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Machine-learning force fields (MLFFs) have emerged as a promising solution for speeding up ab initio molecular dynamics (MD) simulations, where accurate force predictions are critical but often computationally expensive. In this work, we…

Simulations have acted as a cornerstone to understand MOF/polymer interface structure, however, no molecular-level simulation has yet been performed at the nanoparticle scale. In this work, a hybrid MARTINI/Force Matching (FM) force field…

Chemical Physics · Physics 2024-10-22 Cecilia M. S. Alvares , Rocio Semino

Nucleation plays a critical role in the birth of crystals and is associated with a vast array of phenomena such as protein crystallization and ice formation in clouds. Despite numerous experimental and theoretical studies, many aspects of…

Soft Condensed Matter · Physics 2021-08-18 Gabriele M. Coli , Robin van Damme , C. Patrick Royall , Marjolein Dijkstra

Machine learning force fields (MLFFs), which employ neural networks to map atomic structures to system energies, effectively combine the high accuracy of first-principles calculation with the computational efficiency of empirical force…

Machine Learning · Computer Science 2025-11-17 Guangyi Dong , Zhihui Wang

As the number of theoretically predicted materials continues to grow, it becomes increasingly important to assess not only their thermodynamic stability but also their kinetic viability under realistic synthesis conditions. In this study,…

Materials Science · Physics 2026-04-17 Max C. Gallant , David Mrdjenovich , Kristin A. Persson

A machine-learned interatomic potential (MLIP) for multilayer MoS2 was developed using the ultra-fast force field (UF3) framework. The UF3 MLIP reproduces key properties in strong agreement with DFT including lattice constants, interlayer…

Materials Science · Physics 2026-05-20 Emir Bilgili , Nicholas Taormina , Richard Hennig , Simon R. Phillpot , Youping Chen

We propose a novel representation of crystalline materials named orbital-field matrix (OFM) based on the distribution of valence shell electrons. We demonstrate that this new representation can be highly useful in mining material data. Our…

High-entropy alloys (HEAs) have attracted increasing attention due to their unique structural and functional properties. In the study of HEAs, thermodynamic properties and phase stability play a crucial role, making phase diagram…

Materials Science · Physics 2025-12-01 Siya Zhu , Doguhan Sariturk , Raymundo Arroyave

Metal-organic frameworks show both fundamental interest and great promise for applications in adsorption-based technologies, such as the separation and storage of gases. The flexibility and complexity of the molecular scaffold poses a…

We present a computational microscopy analysis (targeted molecular dynamics simulations) of the structure and performance of conductive metal organic framework (MOF) electrodes in supercapacitors with room temperature ionic liquids. The…

Materials Science · Physics 2020-02-24 Sheng Bi , Ming Chen , Runxi Wang , Jiamao Feng , Mircea Dinca , Alexei A. Kornyshev , Guang Feng

The chalcogenide perovskite material BaZrS$_{3}$ is of growing interest for emerging thin-film photovoltaics. Here we show how machine-learning-driven modelling can be used to describe the material's amorphous precursor as well as…

Materials Science · Physics 2025-06-03 Laura-Bianca Paşca , Yuanbin Liu , Andy S. Anker , Ludmilla Steier , Volker L. Deringer

Structurally disordered materials continue to pose fundamental questions, including that of how different disordered phases ("polyamorphs") can coexist and transform from one to another. As a widely studied case, amorphous silicon (a-Si)…

Metal-organic frameworks (MOFs) are excellent candidates for water harvesting due to their tunable pore environments, which can be precisely engineered to capture and release water in arid conditions. Integrating artificial intelligence…

Materials Science · Physics 2026-05-29 Reid A. Coyle , Shyam Chand Pal , Peter Walther , Saeun Park , Bin Feng , Zhiling Zheng

The development of supercapacitors is impeded by the unclear relationships between nanoporous electrode structures and electrochemical performance, primarily due to challenges in decoupling the complex interdependencies of various…

Materials Science · Physics 2025-01-17 Zhenxiang Wang , Taizheng Wu , Liang Zeng , Jiaxing Peng , Ding Yu , Ming Gao , Guang Feng

The research on multiferrocity and magnetoelectric coupling in metal-organic system is rare. Very few hybrid organic-inorganic frameworks (HOIF) exhibit direct magnetoelectric coupling (coupling between spins and dipoles) and also…

The controllable synthesis of iron oxides particles is a critical issue for materials science, energy storage, biomedical applications, environmental science, and earth science. However, synthesis of iron oxides with desired phase and size…

The accurate prediction of solid-solid structural phase transitions at finite temperature is a challenging task, since the dynamics is so slow that direct simulations of the phase transitions by first-principles (FP) methods are typically…

Materials Science · Physics 2021-05-25 Peitao Liu , Carla Verdi , Ferenc Karsai , Georg Kresse

We propose a mechanism for insulator-to-metal (IM) transitions driven by the mismatch of quantized formal polarization (QFP), a symmetry-protected bulk invariant. For a material with a low-symmetry insulating phase and a high-symmetry phase…

Materials Science · Physics 2026-04-03 Hongsheng Pang , Lixin He

Accurately identifying the synthesis conditions of metal-organic frameworks (MOFs) is essential for guiding experimental design, yet remains challenging because relevant information in the literature is often scattered, inconsistent, and…

Artificial Intelligence · Computer Science 2026-02-24 Zuhong Lin , Daoyuan Ren , Kai Ran , Jing Sun , Songlin Yu , Xuefeng Bai , Xiaotian Huang , Haiyang He , Pengxu Pan , Ying Fang , Zhanglin Li , Haipu Li , Jingjing Yao

Over the past decade, climate change has become an increasing problem with one of the major contributing factors being carbon dioxide (CO2) emissions; almost 51% of total US carbon emissions are from factories. Current materials used in CO2…

Machine Learning · Computer Science 2023-11-29 Neel Redkar