arXiv subjects

Benedykt R. Jany

Publications and source records attributed to Benedykt R. Jany.

15 recordsLinked to original sources

arXiv2026

The Emergence of Photonic Crystalline Order and Time-Series Dynamics in NaCl Droplet Deposition

Crystallization during droplet evaporation gives rise to complex, self-organized structures, yet the mechanisms underlying the emergence of ordered functional phases remain poorly understood. In this study, we present a comprehensive, multi-scale investigation into the crystallization dynamics of NaCl during droplet evaporation on a germanium (001) substrate, relevant for its IR applications. Through systematic microscopic characterization, we identify the formation of diverse microstructures, including 1D photonic crystal nanostructures formed within hybrid crystal-glass photonic system. To enable quantitative comparison across experimental conditions, we introduce the NaCl equivalent height as a unified metric to describe and classify the evolution of crystalline morphology. Our results reveal that diffusion anisotropy, rather than growth kinetics, primarily governs the maximal attainable structure size. Quantitative thin film interference analysis demonstrates the presence of discrete thickness layers in the film. Controlled evaporation experiments yield homogeneous crystallization patterns across the entire droplet area, facilitating the emergence of ordered photonic structures. Time-series dynamics analysis of height profiles uncovered the spatiotemporal evolution of the crystallization front, providing insights into the details of underlying physical mechanisms. Together, these results establish a robust experimental framework for understanding and predicting crystallization behavior in evaporating droplets, with potential applications in materials synthesis, photonics, and microscale pattern formation.

cond-mat.mtrl-sci↗

arXiv2026

Exploring Wetting and Optical Properties of CuAg Alloys via Surface Texture Morphology Analysis

Copper-silver (CuAg) alloys are increasingly explored for applications in high-performance electrical and electronic systems, owing to their unique combination of high electrical and thermal conductivity and enhanced mechanical strength. Nevertheless, a thorough understanding of how these alloys surface characteristics fundamentally influence properties remains largely underdeveloped. Here, we explored the complex interplay between surface texture morphology, layer composition, wetting, and optical properties of Cu, Ag, and CuAg thin films deposited on textured silicon substrates via magnetron sputtering. Employing data mining and machine learning techniques, we identified robust correlations between contact angle and surface fractal dimension across all layer types promoting Cassie-Baxter surface state formation. Our analysis revealed a significant connection between layer thickness and surface topography entropy deficit, suggesting a dynamic evolution of surface order/disorder during metal film growth. Furthermore, we observed that contact angle sensitivity to layer thickness implied a correlation with microstructure evolution. Through K-Means clustering, we successfully categorized the formed surface textures morphology. Finally, a Random Forest regression model was developed to accurately predict water contact angles (Mean Absolute Error around 5 deg) using only texture and optical parameters. The model, along with accompanying Python code, is publicly available. Our findings establish a pathway towards targeted surface texture morphology engineering for tailored material performance.

cond-mat.mtrl-sci↗

arXiv2025

Colorimetry and Tribology of Ultrapure Copper Surface Micromodification

Controlling optical and tribological properties of metal surfaces, like color and wear rate, without altering their chemical composition is a highly desirable process across numerous fields of science and industry. It represents a cost-effective alternative to traditional chemical methods, particularly for copper, one of the most important metals widely used where high electrical and thermal conductivity, alongside resistance to corrosion, are required. We investigated the control of copper surface texture through a controlled micromodification process, utilizing constant force and velocity with abrasive silicon carbide sandpaper on ultrapure copper pellets exhibiting elongated crystallographic grains, and its impact on optical properties. Systematically varying grit size and rubbing direction, both along and across the grains, resulted in tunable microgroove morphology, demonstrating a marked difference in wear rate between single-grain and multi-grain abrasion. Furthermore, modification along copper grain boundaries yielded a change in the wear rate by a factor of two, related to single-grain and multi-grain abrasion regime changes, enabling precise control over material performance via tuned abrasion conditions. Colorimetric analysis via C-Microscopy revealed a strong, statistically significant relationship between abrasive parameters, microgroove geometry (inclination angle, depth, and size), and optical spectral signatures, which were then parametrized to achieve targeted control. This research demonstrates a simple yet effective approach to color and reflectance modification via microgroove engineering, offering a pathway to customized material properties by uniquely coupling contact mechanics, surface morphology, and colorimetry at the microscale level.

cond-mat.mtrl-sci↗

arXiv2025

Evaluating Metal-Organic Precursors for Focused Ion Beam Induced Deposition through Solid-Layer Decomposition Analysis

