Deep learning generative model for crystal structure prediction by Xiaoshan Luo, Zhenyu Wang, Pengyue Gao, Jian Lv, Yanchao Wang, Changfeng Chen, Yanming Ma

“…Here, we present a universal GM for crystal structure prediction (CSP) via a conditional crystal diffusion variational autoencoder (Cond-CDVAE) approach, which is tailored to allow user-defined material and physical parameters such as composition and pressure. …”
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Shotgun crystal structure prediction using machine-learned formation energies by Liu Chang, Hiromasa Tamaki, Tomoyasu Yokoyama, Kensuke Wakasugi, Satoshi Yotsuhashi, Minoru Kusaba, Artem R. Oganov, Ryo Yoshida

“…Here, we present significant progress toward solving the crystal structure prediction problem: we performed noniterative, single-shot screening using a large library of virtually created crystal structures with a machine-learning energy predictor. …”
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One−Step Synthesis Strategy for a Platinum−Based Alloy Catalyst Designed via Crystal−Structure Prediction by Dengjie Yan, Lingxin Kong, Baoqiang Xu, Bin Yang

Subjects: “…crystal−structure prediction…”
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Rapid Assessment of Stable Crystal Structures in Single-Phase High-Entropy Alloys via Graph Neural Network-Based Surrogate Modelling by Nicholas Beaver, Aniruddha Dive, Marina Wong, Keita Shimanuki, Ananya Patil, Anthony Ferrell, Mohsen B. Kivy

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Prediction of novel tetravalent metal pentazolate salts with anharmonic effect by Jianan Yuan, Ding Chi, Beatriz H. Cogollo-Olivo, Yunlong Wang, Kang Xia, Jian Sun

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SCXRD, CSP-NMRX and microED in the quest for three elusive polymorphs of meloxicam by Agata Jeziorna, Maura Malinska, Isaac Sugden, Piotr Paluch, Rafał Dolot, Marta K. Dudek

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Rapid prediction of molecular crystal structures using simple topological and physical descriptors by Nikolaos Galanakis, Mark E. Tuckerman

“…To overcome this problem, we introduce a new topological approach to molecular crystal structure prediction. The approach posits that in a stable structure, molecules are oriented such that principal axes and normal ring plane vectors are aligned with specific crystallographic directions and that heavy atoms occupy positions that correspond to minima of a set of geometric order parameters. …”
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Crystal structure generation with autoregressive large language modeling by Luis M. Antunes, Keith T. Butler, Ricardo Grau-Crespo

“…However, most current methods for crystal structure prediction are computationally expensive, slowing the pace of innovation. …”
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Deep reinforcement learning for inverse inorganic materials design by Christopher Karpovich, Elton Pan, Elsa A. Olivetti

“…We apply template-based crystal structure prediction to suggest feasible crystal structure matches for target inorganic compositions identified by our machine learning (ML) algorithms to highlight the plausibility of the identified target compositions. …”
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Topological electride of t-YCl by Yiwei Liang, Xinyan Lin, Biao Wan, Zhaopeng Guo, Xuyan Cao, Dexi Shao, Jian Sun, Huiyang Gou

“…Based on the first-principles calculations and crystal-structure prediction techniques, we find a t-YCl phase with the space group of P4/nmm that is both thermodynamically and lattice dynamically stable, and also recoverable to the ambient condition. …”
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