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Computational materials discovery relies on the generation of plausible crystal structures. The plausibility is typically judged through density functional theory methods which, while typically accurate at zero Kelvin, often favor…

Computational Engineering, Finance, and Science · Computer Science 2025-11-04 Thorben Prein , Willis O'Leary , Aikaterini Flessa Savvidou , Elchaïma Bourneix , Joonatan E. M. Laulainen

A systematic search for multicomponent crystal structures is carried out for five different ternary systems of nuclei in a polarizable background of electrons, representative of accreted neutron star crusts and some white dwarfs. Candidate…

High Energy Astrophysical Phenomena · Physics 2016-03-09 T. A. Engstrom , N. C. Yoder , V. H. Crespi

Conventional methods to calculate the thermodynamics of crystals evaluate the harmonic phonon spectra and therefore do not work in frequent and important situations where the crystal structure is unstable in the harmonic approximation, such…

Statistical Mechanics · Physics 2009-11-13 P. Souvatzis , O. Eriksson , M. I. Katsnelson , S. P. Rudin

Determining the stability of chemical compounds is essential for advancing material discovery. In this study, we introduce a novel deep neural network model designed to predict a crystal's formation energy, which identifies its stability…

Materials Science · Physics 2026-04-21 V. Torlao , E. A. Fajardo

We have performed first principles study for bismuth crystal structure at pressure from 0~14 GPa based on structure search and quasi-harmonic approximation. A new stable phase with Pbcm symmetry is predicted by structure search method. We…

Materials Science · Physics 2019-03-08 Ya-Fan Zhao , Shou-Rui Li , Xing-Yu Gao , Ming-Feng Tian , Hai-Feng Song

We introduce and test several novel approaches for periodicity detection in unevenly-spaced sparse datasets. Specifically, we examine five different kinds of periodicity metrics, which are based on non-parametric measures of serial…

Instrumentation and Methods for Astrophysics · Physics 2016-01-07 Shay Zucker

We develop a method combining machine learning (ML) and density functional theory (DFT) to predict low-energy polymorphs by introducing physics-guided descriptors based on structural distortion modes. We systematically generate crystal…

Materials Science · Physics 2022-09-07 Bastien F. Grosso , Nicola A. Spaldin , Aria Mansouri Tehrani

Over the past decade, a combination of crystal structure prediction techniques and experimental synthetic work has thoroughly explored the phase diagrams of binary hydrides under pressure. The fruitfulness of this dual approach is…

Superconductivity · Physics 2022-02-21 Katerina P. Hilleke , Eva Zurek

The polymeric phase of nitrogen connected by the lower (than three) order N-N bonds has been long sought after for the potential application as high energy density materials. Here we report a hitherto unknown polymeric N$_2$H phase…

Materials Science · Physics 2015-03-16 Ketao Yin , Yanchao Wang , Hanyu Liu , Feng Peng , Lijun Zhang

High-throughput screening of large hypothetical databases of metal-organic frameworks (MOFs) can uncover new materials, but their stability in real-world applications is often unknown. We leverage community knowledge and machine learning…

This paper introduces a new structural phase field crystal (PFC) type model that expands the PFC methodology to a wider class of structurally complex crystal structures than previously possible. Specifically, our new approach allows for…

Materials Science · Physics 2016-02-03 Matthew Seymour , Nikolas Provatas

Nuclear Magnetic Resonance (NMR) spectroscopy is particularly well-suited to determine the structure of molecules and materials in powdered form. Structure determination usually proceeds by finding the best match between experimentally…

Nitrogen represents an archetypal example of material exhibiting a pressure driven transformation from molecular to polymeric state. Detailed investigations of such transformations are challenging because of a large kinetic barrier between…

Two novel three-dimensional (3D) crystal structures of carbon (C) and germanium carbide (GeC2) were predicted using first-principles density-functional theory (DFT) calculations. These newly discovered 3D carbon allotrope and GeC2 are in…

Materials Science · Physics 2020-12-15 Ying Yang , Guang Yang , Xihong Peng

Uranium nitrides have been the subject of intense research owing to their potential applications as advanced nuclear fuels. However, the phase diagram of the U-N system at low temperature and high pressure still remains unclear. In this…

Computational Physics · Physics 2018-04-03 Dawei Zhou , JiaHui Yu , Chunying Pu , Yuling Song

Amorphous materials offer unique functional characteristics, which are often not observed in their crystalline counterparts. This makes them invaluable for many technological applications, such as diffusion barriers in semiconductor…

Materials Science · Physics 2024-12-03 O. V. Pshyk , S. Zhuk , J. Patidar , A. Wieczorek , A. Sharma , J. Michler , C. Cancellieri , V. Stevanovic , S. Siol

All materials are made from atoms arranged either in repeating (crystalline) or in random (amorphous) structures. Diffraction measurements probe average distances between atoms and/or planes of atoms. A transmission electron microscope in…

Materials Science · Physics 2025-07-24 Andreas Werbrouck , Nikhila C. Paranamana , Xiaoqing He , Matthias J. Young

Binary carbides demonstrate attractive set of physical properties that are suitable for numerous and diverse applications. In the present study, we have explored the structural properties, electronic structures, elastic constants, acoustic…

Materials Science · Physics 2022-02-01 M. I. Naher , S. H. Naqib

Phonons, quantized vibrations of the atomic lattice, are fundamental to understanding thermal transport, structural stability, and phase behavior in crystalline solids. Despite advances in computational materials science, most predictions…

Materials Science · Physics 2026-01-15 Huiju Lee , Zhi Li , Jiangang he , Yi Xia

DFT is a widely used method to compute properties of materials, which are often collected in databases and serve as valuable starting points for further studies. In this article, we present the Materials Cloud Three-Dimensional Structure…