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Parallel Molecular Dynamics simulations are conducted for describing growth on surfaces with different kind of roughness: a perfect ordered crystalline flat graphite surface, a disordered rough graphite surface and flat surface with an…

Materials Science · Physics 2007-05-23 Pascal Brault , Guy Moebs

In recent years, researchers have increasingly sought batteries as an efficient and cost-effective solution for energy storage and supply, owing to their high energy density, low cost, and environmental resilience. However, the issue of…

Computational Physics · Physics 2025-03-04 Zirui Zhao , Junchao Xia , Si Wu , Xiaoke Wang , Guanping Xu , Yinghao Zhu , Jing Sun , Hai-Feng Li

The assembly of virus capsids from free coat proteins proceeds by a complicated cascade of association and dissociation steps, the great majority of which cannot be directly experimentally observed. This has made capsid assembly a rich…

Quantitative Methods · Quantitative Biology 2015-07-09 Lu Xie , Gregory R. Smith , Russell Schwartz

Simulating and predicting multiscale problems that couple multiple physics and dynamics across many orders of spatiotemporal scales is a great challenge that has not been investigated systematically by deep neural networks (DNNs). Herein,…

Computational Physics · Physics 2021-03-31 Chensen Lin , Zhen Li , Lu Lu , Shengze Cai , Martin Maxey , George Em Karniadakis

CdTe is the most commercially successful thin-film photovoltaic technology to date. The recent development of Se-alloyed CdSe$_{x}$Te$_{1-x}$ layers in CdTe solar cells has led to higher device efficiencies, due to a lowered bandgap…

Materials Science · Physics 2023-10-11 Alan R Bowman , Jacob J Leaver , Kyle Frohna , Samuel D Stranks , Giulia Tagliabue , Jon D Major

Generating molecular dynamics (MD) trajectories using deep generative models has attracted increasing attention, yet remains inherently challenging due to the limited availability of MD data and the complexities involved in modeling…

Machine Learning · Computer Science 2026-04-07 Aniketh Iyengar , Jiaqi Han , Pengwei Sun , Mingjian Jiang , Jianwen Xie , Stefano Ermon

Today the study of two-dimensional (2D) materials has become one of the key objectives of materials science. Unlike their three-dimensional counterparts, 2D materials can simultaneously demonstrate unique transport and mechanical properties…

Materials Science · Physics 2021-03-16 Arslan B. Mazitov , Artem R. Oganov

Light interacting with plant leaves undergoes reflection, transmission, scattering, and absorption, which together determine leaf optical properties. Changes in leaf architecture disrupt internal light scattering dynamics and consequently…

Biological Physics · Physics 2025-12-23 Da-Young Lee , Dong-Yeop Na

Machine learning interatomic potentials (MLPs) are a promising technique for atomic modeling. While high accuracy and small errors are widely reported for MLPs, an open concern is whether MLPs can accurately reproduce atomistic dynamics and…

Materials Science · Physics 2023-10-02 Yunsheng Liu , Xingfeng He , Yifei Mo

Molecules can form myriad crystalline polymorphs, each with distinct properties affecting their performance across diverse applications, from pharmaceuticals to functional materials and more. Predicting the thermodynamically most stable…

In solid-state physics/chemistry, a precise understanding of defect formation and its impact on the electronic properties of wide-bandgap insulators is a cornerstone of modern semiconductor technology. However, complexities arise in the…

Materials Science · Physics 2023-07-11 Harshan Reddy Gopidi , Lovelesh Vashist , Oleksandr I. Malyi

Point defects govern many important functional properties of two-dimensional (2D) materials. However, resolving the three-dimensional (3D) arrangement of these defects in multi-layer 2D materials remains a fundamental challenge, hindering…

Understanding the physics of structurally and chemically complex transition-metal oxide and polyanionic materials such as those used for battery electrodes is challenging, even at the level of pristine compounds. Yet these materials are…

Materials Science · Physics 2018-07-19 Khang Hoang , M D Johannes

Radiation-induced photocurrent in semiconductor devices can be simulated using complex physics-based models, which are accurate, but computationally expensive. This presents a challenge for implementing device characteristics in high-level…

Computational Physics · Physics 2020-08-31 Joshua Hanson , Pavel Bochev , Biliana Paskaleva

In contrast to extensively studied defects in traditional materials, we report here for the first time a systematic investigation of the formation mechanism of intrinsic defects in self-assembled peptide nanostructures. The Monte Carlo…

Soft Condensed Matter · Physics 2015-11-11 Li Deng , Yurong Zhao , Hai Xu , Yanting Wang

Additive manufacturing (AM) is an emerging digital manufacturing technology to produce complex and freeform objects through a layer-wise deposition. High deposition rate robotic AM (HDRRAM) processes, such as cold spray additive…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Subash Gautam , Alejandro Vargas-Uscategui , Peter King , Hans Lohr , Alireza Bab-Hadiashar , Ivan Cole , Ehsan Asadi

The complicated mesoscopic configurations of composite plate and shell structures requires a huge amount of computational overhead for directly simulating their mechanical problems. In this paper, a unified high-order multi-scale method,…

Numerical Analysis · Mathematics 2023-05-02 Ge Bu-Feng , Gao Ming-Yuan , Dong Hao

Point defects are a universal feature of crystalline materials. Their identification is often addressed by combining experimental measurements with theoretical models. The standard approach of simulating defects is, however, prone to…

Materials Science · Physics 2023-02-20 Irea Mosquera-Lois , Seán R. Kavanagh , Aron Walsh , David O. Scanlon

Irradiation of materials in nuclear test reactors and power plants is known to alter the properties of the material. The irradiation event happening at pico- or nanosecond time scales are affecting the evolution and properties of the…

Density functional theory is routinely applied to predict crystal structures. The most common exchange-correlation functionals used to this end are the Perdew-Burke-Ernzerhof (PBE) approximation and its variant PBEsol. We investigate the…

Materials Science · Physics 2022-05-18 Robert Hussein , Jonathan Schmidt , Tomás Barros , Miguel A. L. Marques , Silvana Botti
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