arXiv subjects

Yevgeny Rakita

Publications and source records attributed to Yevgeny Rakita.

10 recordsLinked to original sources

arXiv2025

Protocol for Clustering 4DSTEM Data for Phase Differentiation in Glasses

Phase-change materials (PCMs) such as Ge-Sb-Te alloys are widely used in non-volatile memory applications due to their rapid and reversible switching between amorphous and crystalline states. However, their functional properties are strongly governed by nanoscale variations in composition and structure, which are challenging to resolve using conventional techniques. Here, we apply unsupervised machine learning to 4-dimensional scanning transmission electron microscopy (4D-STEM) data to identify compositional and structural heterogeneity in Ge-Sb-Te. After preprocessing and dimensionality reduction with principal component analysis (PCA), cluster validation was performed with t-SNE and UMAP, followed by k-means clustering optimized through silhouette scoring. Four distinct clusters were identified which were mapped back to the diffraction data. Elemental intensity histograms revealed chemical signatures change across clusters, oxygen and germanium enrichment in Cluster 1, tellurium in Cluster 2, antimony in Cluster 3, and germanium again in Cluster 4. Furthermore, averaged diffraction patterns from these clusters confirmed structural variations. Together, these findings demonstrate that clustering analysis can provide a powerful framework for correlating local chemical and structural features in PCMs, offering deeper insights into their intrinsic heterogeneity.

cond-mat.mtrl-sci↗

arXiv2025

Prediction of EDS Maps from 4DSTEM Diffraction Patterns Using Convolutional Neural Networks

Understanding the relationship between atomic structure (order) and chemical composition (chemistry) is critical for advancing materials science, yet traditional spectroscopic techniques can be slow and damaging to sensitive samples. Four-dimensional scanning transmission electron microscopy (4D-STEM) captures detailed diffraction patterns across scanned regions, providing rich structural information, while energy dispersive X-ray spectroscopy (EDS) offers complementary chemical data. In this work, we develop a machine learning framework that predicts EDS spectra directly from 4D-STEM diffraction patterns, reducing beam exposure and acquisition time. A convolutional neural network (CNN) accurately infers elemental compositions, particularly for elements with strong diffraction contrast or higher concentrations, such as Oxygen and Tellurium. Both extrapolation and interpolation strategies demonstrate consistent performance, with improved predictions when additional structural context is available. Visual and cross-correlation analyses confirm the model's ability to capture global and local compositional trends. This approach establishes a data-driven pathway to non-destructive, high-throughput materials characterization.

cond-mat.mtrl-sci↗

arXiv2023

Stretched Non-negative Matrix Factorization

An algorithm is described and tested that carries out a non negative matrix factorization (NMF) ignoring any stretching of the signal along the axis of the independent variable. This extended NMF model is called StretchedNMF. Variability in a set of signals due to this stretching is then ignored in the decomposition. This can be used, for example, to study sets of powder diffraction data collected at different temperatures where the materials are undergoing thermal expansion. It gives a more meaningful decomposition in this case where the component signals resemble signals from chemical components in the sample. The StretchedNMF model introduces a new variable, the stretching factor, to describe any expansion of the signal. To solve StretchedNMF, we discretize it and employ Block Coordinate Descent framework algorithms. The initial experimental results indicate that StretchedNMF model outperforms the conventional NMF for sets of data with such an expansion. A further enhancement to StretchedNMF for the case of powder diffraction data from crystalline materials called Sparse-StretchedNMF, which makes use of the sparsity of the powder diffraction signals, allows correct extractions even for very small stretches where StretchedNMF struggles. As well as demonstrating the model performance on simulated PXRD patterns and atomic pair distribution functions (PDFs), it also proved successful when applied to real data taken from an in situ chemical reaction experiment.

cond-mat.mtrl-sci↗

arXiv2022

Mapping Structural Heterogeneity at the Nanoscale with Scanning Nano-structure Electron Microscopy (SNEM)

