Wulff construction analysis, iron nanoparticles adopt different morphologies depending on the ratio of the growth rate along the <100> and the <110> directions.
Chapter 4 gives a method to decrease the minimum particle size that can be
obtained by introducing a backing plate in between the target and the magnetron. The magnetic field distribution above the target surface can be modified by the variant target-magnetron spacing, resulting in smaller particles with a thicker backing plate. Particle morphologies evolves from faceted to close-to-spherical polyhedral shapes with increasing spacer thickness.
Chapter 5 describes the determination of the ferromagnetism of iron
nanoparticles with a size ~50-70 nm using magnetic force microscopy. Indeed, the reversal of the magnetic contrasts observed with opposite tip polarities confirms the ferromagnetism of the measured nanoparticles. Moreover, the bright and dark contrasts agree with the single-domain structure, and the specific magnetization orientation can be probed by theoretical analysis of the magnetic force microscopy data.
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Chapter 2
Nanoparticle Synthesis and Characterization
T
his Chapter describes the techniques utilized for the
production of nanoparticles, and the subsequent experimental
methods employed for sample characterization and data analysis.
A nanoparticle deposition source, which combined high pressure
magnetron sputtering and gas condensation, was used to produce
nanoparticles. Transmission Electron Microscope (TEM) and
Scanning Probe Microscope (SPM) were used to determine the
nanoparticle morphology, structure, and their magnetic
properties.
2.1 Gas-Phase Synthesis of Nanoparticles
Gas-phase synthesis has been extensively explored as a versatile technique to produce a wide variety of nanostructured materials. This bottom-up method puts individual atoms or molecules together to form the desired nanoparticles. Compared to top-down processing that breaks down the bulk material into nanometer-sized particles, bottom-up techniques provide remarkably better control in size and shape of the resultant nano-structure1.
2.1.1 History
Inert-gas condensation derives from studies in the 1930s when Pfund et al. reported nucleation and growth of clusters in a noble-gas atmosphere and managed to produce nanoparticles via the referred inert-gas evaporation method. This technique affords more options of target materials. The subsequent study by Granqvist and Buhrman6 proposed modified experimental technique. Various metals were
evaporated from a temperature-stabilized source, instead of a resistant filament, into a low pressure inert gas atmosphere to produce ultrafine particles with a well-controlled size and size distribution. Parameters such as evaporation rate, type of gas, and gas pressure were defined as factors that influence the particle size. However, the real breakthrough with respect to the development of this technique came about in 1981 when Gleiter referred to the products as “microcrystalline materials” or “interfacial materials”. It was suggested that ultrafine particles were produced by in-situ consolidation with a large proportion of atoms located in the grain boundaries3. Modifications and improvements have been made to the initial experimental setup ever since to make inert-gas condensation nowadays a versatile technique to synthesize a large variety of nanostructured materials.
2.1.2 Inert-Gas Condensation (IGC)
Synthesis of nanostructured materials by inert-gas condensation involves two steps: evaporation of target materials, and controlled condensation. In general, the main apparatus consists of an ultrahigh-vacuum (UHV) system together with one or more vapor sources, and a cluster collection part. The generated metal vapor is confined by the local inert gas pressure and cooled by repetitive collision with the carrier gas. Supersaturation is consequently achieved, in which state nucleation occurs resulting in the formation of nanoparticles.
2.1.2.1 Cluster sources
In general, nanoparticles originate from a vapor source inside a vacuum chamber containing inert gas. The adopted vapor source evolved from a resistive filament in the earliest stage to a temperature-stabilized oven in 19762 to maintain a constant evaporation rate and consequently a well-controlled particle size. Since then various techniques were developed and modified to produce clusters, including thermal evaporation, sputtering, and laser ablation. Fundamental choices have to be made when designing an experimental system, depending on the type of desired clusters, the size and species, the temperature requirement, and whether they should be ionized4.
Thermal evaporation using oven sources provides a simple and reliable manner to produce nanoparticles with a wide size range; nevertheless, this method is not applicable to substances with high cohesive energies that require high temperature for the evaporation. Moreover, a large quantity of starting materials as well as the reactivity of metal vapors with ovens needs to be taken into account in the experimental setup. Laser evaporation technique focuses a high-energy pulsed laser on target materials to generate clusters5. The high temperature caused by the highly efficient vaporization overcomes the limitation of thermal evaporation, but a suitable laser can be quite expensive. Magnetron sputtering was first combined with inert gas condensation by Haberland et al.6, and the sputtering source can be applied to not only metals but insulators (with radiofrequency sputtering). Despite of the different vapor source, the subsequent condensation, including cluster nucleation and growth, follows the same principle.
