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Recent progress towards universal machine-learned interatomic potentials holds considerable promise for materials discovery. Yet the accuracy of these potentials for predicting phase stability may still be limited. In contrast, cluster…

Materials Science · Physics 2024-05-03 A. Dana , L. Mu , S. Gelin , S. B. Sinnott , I. Dabo

Electron backscatter diffraction is a widely used technique for nano- to micro-scale analysis of crystal structure and orientation. Backscatter patterns produced by an alloy solid solution matrix and its ordered superlattice exhibit only…

Materials Science · Physics 2020-10-13 Thomas P McAuliffe , David Dye , T Ben Britton

Phase-change materials (PCMs)-based integrated photonic memory offers a viable pathway for the development of neuromorphic computing chip. The sizable optical contrast in the telecom band between amorphous and crystalline phases of PCM, in…

Materials Science · Physics 2026-03-12 Xueyang Shen , Ruixuan Chu , Ding Xu , Yuan Gao , Wen Zhou , Wei Zhang

Materials property predictions have improved from advances in machine learning algorithms, delivering materials discoveries and novel insights through data-driven models of structure-property relationships. Nearly all available models rely…

Materials Science · Physics 2022-04-13 Yiqun Wang , Xiao-Jie Zhang , Fei Xia , Elsa A. Olivetti , Ram Seshadri , James M. Rondinelli

In order to identify clusters of objects with features transformed by unknown affine transformations, we develop a Bayesian cluster process which is invariant with respect to certain linear transformations of the feature space and able to…

Methodology · Statistics 2016-12-01 Hsin-Hsiung Huang , Jie Yang

We present molecular dynamics (MD) simulations results for dense fluids of ultrasoft, fully-penetrable particles. These are a binary mixture and a polydisperse system of particles interacting via the generalized exponential model, which is…

Soft Condensed Matter · Physics 2012-12-24 Daniele Coslovich , Marco Bernabei , Angel J. Moreno

Accurate grain orientation mapping is essential for understanding and optimizing the performance of polycrystalline materials, particularly in energy-related applications. Lithium nickel oxide (LiNiO$_{2}$) is a promising cathode material…

Disordered Systems and Neural Networks · Physics 2025-11-26 Sebastian Wissel , Jonas Scheunert , Aaron Dextre , Shamail Ahmed , Andreas Bayer , Kerstin Volz , Bai-Xiang Xu

Advancements in fast electron detectors have enabled the statistically significant sampling of crystal structures on the nanometre scale by means of Scanning Electron Nanobeam Diffraction (SEND). Characterisation of structural similarity…

Materials Science · Physics 2022-07-28 Andy Bridger , William I. F. David , Thomas J. Wood , Mohsen Danaie , Keith T. Butler

Phase-change materials based on Ge-Sb-Te alloys are widely used in industrial applications such as nonvolatile memories, but reaction pathways for crystalline-to-amorphous phase-change on picosecond timescales remain unknown. Femtosecond…

We applied the clustering technique using DTW (dynamic time wrapping) analysis to XRD (X-ray diffraction) spectrum patterns in order to identify the microscopic structures of substituents introduced in the main phase of magnetic alloys. The…

Chalcogenide phase-change materials (PCMs) are one of the most mature candidates for next-generation memory technology. Recently, CrGeTe3 (CrGT) emerged as a promising PCM due to its enhanced amorphous stability and fast crystallization for…

Materials Science · Physics 2024-11-12 Yihui Jiang , Suyang Sun , Hanyi Zhang , Xiaozhe Wang , Yibo Lei , Riccardo Mazzarello , Wei Zhang

Phase-change materials (PCMs) have emerged as key enablers of non-volatile, ultra-compact photonic switches for energy-efficient deep neural network (DNN) applications. In this work, we investigate the recently discovered…

Optics · Physics 2025-12-23 Arpan Sur , Sudipta Saha , Chih-Yu Lee , Ichiro Takeuchi

The robust and automated determination of crystal symmetry is of utmost importance in material characterization and analysis. Recent studies have shown that deep learning (DL) methods can effectively reveal the correlations between X-ray or…

Computational Physics · Physics 2020-05-27 Leslie Ching Ow Tiong , Jeongrae Kim , Sang Soo Han , Donghun Kim

Germanium antimony telluride has been the most used and studied phase-change material for electronic memory due to its suitable crystallization temperature, amorphous to crystalline resistance contrast, and stability of the amorphous phase.…

Materials Science · Physics 2020-01-23 Shalini Tripathi , Paul Kotula , Manish Singh , Chanchal Ghosh , Gokhan Bakan , Helena Silva , Barry Carter

The information content of crystalline materials becomes astronomical when collective electronic behavior and their fluctuations are taken into account. In the past decade, improvements in source brightness and detector technology at modern…

We present a new analysis method for atomic resolution four-dimensional scanning transmission electron microscopy (4D-STEM, in which a diffraction pattern is collected at each point of a raster scan of a focused electron beam across the…

Instrumentation and Detectors · Physics 2025-08-11 Yining Xie , Eoin Moynihan , Marin Alexe , Louis Piper , Ana Sanchez , Richard Beanland

High-throughput analysis of multidimensional transmission electron microscopy (TEM) datasets remains a significant challenge, limiting the broader impact on strategic materials research. Conventional workflows typically involve sequential,…

Materials Science · Physics 2025-07-16 Arda Genc , Ravit Silverstein

Chalcogenide optical phase change materials (PCMs) have garnered significant interest for their growing applications in programmable photonics, optical analog computing, active metasurfaces, and beyond. Limited endurance or cycling lifetime…

Chalcogenide alloys are materials of interest for optical recording and non-volatile memories. We perform ab-initio molecular dynamics simulations aiming at shading light onto the structure of amorphous Ge2Sb2Te5 (GST), the prototypical…

Materials Science · Physics 2009-11-13 S. Caravati , M. Bernasconi , T. D. Kuehne , M. Krack , M. Parrinello

This work presents a novel approach to improve phase identification in nanomechanical property maps of multiphase materials, such as those obtained by nanoindentation or atomic force microscopy (AFM). A major challenge in validating…

Materials Science · Physics 2026-03-03 David Mercier , Yasmine El Gharoussi