Dynamics of thermally induced assembly of Au nanoislands from a thin Au layer on Ge(001)

Nikiel, Marek; Jany, Benedykt R.; Wrana, Dominik; Szajna, Konrad; Janas, Arkadiusz; Kozubski, R.

doi:10.1039/c6ce00471g

Cited by 3 publications

(4 citation statements)

References 33 publications

(68 reference statements)

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“…Our findings are in agreement with the results of Nikiel et al . 26 and Rath et al . 27 , who have shown the formation of holes under Au particles formed by dewetting of thin Au films on Ge(100).…”

Section: Dissolution Anisotropymentioning

confidence: 93%

Surface-dependent scenarios for dissolution-driven motion of growing droplets

Curiotto

Leroy

Cheynis

et al. 2017

Sci Rep

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Nano-droplets on a foreign substrate have received increasing attention because of their technological possible applications, for instance to catalyse the growth of nanowires. In some cases the droplets can move as a result of a reaction with the substrate. In this work we show that the substrate orientation, the surface morphology and the shape of the pits etched in the substrate by the droplets affect the droplet motion, so that a single mechanism (droplet-induced substrate dissolution) may lead to several unexpected droplet dynamics. The experiments are carried out by low energy electron microscopy on Au-Si and Au-Ge, which are model systems for studying liquid droplet alloys. Studying in-situ the behaviour of Au droplets on various Si and Ge surfaces, we describe a subtle interplay between the substrate orientation, the surface defects, and the droplet motion. Our observations allow a deep understanding of the interfacial mechanisms at the origin of the alloy formation and the associated droplet motion. These mechanisms are based on events of substrate dissolution/recrystallization. The outcomes of this work highlight the importance of the etching anisotropy on the droplet-substrate behaviours, and are essential in the perspective of positioning liquid alloy droplets used for instance as nanowire catalysts.

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Section: Dissolution Anisotropymentioning

confidence: 93%

Surface-dependent scenarios for dissolution-driven motion of growing droplets

Curiotto

Leroy

Cheynis

et al. 2017

Sci Rep

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“…When the post-annealing temperature exceeds T e , the islands reshape into an asymmetric polyhedral (see Supplementary Fig. S1 ), indicating the formation of a AuGe eutectic liquid during the high-temperature stage of the treatment 19 . The longest edge of the island is aligned along the Ge <110> direction (as observed in Fig.…”

mentioning

confidence: 99%

“…It is separated into 4 steps. At the beginning of the annealing process, the deposited Au atoms aggregate into clusters due to surface diffusion of Au atoms on an Au rich surface and particle coarsening 19 . When the temperature exceeds the eutectic temperature of the system, a liquid Au-Ge droplet is formed by incorporation of Ge atoms from the substrate into the hot Au clusters, as described previously in nanowires 12 .…”

mentioning

confidence: 99%

Controlled growth of hexagonal gold nanostructures during thermally induced self-assembling on Ge(001) surface

Jany

Gauquelin

Willhammar

et al. 2017

Sci Rep

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Nano-sized gold has become an important material in various fields of science and technology, where control over the size and crystallography is desired to tailor the functionality. Gold crystallizes in the face-centered cubic (fcc) phase, and its hexagonal closed packed (hcp) structure is a very unusual and rare phase. Stable Au hcp phase has been reported to form in nanoparticles at the tips of some Ge nanowires. It has also recently been synthesized in the form of thin graphene-supported sheets which are unstable under electron beam irradiation. Here, we show that stable hcp Au 3D nanostructures with well-defined crystallographic orientation and size can be systematically created in a process of thermally induced self-assembly of thin Au layer on Ge(001) monocrystal. The Au hcp crystallite is present in each Au nanostructure and has been characterized by different electron microscopy techniques. We report that a careful heat treatment above the eutectic melting temperature and a controlled cooling is required to form the hcp phase of Au on a Ge single crystal. This new method gives scientific prospects to obtain stable Au hcp phase for future applications in a rather simple manner as well as redefine the phase diagram of Gold with Germanium.

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“…On the basis of the studied examples of AuIn 2 nanowires on InSb surface and Au hcp nanostructures on germanium surface , (see Supporting Information), we have shown that by careful optimization of SEM EDX SI collection at the nanoscale and by using the non-negative matrix factorization based blind source separation techniques on the collected SI we can successfully extract the nanostructures pure X-ray signal from other X-ray signal present in the data like bulk matrix, carbon background, or secondary fluorescence. The extracted X-ray signal originating from nanostructures is used to determine the true chemical composition of the formed nanostructures by the EDX ZAF method, the quantification is verified by detailed Monte Carlo simulations.…”

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confidence: 99%

Retrieving the Quantitative Chemical Information at Nanoscale from Scanning Electron Microscope Energy Dispersive X-ray Measurements by Machine Learning

Jany

Janas

2017

Nano Lett.

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The quantitative composition of metal alloy nanowires on InSb semiconductor surface and gold nanostructures on germanium surface is determined by blind source separation (BSS) machine learning method using non-negative matrix factorization from energy dispersive X-ray spectroscopy (EDX) spectrum image maps measured in a scanning electron microscope (SEM). The BSS method blindly decomposes the collected EDX spectrum image into three source components, which correspond directly to the X-ray signals coming from the supported metal nanostructures, bulk semiconductor signal, and carbon background. The recovered quantitative composition is validated by detailed Monte Carlo simulations and is confirmed by separate cross-sectional transmission electron microscopy EDX measurements of the nanostructures. This shows that simple and achievable SEM EDX measurements together with machine learning non-negative matrix factorization-based blind source separation processing could be successfully used for the nanostructures quantitative chemical composition determination. Our finding can make the chemical quantification at the nanoscale much faster and cost efficient for many systems.

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Dynamics of thermally induced assembly of Au nanoislands from a thin Au layer on Ge(001)

Cited by 3 publications

References 33 publications

Surface-dependent scenarios for dissolution-driven motion of growing droplets

Surface-dependent scenarios for dissolution-driven motion of growing droplets

Controlled growth of hexagonal gold nanostructures during thermally induced self-assembling on Ge(001) surface

Retrieving the Quantitative Chemical Information at Nanoscale from Scanning Electron Microscope Energy Dispersive X-ray Measurements by Machine Learning

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