The development of modern metal deposition techniques like Focused Ion/Electron Beam Induced Deposition FIBID/FEBID relies heavily on the availability of metal-organic precursors of particular properties. To create a new precursor, extensive testing under specialized gas injection systems is required along with time-consuming and costly chemical analysis typically conducted using scanning electron microscopes. This process can be quite challenging due to its complexity and expense. Here, the response of new metal-organic precursors, in the form of supported thick layers, to the ion beam irradiation is studied through analysis of the chemical composition and morphology of the resulting structures. This is done using SEM BSE/EDX along with Machine Learning data processing techniques. This approach enables a comprehensive fast examination of precursor decomposition processes during FIB irradiation, and provides valuable insights into how the precursor's composition influences the final properties of the metal-rich deposits. Although solid-layer irradiation differs from gas-phase deposition, we think that our method, can be employed to optimize pre-screen and score new potential precursors for FIB applications by significantly reducing the time required and conserving valuable resources.

cond-mat.mes-hall↗

arXiv2024

EBSD and TKD analyses using inverted contrast Kikuchi diffraction patterns and alternative measurement geometries

Electron backscatter diffraction (EBSD) patterns can exhibit Kikuchi bands with inverted contrast due to anomalous absorption. This can be observed, for example, on samples with nanoscale topography, in case of a low tilt backscattering geometry, or for transmission Kikuchi diffraction (TKD) on thicker samples. Three examples are discussed where contrast-inverted physics-based simulated master patterns have been applied to find the correct crystal orientation. As the first EBSD example, self-assembled gold nanostructures made of Au fcc and Au hcp phases on single-crystal germanium were investigated. Gold covered about 12% of the mapped area, with only two-thirds being successfully interpreted using standard Hough-based indexing. The remaining third was solved by brute force indexing using a contrast-inverted master pattern. The second EBSD example deals with maps collected at a non-tilted surface instead of the commonly used 70 degree tilted one. As TKD example, a jet-polished foil made of duplex stainless steel 2205 was examined. The thin part close to the hole edge producing normal-contrast patterns were standard indexed. The areas of the foil that become thicker with increasing distance from the edge of the hole produce contrast-inverted patterns. They covered three times the evaluable area and were successfully processed using the contrast-inverted master pattern. In the last example, inverted patterns collected at a non-tiled sample were mathematically inverted to normal contrast, and Hough/Radon-based indexing was successfully applied.

cond-mat.mtrl-sci↗

arXiv2023

Quantifying colors at micrometer scale by colorimetric microscopy (C-Microscopy) approach

The color is the primal property of the objects around us and is direct manifestation of light-matter interactions. The color information is used in many different fields of science, technology and industry to investigate material properties or for identification of concentrations of substances. Usually the color information is used as a global parameter in a macro scale. To quantitatively measure color information in micro scale one needs to use dedicated microscope spectrophotometers or specialized micro-reflectance setups. Here, the Colorimetric Microscopy (C-Microscopy) approach based on digital optical microscopy and a free software is presented. The C-Microscopy approach uses color calibrated image and colorimetric calculations to obtain physically meaningful quantities i.e., dominant wavelength and excitation purity maps at micro level scale. This allows for the discovery of the local color details of samples surfaces. Later, to fully characterize the optical properties, the hyperspectral reflectance data at micro scale (reflectance as a function of wavelength for a each point) are colorimetrically recovered. The C-Microscopy approach was successfully applied to various types of samples i.e., two metamorphic rocks unakite and lapis lazuli, which are mixtures of different minerals; and to the surface of gold 99.999 % pellet, which exhibits different types of surface features. The C-Microscopy approach could be used to quantify the local optical properties changes of various materials at microscale in an accessible way. The approach is freely available as a set of python jupyter notebooks.

physics.ins-det↗

arXiv2023

Density functional theory study of experimentally observed Au/Ge interfaces

In recent years, nanostructures with hexagonal polytypes of gold have been synthesised, opening new possibilities in nanoscience and technology. As bulk gold crystallizes in the \textit{fcc} phase, surface effects can play an important role in stabilizing hexagonal gold nanostructures. Here we investigate several hetero-structures with Ge substrate, including the \textit{fcc} and \textit{hcp} phases of gold that have been observed experimentally. We determine and discuss their interfacial energies and optimized atomic arrangements, comparing the theory results with available experimental data. Our calculations for the Au-\textit{fcc}(011)/Ge(001) show how the presence of defects in the interface layer can help to stabilize the atomic pattern consistent with microscopic images. The Au-\textit{hcp}/Ge interface with the significant mismatch between two surfaces reveals large atomic displacements, which might indicate that the (111) germanium substrate is not responsible for the formation of the \textit{hcp} phase of gold. Finally, analyzing the electronic properties, we demonstrate that Au/Ge systems have metallic character but covalent-like bonding states between interfacial Ge and Au atoms are also present.