2.1.2.2 Achieving supersaturation
Generally speaking, the high pressure of inert gas in the aggregation volume contributes to the supersaturation of the metal vapor. This local confinement decreases the diffusion rate of the evaporated atoms away from the source region by frequent collisions between inert gas atoms and metal atoms. The collisions, additionally, result in energy loss and consequently the cooling of metal atoms, further shortening the mean free path. Based on Granqvist and Buhrman’s work, heavier gas atoms are more effective in limiting the mean free path.
2.1.2.3 Nucleation
Nucleation from a continuous vapor phase can occur heterogeneously or homogeneously. Heterogeneous nucleation occurs with foreign nuclei or dust particles being present in the vapor phase. However, homogeneous nucleation takes
place without any foreign particles, under which condition the metal vapor condenses to form embryonic droplets or nuclei. During gas phase synthesis of nanoparticles, homogeneous nucleation occurs when a sufficiently high supersaturation is achieved. Classical nucleation theory is based on the assumption that the formed embryonic clusters can be described as spherical liquid drops with the bulk liquid density inside and the vapor density outside. The cluster free energy, relative to the vapor phase, consists of two parts: a positive contribution from the surface free energy, and a negative contribution from the bulk free energy difference between the metal vapor and the liquid. The surface free energy originates from the reversible work required for the development of the interface between the liquid drop and the vapor atmosphere. The interface energy needed to generate a cluster containing n atoms or molecules can be described by7
n 4
3v 4
23n23A
(2.1)
where represents the surface energy per unite area, A(n) is the total surface area, and v gives the atomic volume in the bulk liquid. The contribution resulting from the bulk free energy difference produced during the transfer of the n molecules from vapor to cluster is given by7:
lv
nnkBTln
P Pe
(2.2)where l and v represent the chemical potentials per molecule in the bulk liquid and vapor state, respectively, kBis the Boltzmann constant, T is the temperature, and P Pe shows the supersaturation ratio with P the vapor pressure and Pe the equilibrium or saturation vapor pressure. The aforementioned two contributions make up the reversible free energy (work) needed to form a cluster consisting of n atoms or molecules, which is given by7:
n
v
n nkBT
P Pe
W 4 3 4 23 23 ln (2.3)
During the inert-gas condensation, it is thermodynamically stable to form solid state materials, i.e. nanoparticles in this case, relative to sustaining vapor phase. While the positive contribution from the surface free energy results in a barrier in the
nucleation. Equation (2.3) describes the competition of the surface free energy and the bulk free energy, which determines cluster stability or cluster concentration. The smallest stable cluster that can form with a free energy that decreases beyond this size (and increases up to this size) is determined by the condition W n0, giving the critical cluster size
n
*
andr
*
as follows:3 2 3 )) ln( ( 3 32 * v kBT P Pe n (2.4) r*2v
kTln
PPe
(2.5) Therefore, the barrier height W(n*) is determined by substitutingn
*
into equation (2.3), giving 3 2 2 )) ln( ( 3 16 *) (n v kBT P Pe W (2.6)A high supersaturation results in a decrease in the critical nucleus size as well as the barrier height, allowing more clusters to grow into stable droplets. However, for extremely high supersaturation, the steady-state nucleation theory is no longer applicable as the critical cluster size may reduce down to a few atoms, which is unreasonable to be regarded as a macroscopic entity with macroscopic properties, as for example, surface tension and density7.
2.1.2.4 Cluster growth
Once nucleation occurs, condensation of the vapor-phase atoms on the nuclei contribute to the growth of the clusters to some extent, which, on the other hand, depletes the partial pressure of the metal vapor and quenches further nucleus formation. However, cluster growth is predominantly attained by coalescence when clusters collide in high enough temperature, lose their kinetic energy, and form a larger cluster. Once the clusters are cooled down to a level that cannot affords the proceeding of coalescence, coagulation predominates the growth of clusters forming loose agglomerates with open structures. The growth time is determined by the efficiency of the cooling effect. In case of short growth time or low particle density, cluster agglomerations are small. Granqvist and Burhman8 reported that
the final particles size is principally an integration of several coalescence processes, leading to a log-normal size distribution.