Here we explore the use of scanning electron diffraction coupled with electron atomic pair distribution function analysis (ePDF) to understand the local order as a function of position in a complex multicomponent system, a hot rolled, Ni-encapsulated, Zr$_{65}$Cu$_{17.5}$Ni$_{10}$Al$_{7.5}$ bulk metallic glass (BMG), with a spatial resolution of 3 nm. We show that it is possible to gain insight into the chemistry and chemical clustering/ordering tendency in different regions of the sample, including in the vicinity of nano-scale crystallites that are identified from virtual dark field images and in heavily deformed regions at the edge of the BMG. In addition to simpler analysis, unsupervised machine learning was used to extract partial PDFs from the material, modeled as a quasi-binary alloy, and map them in space. These maps allowed key insights not only into the local average composition, as validated by EELS, but also a unique insight into chemical short-range ordering tendencies in different regions of the sample during formation. The experiments are straightforward and rapid and, unlike spectroscopic measurements, don't require energy filters on the instrument. We spatially map different quantities of interest (QoI's), defined as scalars that can be computed directly from positions and widths of ePDF peaks or parameters refined from fits to the patterns. We developed a flexible and rapid data reduction and analysis software framework that allows experimenters to rapidly explore images of the sample on the basis of different QoI's. The power and flexibility of this approach are explored and described in detail. Because of the fact that we are getting spatially resolved images of the nanoscale structure obtained from ePDFs we call this approach scanning nano-structure electron microscopy (SNEM), and we believe that it will be powerful and useful extension of current 4D-STEM methods.

cond-mat.mtrl-sci↗

arXiv2020

The tetragonal phase of CH$_{3}$NH$_{3}$PbI$_{3}$ is strongly anharmonic

Halide perovskite (HP) semiconductors exhibit unique strong coupling between the electronic and structural dynamics. The high-temperature cubic phase of HPs is known to be entropically stabilized, with imaginary frequencies in the calculated phonon dispersion relation. Similar calculations, based on the static average crystal structure, predict a stable tetragonal phase with no imaginary modes. This work shows that in contrast to standard theory predictions, the room-temperature tetragonal phase of CH$_{3} $NH$_{3} $PbI$_{3}$ is strongly anharmonic. We use Raman polarization-orientation (PO) measurements and \textit{ab initio} molecular dynamics (AIMD) to investigate the origin and temperature evolution of the strong structural anharmonicity throughout the tetragonal phase. Raman PO measurements reveal a new spectral feature that resembles a soft mode. This mode shows an unusual continuous increase in damping with temperature which is indicative of an anharmonic potential surface. The analysis of AIMD trajectories identifies two major sources of anharmonicity: the orientational unlocking of the [CH$_{3} $NH$_{3}$]$^+$ ions and large amplitude octahedral tilting that continuously increases with temperature. Our work suggests that the standard phonon picture cannot describe the structural dynamics of tetragonal CH$_{3} $NH$_{3} $PbI$_{3}$.

cond-mat.mtrl-sci↗

arXiv2019

Halide perovskites under polarized light: Vibrational symmetry analysis using polarized Raman

In the last decade, hybrid organic-inorganic halide perovskites have emerged as a new type of semiconductor for photovoltaics and other optoelectronic applications. Unlike standard, tetrahedrally bonded semiconductors (e.g. Si and GaAs), the ionic thermal fluctuations in the halide perovskites (i.e. structural dynamics) are strongly coupled to the electronic dynamics. Therefore, it is crucial to obtain accurate and detailed knowledge about the nature of atomic motions within the crystal. This has proved to be challenging due to low thermal stability and the complex, temperature dependent structural phase sequence of the halide perovskites. Here, these challenges are overcome and a detailed analysis of the mode symmetries is provided in the low-temperature orthorhombic phase of methylammonium-lead iodide. Raman measurements using linearly- and circularly- polarized light at 1.16 eV excitation are combined with density functional perturbation theory (DFPT). By performing an iterative analysis of Raman polarization-orientation dependence and DFPT mode analysis, the crystal orientation is determined. Subsequently, accounting for birefringence effects detected using circularly polarized light excitation, the symmetries of all the observed Raman-active modes at 10 K are assigned.

cond-mat.mtrl-sci↗

arXiv2019

Type and Degree of Covalence: Empirical Derivation and Implications

The way atoms attach to each other defines the function(s), e.g., mechanical, optical, electronic, of a given material. The nature of the chemical bond is, therefore, one of the most fundamental issues in materials. Both ionic interactions, i.e., resulting from electrical charges associated with the atoms, and covalent ones, i.e., the sharing of electrons between nuclei of different atoms, are usually viewed as forces that attract between atoms to form a rigid structure. Although less common for solid materials, it was shown theoretically to be possible for covalent interactions at the chemically-active electronic shell (or valence-band maximum) of semiconductors to reverse their more common nature and become repulsive, i.e., act against bonding. Some semiconductors with such predicted anti-bonding valence-band maximum levels (such as halide perovskites) show experimentally some amazing (opto-) electronic properties. Predictions that anti-bonding character can allow tolerance for existing defects, at least in part, can explain the superior properties of such semiconductors. Although there are known experimental ways to estimate the degree of the covalent nature (e.g., electronegativity), this was not possible hitherto for the type, i.e., distinguishing whether a material exhibits bonding or anti-bonding covalent interactions. We have developed a simple way to reveal the complete nature (both type and degree) of chemical bonds, using experimental data. After confirming our development with classical models and theoretical predictions, with a set of ~40 different functional semi-conductors, we show how knowledge of the complete nature of covalent bonding is of critical importance for fundamental properties of semiconductors.