cond-mat.mtrl-sci↗

arXiv2021

Into the Origin of Electrical Conductivity for the Metal-Semiconductor Junction at the Atomic Level

The metal-semiconductor (M-S) junction based devices are commonly used in all sorts of electronic devices. Their electrical properties are defined by the metallic phase properties with a respect to the semiconductor used. Here we make an in-depth survey on the origin of the M-S junction at the atomic scale by studying the properties of the AuIn2 nanoelectrodes formed on the InP(001) surface by the in situ electrical measurements in combination with a detailed investigation of atomically resolved structure supported by the first-principle calculations of its local electrical properties. We have found that a different crystallographic orientation of the same metallic phase with a respect to the semiconductor structure influences strongly the M-S junction rectifying properties by subtle change of the metal Fermi level and influencing the band edge moving at the interface. This ultimately changes conductivity regime between Ohmic and Schottky type. The effect of crystallographic orientation has to be taken into account in the engineering of the M-S junction-based electronic devices.

cond-mat.mtrl-sci↗

arXiv2021

Towards Understanding of Gold Interaction with AIII-BV Semiconductors at Atomic Level

AIII-BV semiconductors have been considered for decades to be a promising material in overcoming the limitations of silicon semiconductor devices. One of the important aspects within AIII-BV semiconductor technology are gold-semiconductor interactions on the nanoscale. We report on investigations into the basic chemical interactions of Au atoms with AIII-BV semiconductor crystals by an investigation of nanostructures formation in the process of thermally-induced Au self-assembly on various AIII-BV surfaces, and this by means of atomically resolved High Angle Annular Dark Field (HAADF) Scanning Transmission Electron Microscopy (STEM) measurements. We have found that the formation of nanostructures is a consequence of the surface diffusion and nucleation of adatoms produced by Au induced chemical reactions on AIII-BV semiconductor surfaces. Only for InSb crystal we have found that there is efficient diffusion of Au atoms into the bulk, which we experimentally studied by Machine Learning HAADF STEM image quantification and theoretically by Density Functional Theory (DFT) calculations with the inclusion of finite temperature effects. Furthermore, the effective number of Au atoms needed to release one AIII metal atom has been estimated. The experimental finding reveals a difference in the Au interactions with In- and Ga-based groups of AIII-BV semiconductors. Our comprehensive and systematic studies uncover details of the Au interactions with the AIII-BV surface at the atomic level with chemical sensitivity and shed new light on the fundamental Au/AIII-BV interactions at the atomic scale.

cond-mat.mes-hall↗

arXiv2020

Quantitative near-field characterization of Surface Plasmon Polaritons on nanofabricated transmission structure

The tailoring of plasmonic near-fields is central to the field of nanophotonics. The detailed knowledge of the field distribution is crucial for a design and fabrication of plasmonic sensors, detectors, photovoltaics, plasmon-based cicuits, nanomanipulators, electrooptic plasmonic modulators and atomic devices. We report on a fully quantitative comparison between near field observation and numerical calculations, considering the intensity distribution for TM and TE polarisations, necessary for the construction of devices in all these areas. We present the near field scanning microscopy (NSOM) results of Surface Plasmon Polaritons (SPPs), excited by linearly polarized illumination on a gold, nanofabricated transmission grating. The optimization process is performed for infrared light, for future applications in cold atoms trapping and plasmonic sensing. We show the in situ processes of build up and propagation of SPPs and confirm that the out of plane component is not coupled to the aperture-type NSOM probe.

physics.optics↗

arXiv2019

Automatic microscopic image analysis by moving window local Fourier Transform and Machine Learning

Analysis of microscope images is a tedious work which requires patience and time, usually done manually by the microscopist after data collection. Here we introduce an approach of automatic image analysis, which is based on locally applied Fourier Transform and Machine Learning methods. In this approach, a whole image is scanned by a local moving window with defined size and the 2D Fourier Transform is calculated for each window. Then, all the Local Fourier Transforms are fed into Machine Learning processing. Firstly, a number of components in the data is estimated from Principal Component Analysis (PCA) Scree Plot performed on the data. Secondly, the data are decomposed blindly by Non-Negative Matrix Factorization (NMF) into interpretable spatial maps (loadings) and corresponding Fourier Transforms (factors). The microscopic image is analyzed and the features on the image are automatically discovered, based on the local changes in Fourier Transform. The user selects only a size and movement of the scanning local window which defines the final analysis resolution. This automatic approach was successfully applied to analysis of various microscopic images with and without local periodicity i.e. atomically resolved High Angle Annular Dark Field (HAADF) Scanning Transmission Electron Microscopy (STEM) image of Au nanoisland of fcc and Au hcp phases, Scanning Tunneling Microscopy (STM) image of Au-induced reconstruction on Ge(001) surface, Scanning Electron Microscopy (SEM) image of metallic nanoclusters grown on GaSb surface, and Fluorescence microscopy image of HeLa cell line of cervical cancer. The proposed approach could be used to automatically analyze the local structure of microscopic images within a time of about a minute for a single image on a modern desktop/notebook computer and it is freely available as a Python analysis notebook and Python program for batch processing.