2.1.3 Inert Gas Condensation with Magnetron Cluster Source
The instrument employed to deposit Fe nanoparticles (NPs) is a home-modified Nanosys50 from Mantis Deposition Ltd. (http://www.mantisdeposition.com) which is a combination of magnetron sputtering and gas condensation. Magnetron sputtering is applied as the vapor source. Figure 2.1 gives the system setup (Figure 2.1(a) and (b)), and details of nanoparticle sources (Figure 1(c)) consisting of two chambers: the aggregation chamber where nucleation and cluster growth take place, and the main chamber where produced nanoparticles are collected (as shown in Figure 2.1(a)). Two Leybold turbo molecular pumps with a capacity of 300 lt/s are employed to evacuate the system, and a Varian LTH 10 scroll vacuum pump is used to back the evacuation. The vacuum in the main and aggregation chamber can reach 1×10-8 mbar and 1×10-6 mbar, respectively. The pressure sensors in the two chambers give pressure readings on the Mantis controller (shown in Figure 2.1(b)). The settings can be adjusted and monitored by the controller.
The sputtering process starts with the introduction of gas flow into the system where inert gas is generally used due to the minimal interference with the target material. The potential difference, caused by the applied voltage, accelerate electrons away from the target that acts as the cathode (with the magnetron cover acting as the anode), and the collisions between these electrons and inert gas atoms, normally Ar, result in the ionization of the sputtering gas forming excited species. The ionized Ar atoms (Ar+) are accelerated by the potential difference and subsequently impact on the target breaking off particles (atoms, dimers etc.) which together compose the desired target material vapor. The release of secondary electrons are expected to occur accompanying the sputtering of the target, which are repelled away from the target and feed the ionization process further. The magnetron positioned under the target can enhance the efficiency of the ionization as the helical path that free electrons follow in the magnetic field results in a longer effective path length and therefore more chances of collisions with the sputtering gas atoms.
The material vapor is then swept by the gas flow to the aggregation volume just above the plasma where the vapor is confined by the local inert gas pressure and achieves supersaturation. The high pressure in the aggregation chamber can reduce the sputtering rate because collisions with inert gas atoms drain the energy
of the ions so that fewer of them keep sufficient threshold energy for the subsequent sputtering. However, in most cases there is an adequately broad pressure range in which a decent balance can be achieved between achieving supersaturation and maintaining an acceptable sputtering rate.
Figure 2.1 The nanoparticle deposition system (a), and the associated controller (b). Details
A magnetron sputtering system, as is schematically illustrated in Figure 2.1 (c), consists of the following main components: a magnetron head, a double gas inlet system, water cooling system for both magnetron head and aggregation chamber wall. A target material disk (2 inches in diameter) is placed on the magnetron, and an anode is then mounted on top connected to a TDK-Lambda Genesys Gen 600-1.3 programmable DC power supply with a range up to 600 V and 1.3 A. An adaptable DC voltage is applied between the target (cathode) and the anode, and the discharge power can be tuned by a built-in voltage and current limiter.
Once supersaturation is achieved, nucleation and cluster growth take place to produce nanoparticles with desired particle size. The produced nanoparticles are then carried by the gas flow to the main chamber because of the pressure difference between the two chambers, and then land on collecting substrates. The deposition rate can be monitored by a home-built quartz crystal microbalance (QCM) that is located slightly off-center of the conical cluster beam.
2.2 Transmission Electron Microscopy
Transmission Electron Microscopy (TEM) is a powerful technique that makes use of a high energy electron beam with high energy (200 keV), instead of optical light, to achieve high spatial resolution characterization of morphology, crystallography, and chemical structure depending on the operation mode. The high energy electron beam create very short electron wave (of a few pm, 2.5 pm in case of 200 keV) allowing sub-nanometer scale structure to be resolved with magnetic lenses9, and atomic resolution can be readily obtained according to the Rayleigh criterion. In this case the highest obtainable resolution is directly proportional to the wavelength of the adopted radiation. However, in practice the resolution is not diffraction limited, but is limited by spherical aberration. However, in this case still a resolution of a few Angstrom is readily achieved. Besides its capability of high resolution imaging, interactions between the electron beam and the specimen result in characteristic processes that can be exploited in spectroscopies such as energy dispersive x-ray spectroscopy (EDX/EDS), and electron energy loss spectroscopy (EELS).