cond-mat.mtrl-sci↗

arXiv2018

Between Structure and Performance in Halide Perovskites for Photovoltaic Applications: the Role of Defects

My study is about Halide Perovskites (HaPs) and focuses the fundamental structural, chemical and dielectric properties of HaPs in reference to their PV-related properties. * I present my main research model: HaP single-crystals - their growth and characterization; * I start by exploring the bond nature of HaPs using Nanoindentation and Solid-State NMR techniques. * I explore the 'deformation potential' of the structure and show that its low and positive value in HaPs strongly suggests a pronounced 'defect tolerance'. * I explore the scattering mechanism of charges in the soft and highly polarizable system such as HaPs, and show that its low mobility (relative to other heteropolar systems) is fundamental and cannot be improved. I also show that a positive 'deformation potential' (so the valence band is 'anti-bonding', where a system should promote 'defect-tolerance') is something that is common to other highly polarizable systems, such as AgX, and Pb-chalcogenides. * I explore the chemistry of the system and show that HaPs can easily break to constituents, but also easily be made by the same constituents, suggesting a low activation energy for annealing process to take care even at RT. This RT annealing can promote 'self-healing' at ~second to ~minute time-scale, which we clearly observe. We find 'entropic-stabilization' to be very important in 'self-healing' processes of that kind. * I explore the importance of symmetry breaking in the HaP structure, which can induce a polar - and thus Ferroelectric - structure. We conclude that Ferroelectricity is not a fundamental property of HaPs, since it doesn't exist in MAPbBr3, but only in MAPbI3 - as proven unambiguously - and what is present in MAPbI3 is in doubt important for photovoltaics, when using them at RT or above. Due to compression, if you find a low-quality figure you want- please email me.

cond-mat.mtrl-sci↗

arXiv2017

Tetragonal CH3NH3PbI3 Is Ferroelectric

Halide perovskite (HaP) semiconductors are revolutionizing photovoltaic (PV) solar energy conversion by showing remarkable performance of solar cells made with esp. tetragonal methylammonium lead tri-iodide (MAPbI3). In particular, the low voltage loss of these cells implies a remarkably low recombination rate of photogenerated carriers. It was suggested that low recombination can be due to spatial separation of electrons and holes, a possibility if MAPbI3 is a semiconducting ferroelectric, which, however, requires clear experimental evidence. As a first step we show that, in operando, MAPbI3 (unlike MAPbBr3) is pyroelectric, which implies it can be ferroelectric. The next step, proving it is (not) ferroelectric, is challenging, because of the material s relatively high electrical conductance (a consequence of an optical band gap suitable for PV conversion!) and low stability under high applied bias voltage. This excludes normal measurements of a ferroelectric hysteresis loop to prove ferroelctricity s hallmark for switchable polarization. By adopting an approach suitable for electrically leaky materials as MAPbI3, we show here ferroelectric hysteresis from well-characterized single crystals at low temperature (still within the tetragonal phase, which is the room temperature stable phase). Using chemical etching, we also image polar domains, the structural fingerprint for ferroelectricity, periodically stacked along the polar axis of the crystal, which, as predicted by theory, scale with the overall crystal size. We also succeeded in detecting clear second-harmonic generation, direct evidence for the material s non-centrosymmetry. We note that the material s ferroelectric nature, can, but not obviously need to be important in a PV cell, operating around room temperature.

cond-mat.mtrl-sci↗

arXiv2015

Mechanical Properties of APbX3 (A=Cs or CH3NH3; X=I or Br) Perovskite Single Crystals

The remarkable optoelectronic, and especially photovoltaic performance of hybrid-organic-inorganic perovskite (HOIP) materials drives efforts to connect materials properties to this performance. From nano-indentation experiments on solution-grown single crystals we obtain elastic modulus and nano-hardness values of APbX3 (A = Cs, CH3NH3 and X = I, Br). The Youngs moduli are about 14, 19.5 and 16 GPa, for CH3NH3PbI3, CH3NH3PbBr3 and CsPbBr3, respectively, lending credence to theoretically calculated values. We discuss possible relevance of our results to suggested self-healing, ion diffusion and ease of manufacturing. Using our results, together with literature data on elastic moduli, we classified HOIPs amongst relevant materials groups, based on their elasto-mechanical properties.

cond-mat.mtrl-sci↗