eess.IV↗

arXiv2019

Nanostructure phase and interface engineering via controlled Au self-assembly on GaAs(001) surface

We have investigated the temperature-dependent morphology and composition changes occurring during a controlled self-assembling of thin Au film on the Gallium arsenide (001) surface utilizing electron microscopy at nano and atomic levels. It has been found that the deposition of 2 ML of Au at a substrate temperature lower than 798 K leads to the formation of pure Au nanoislands. For the deposition at a substrate temperature of about 798 K the nanostructures of the stoichiometric AuGa phase were/had been grown. Gold deposition at higher substrate temperatures results in the formation of octagonal nanostructures composed of an AuGa2 alloy. We have proved that the temperature-controlled efficiency of Au-induced etching-like of the GaAs substrate follows in a layer-by-layer manner leading to the enrichment of the substrate surface in gallium. The excess Ga together with Au forms liquid droplets which, while cooling the sample to room temperature, crystallize therein developing crystalline nanostructures of atomically-sharp interfaces with the substrate. The minimal stable cluster of 3 atoms and the activation energy for the surface diffusion Ed=0.816+-0.038eV was determined. We show that by changing the temperature of the self-assembling process one can control the phase, interface and the size of the nanostructures formed.

cond-mat.mes-hall↗

arXiv2017

Retrieving the quantitative chemical information at nanoscale from SEM EDX measurements by Machine Learning

The quantitative composition of metal alloy nanowires on InSb(001) semiconductor surface and gold nanostructures on germanium surface is determined by blind source separation (BSS) machine learning (ML) method using non negative matrix factorization (NMF) 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 TEM EDX measurements of the nanostructures. This shows that SEM EDX measurements together with machine learning blind source separation processing could be successfully used for the nanostructures quantitative chemical composition determination.

cond-mat.mes-hall↗

arXiv2011

Leading Modes of the 3pi0 production in proton-proton collisions at incident proton momentum 3.35GeV/c

This work deals with the prompt pp-->pp3pi0 reaction where the 3pi0 do not origin from the decay of narrow resonances like η(547), ω(782), η'(958). The reaction was measured for the proton beam momentum of 3.35GeV/c with the WASA-at-COSY detector setup. The dynamics of the reaction is investigated by Dalitz and Nyborg plots studies. The reaction is described by the model assuming simultaneous excitation of two baryon resonances Δ(1232) and N*(1440) where resonances are identified by their unique decays topology on the missing mass of two protons MMpp dependent Dalitz and Nyborg plots. The ratio R=Γ(N*(1440)->Nππ)/Γ(N*(1440)->Δ(1232)π->Nππ)= 0.039 +- 0.011(stat.) +- 0.008(sys.) is measured for the first time in a direct way. It shows that the {N*(1440)->Δ(1232)π->Nππ} decay is a leading mode of 3pi0 production. It is also shown that the MMpp is very sensitive to the structure of the spectral line shape of the N*(1440) resonance as well as on the interaction between the Δ(1232) and N*(1440) resonances. The multipion spectroscopy - a precision tool to directly access the properties of baryon resonances is considered. The pp-->ppη(3pi0) reaction was also measured simultaneously. It is shown that the η production mechanism via N*(1535) is 43.4 +- 0.8(stat.) +- 2.0(sys.) of the total production, for the η momentum in the CM system q_η^CM=0.45-0.7GeV/c. First time momentum dependence of the η angular distribution is seen, the strongest effect is observed for the cos(θ_η^CM) distribution.

nucl-ex↗

arXiv2007

Physics of EtaPrime->Pi+Pi-Eta and EtaPrime->Pi+Pi-Pi0 decays

The article describes experimental status of EtaPrime->Pi+Pi-Eta and EtaPrime->Pi+Pi-Pi0 decays. A theoretical framework used for description of the decays mechanism is also reviewed. The possibilities for the measurements with WASA-at-COSY are mentioned.

nucl-ex↗