2.2.1 Beam Interactions with Specimen
The incident electron beam is transmitted through an ultrathin specimen, and various signals can be generated from the interactions between the highly energetic
electron beam with the ultrathin specimen, as shown in Figure 2.2, among which the elastically scattered electrons are basically responsible for the possibility to perform TEM imaging. The formation of elastically scattered electrons can be attributed to the interaction between the incident electron beam with the nuclei of the atoms in the sample. The scattering results in a relatively large deviation in the path of the electrons, but the velocity (
v
) and wavelength (
) exhibit no variation with little or no energy loss. The elastic scattering for non-crystalline materials depends principally on the mass-thickness of the sample, with more electrons scattered for samples with large mass-thickness. For crystalline materials, the scattering mainly results from Bragg diffraction, depending on the crystal structure and the relative orientation with respect to the incident beam. These elastically scattered electrons are focused by electromagnetic lenses to form images in the electron microscope. Interactions of the beam with orbital electrons generate inelastically scattered electrons, with a slight deviation in the path (104 radians),which are characterized by a loss of energy. The inelastic scattering of the electrons is generally accompanies by specimen damage. However, for TEM samples with a thickness smaller than 100 nm, as is normally the case, most of the highly accelerated electrons transmit through the specimen with inelastically scattered ones being a minor fraction.
Figure 2.2 Signals generated when a high‐energy electron beam interacts with a thin
specimen. The directions shown for each signal do not always present the physical direction of the signal, but indicate, in a relative manner, where the signal is strongest or where it is detected10.
2.2.2 Basic Operation Modes
The interactions between the incident electron beam and the specimen form the image that is subsequently magnified and focused on an imaging device (e.g. a photographic film, a fluorescent screen) or detected by a CCD camera, as schematically illustrated in Figure 2.3 (a). Different operating modes can be realized by lens strength variation or lens deactivation. The ray diagram of imaging and diffraction mode is shown in Figure 2.3 (b).
Figure 2.3 schematic Diagram of (a) a transmission electron microscope, and (b) imaging
and diffraction modes in TEM10,11.
2.2.2.1 Bright field imaging
In imaging mode, an objective aperture is inserted in the back-focal plane of the objective lens, as illustrated in Figure 2.3 (b) right. For bright field imaging, a small objective aperture is used with the central beam selected and the rest signal blocked. The selected signal is subsequently magnified and projected by intermediate and projector lenses to obtain the sample image. The image can be
assumed to be a simple two dimensional projection of the sample down the optic axis indicating the mass thickness distribution.
2.2.2.2 Diffraction
Diffraction contrast can be produced when the incident beam interacts with a crystalline sample, resulting in Bragg scattering that disperses electrons into discrete locations (diffraction spots). In diffraction mode, a selected area aperture is placed in the back-focal plane to define the specimen area to be projected on the screen.
Selected area electron diffraction (SAED), as a diffraction technique, is a powerful tool for crystal structure and orientation determination, as well as lattice defects identification. As can be noticed in the schematic of diffraction mode (Figure 2.3(b) left), a selected area aperture is inserted into the beam path, located below the sample holder and allowing selection of the area from which the diffraction pattern is recorded. The high-energy electron beam, typically with an energy of 100-400 keV, passes through the ultrathin sample and exhibits a wave-like behavior. As the spacing between atoms in a solid is around a hundred times larger than the wavelength of the high-energy electrons (a few thousands of a nanometer), atoms act as a diffraction grating resulting in the diffraction of electrons. Consequently, part of the electrons are scattered to particular angles that are determined by the crystal structure of the solid material, while the remaining part pass through the specimen without deflection. The resulted discrete diffraction spots are collected on the screen with each spot corresponding to a satisfied diffraction condition of the crystal structure. Individual spots will be obtained from a single crystal, whereas ring patterns form for polycrystalline materials or assemblies of randomly oriented single crystals.
2.2.3 Electron Energy Loss Spectroscopy (EELS)
The interactions between electrons and matter generate both elastically and inelastically scattered electrons. The elastically scattered ones contribute to imaging and diffraction patterns as mentioned above. Inelastically scattered electrons exhibit a characteristic energy loss, which highly depends on the atomic species present in the material. In this respect, a typical EEL spectrum is shown in Figure 2.4, which shows three regions, i.e. zero-loss peak (ZLP), Low-loss region, and core-loss region. ZLP represents the elastically scattered electrons with zero or negligible energy loss. The low-loss region covers the range 0-50 eV in the spectrum. It indicates the energy loss in the excitation of the valence electrons
within the specimen, and the broad peak is the representation of the resonant oscillations of the valence electrons (i.e. plasmons). The core-loss region gives the inner-core electronic structure of the atoms that are present in the sample. The energy loss of the core shell ionized edges determines the presence of certain atomic species in the sample, while the fine structures relates to the specific chemical environment, e.g. show variations for different valence states of atoms and different types of bonding between atoms.
Figure 2.4 A typical energy loss spectrum: (a) low‐loss region, and (b) core‐loss region,
showing ionization edges12.
2.3 Scanning Probe Microscopy
In 1981, G. Binnig et al. observed vacuum tunneling of electrons between a sharp tungsten tip and a platinum sample, which inspired the development of scanning tunneling microscope (STM). The first practice of this novel technique was reported in 1982 when G. Binnig et al.13 used vacuum tunneling to obtain three-dimensional surface topographic images with an atomic-scale resolution. STM determines the surface topography by using the dependence of the tunneling current on the tip-sample separation, and it allows the imaging of atomic structures in real space, making the structures at the atomic level directly ‘visible’. Furthermore, the sharp tip provides the possibility to detect physical properties of materials on a small scale. However, besides vacuum tunneling of electrons, new means had been explored by which local properties of matter could be probed, triggering the invention of a whole class of techniques referred to as scanning probe microscopes (SPMs).
Among the various techniques, atomic force microscope (AFM) was developed in 1986 to image topographical structures of both conducting and insulating surfaces with atomic-scale resolution14. The introduction of AFM overcomes the limit of STM that is only applicable to conductors or semiconductors. In AFM, sample surface is scanned by a tip, which is mounted to a cantilever spring. With the tip approaching the sample surface, AFM images are obtained by measurement of the forces between the atoms on the sample and the atoms on the tip. The following exploitation of SPMs was motivated by making use of almost every kind of interactions between the tip and sample of which one can think, to characterize topographical structures as well as physical properties.
In general terms, SPMs describe the family of instruments that were developed to characterize surfaces of materials by employing a sharp probe scanning over the surface with a very small tip-sample separation. AFM, together with its “daughter” techniques such as magnetic force and Kelvin probe microscopy (MFM-KPFM), has evolved to a crucial widely used SPM techniques.
2.3.1 Atomic Force Microscopy
AFM employs a cantilever with a sharp tip to provide the means for sensing the forces exerted on the tip by the sample surface atoms, and the cantilever is, in any case, a critical component. To detect the small interatomic forces, the cantilever should be insensitive to external disturbance from the surroundings, such as building vibrations (near 100 Hz). Therefore, cantilevers with high resonance frequency, greater than 2 kHz, should be employed to minimize the extraneous vibrational noise. Since the imaging forces in AFM are typically in the range of 10 -12-10-7 N, the spring constant of the cantilever should be less than 0.01 N/m so that a deflection greater than 1 Å can be produced for a force of 10-12 N contributing to the high sensitivity of this technique.
The schematic of AFM operation is demonstrated in Figure 2.5. A cantilever is fixed to the modulation piezo, and the sample is attached to a three-dimensional piezoelectric drive, i.e. the x, y, a scanner. The tip mounted at the end of the cantilever is brought in close proximity to the sample surface to sense the tip-sample interaction forces. A focused laser beam reflects off the back side of the deflected cantilever, and the displacement of the cantilever when scanning the sample surface is amplified in the movement of the reflected laser beam. The beam is subsequently collected by a position sensitive detector consisting of four closely spaced photodiodes. The amplified signal resulted from the angular displacement (including both normal bending and torsion) of the cantilever gives more light in
one photodiode than the others, producing an output signal that is proportional to the cantilever deflection. The differential signal is converted to voltage and provides feedback signal to maintain the force acting on the stylus at a constant level.
Figure 2.5 schematic of AFM operation15
2.3.1.1 Imaging modes
The commonly used imaging modes can be divided into two distinct operations: static and dynamic AFM. In static mode, the surface topography is mapped by scanning with a deflection of the tip in z direction and a constant tip-sample force/separation. The cantilever deflection is monitored during the scanning, and any variation is followed by a vertical movement of the tip to maintain a preset deflection value. According to Hooke’s law, the displacement of the cantilever is proportional to the applied force. So, in other words, the feedback loop maintains a constant force between the tip and sample, and the position of the cantilever is changed in such a way that the cantilever bending produces a constant force. The changes in z-direction required to maintain a constant tip-sample force/separation give the topographic information of the sample surface. Static mode operated with a close proximity to the sample surface and a repulsive tip-sample interaction is referred to as contact mode in which condition the last atoms of the tip-apex are
directly contacted to the sample surface. However, during scanning, the sample experiences compressive forces attributed to tip-sample interaction, as well as shear forces owing to the lateral movement with respect to the tip, both of which can substantially results in the deterioration of the tip and the sample. Besides, the stick-slip motion of the tip caused by capillary condensation and the lateral forces, combined with the degradation of the tip shape due to the tip-sample interaction, lead to a relatively poor resolution of the resulting imaging.
Dynamic AFM is operated with an oscillating cantilever, and the tip-sample separation is normally in the range where it shows a repulsive interaction. This non-contact mode provides a reliable method to image soft materials that would be damaged by the direct contact with the probe. In dynamic mode, the cantilever oscillates near its resonance frequency driven by a piezoelectric actuator. As the tip approaches the sample surface, the oscillation state of the cantilever, including the amplitude, the resonance frequency as well as the phase shift, is changed by the tip-sample interaction with respect to the driving signal. Any of the three type of changes can be detected to track the topography of surfaces and simultaneously provide the feedback signal to maintain a constant distance between the tip and sample and therefore a constant force. Two dynamic modes are mainly used for the scanning of the surface topography, i.e. amplitude modulation (AM) AFM and frequency modulation (FM) AFM, with different feedback signals. In dynamic mode, a tip-sample separation of about 5-15 nm is maintained, where the topographic information derives from the van der Waals forces between the tip and sample.
In view of the drawbacks of the aforementioned modes, amplitude modulation AFM was later developed to be used with a closer tip-sample distance involving repulsive interactions, which is referred to as “Tapping mode”16. This mode makes it possible to achieve high resolution imaging without inducing destructive frictional forces. The cantilever oscillates near its resonance frequency with an amplitude typically in the range 20-100 nm. A certain distance between the tip and sample surface is maintained to establish an intermittent contact, where the probe strike the sample surface at the lowest position of each oscillation. However, for a large range of cantilever positions in z direction, the energy associated with the vibration can sufficiently overcome the stickiness of the surface, which is attributed to the large oscillation amplitude in tapping mode. The perturbation of the cantilever oscillation amplitude, resulted from the intermittent contact with the sample surface, is detected by the feedback system. The deviated amplitude can subsequently be used as a setpoint which is maintained constant by a height modulation throughout the lateral scanning, generating a topographic image.
Tapping mode AFM provides topographic imaging with high resolution due to its minimized sample deformation attributed to the reduced contact force per strike as well as the essentially eliminated lateral shear force.
2.3.1.2 Fundamentals of force microscopy
The basic concept of non-contact force microscopy is to raise the cantilever probe to a certain height away from the sample surface and to measure the long-range interactions exerted on the cantilever. The tip scans across the surface in a raster pattern, allowing the collection of special variations of the probe-sample interaction by detecting the change of the cantilever oscillation. The resonance frequency of the cantilever describes the characteristic part of the dynamic properties of the probe, which is be given by
m
c
f
0
(2.7) where c is the cantilever spring constant and m is the effective mass. In general, the sinusoidal oscillation of the cantilever is actuated by bimorph piezoelectric modulation with a frequency and an amplitude A0, and the tip likewise vibrates sinusoidally with a distinct amplitude A and a phase shift Δφ with respect to the drive signal from the piezoelectric actuator. With a large enough bandwidth, the motion of the tip is monitored by the deflection sensor of the force microscope, which is preferentially an optical sensor. The output motion from the deflection sensor can be described by20
d
d
A
f
ft
f
t
d
f
t
d
cos
Q
0 0 0 2 0 0 2 2
(2.8)where d0 represents the tip-sample separation with zero oscillation amplitude (i.e. the user-defined lift height) and d(t) the instantaneous distance. Besides the intrinsic properties of the cantilever itself, the equation also includes the exoteric influences by introducing a quality factor Q that is determined by the damping factor :
