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Electronic structure theory calculations offer an understanding of matter at the quantum level, complementing experimental studies in materials science and chemistry. One of the most widely used methods, density functional theory (DFT),…

Computational Physics · Physics 2024-04-11 Vincent Martinetto , Karan Shah , Attila Cangi , Aurora Pribram-Jones

Medium-entropy alloys (MEAs) such as CoCrFeNi and CoCrNi are promising structural materials owing to their outstanding mechanical and thermal properties, which arise from complex chemical disorder and atomic-scale interactions. Although…

Materials Science · Physics 2025-09-16 Mashroor S. Nitol , Artur Tamm , Subah Mubassira , Shuozhi Xu , Saryu J. Fensin

In the last decade, the use of Machine and Deep Learning (MDL) methods in Condensed Matter physics has seen a steep increase in the number of problems tackled and methods employed. A number of distinct MDL approaches have been employed in…

Computational Engineering, Finance, and Science · Computer Science 2023-03-08 Edoardo Di Napoli , Xinzhe Wu , Thomas Bornhake , Piotr M. Kowalski

Strongly correlated materials exhibit complex electronic phenomena that are challenging to capture with traditional theoretical methods, yet understanding these systems is crucial for discovering new quantum materials. Addressing the…

Strongly Correlated Electrons · Physics 2024-11-22 Egor Agapov , Oriol Bertomeu , Andrés Carballo , Christian B. Mendl , Aaron Sander

In this study, a machine learning-based technique is developed to reduce the computational cost required to explore large design spaces of substitutional alloys. The first advancement is based on a neural network approach to predict the…

Computational Physics · Physics 2020-04-03 Alhassan S. Yasin , Terence D. Musho

Using artificial neural-network machine learning (ANN-ML) to generate interatomic potentials has been demonstrated to be a promising approach to address the long-standing challenge of accuracy versus efficiency in molecular dynamics (MD)…

Materials Science · Physics 2022-08-16 Chao Zhang , Ling Tang , Yang Sun , Kai-Ming Ho , Renata M. Wentzcovitch , Cai-Zhuang Wang

Fluids with competing short range attraction and long range repulsive interactions between the particles can exhibit a variety of microphase separated structures. We develop a lattice-gas (generalised Ising) model and analyse the phase…

Soft Condensed Matter · Physics 2016-01-20 Blesson Chacko , Christopher Chalmers , Andrew J. Archer

The design of efficient electrolysis devices for pure metal production requires accurate data on the properties of the melts used in the process. This work focuses on two key systems for calcium production: the molten Ca-Cu alloy and the…

Materials Science · Physics 2026-03-27 M. Polovinkin , N. Rybin , D. Maksimov , F. Valiev , A. Khudorozhkova , M. Laptev , A. Rudenko , A. Shapeev

In computational materials science, a common means for predicting macroscopic (e.g., mechanical) properties of an alloy is to define a model using combinations of descriptors that depend on some material properties (elastic constants,…

Materials Science · Physics 2022-10-17 Ivan Novikov , Olga Kovalyova , Alexander Shapeev , Max Hodapp

Using ab-initio calculations within the framework of Density Functional Theory (DFT), atomic structures and electronic properties of MoS2/HfO2 interface are investigated. The impact of interfacial oxygen concentration on the MoS2/HfO2…

Materials Science · Physics 2014-02-10 Santosh KC , Roberto C. Longo , Robert M. Wallace , Kyeongjae Cho

Next generation batteries based on lithium (Li) metal anodes have been plagued by the dendritic electrodeposition of Li metal on the anode during cycling, resulting in short circuit and capacity loss. Suppression of dendritic growth through…

In this study, we present a sophisticated hybrid machine-learning framework that significantly improves the accuracy of predicting hydrogen storage capacities in metal hydrides. This is a critical challenge due to the scarcity of…

Materials Science · Physics 2024-08-29 Satadeep Bhattacharjee , Pritam Das , Swetarekha Ram , Seung-Cheol Lee

While first-principles calculations of electrode-molecule binding play an indispensable role in obtaining atomic-level understanding in surface science and electrochemistry, a significant challenge remains because the adsorption energy is…

Materials Science · Physics 2024-03-29 Juho Lee , Hyeonwoo Yeo , Ryong-Gyu Lee , Yong-Hoon Kim

We compute the thermal conductivity of water within linear response theory from equilibrium molecular dynamics simulations, by adopting two different approaches. In one, the potential energy surface (PES) is derived on the fly from the…

Materials Science · Physics 2021-12-24 Davide Tisi , Linfeng Zhang , Riccardo Bertossa , Han Wang , Roberto Car , Stefano Baroni

The electric double layer (EDL) governs electrocatalysis, energy conversion, and storage, yet its atomic structure, capacitance, and reactivity remain elusive. Here we introduce a machine learning interatomic potential framework that…

Chemical Physics · Physics 2025-09-18 Xiaoyu Wang , Junmin Chen , Zezhu Zeng , Frederick Stein , Junho Lim , Bingqing Cheng

Solid-state electrolytes are essential in the development of all-solid-state batteries. While density functional theory (DFT)-based nudged elastic band (NEB) and ab initio molecular dynamics (AIMD) methods provide fundamental insights on…

Materials Science · Physics 2025-07-04 Jingchen Lian , Xiao Fu , Xuhe Gong , Ruijuan Xiao , Hong Li

We review recent ab initio molecular dynamics studies of electrode/electrolyte interfaces in lithium ion batteries. Our goals are to introduce experimentalists to simulation techniques applicable to models which are arguably most faithful…

Materials Science · Physics 2013-04-23 Kevin Leung

One of the main applications of atomistic computer simulations is the calculation of ligand binding energies. The accuracy of these calculations depends on the force field quality and on the thoroughness of configuration sampling. Sampling…

Computational Physics · Physics 2021-01-11 Valerio Rizzi , Luigi Bonati , Narjes Ansari , Michele Parrinello

Layered LiMnO$_2$ and Li$_2$MnO$_3$ are of great interest for lithium-ion battery cathodes because of their high theoretical capacities. The practical application of these materials is, however, limited due to poor electrochemical…

Materials Science · Physics 2015-02-25 Khang Hoang

The surface charge of a water interface determines many fundamental processes in physical chemistry and interface science, and it has been intensively studied for over a hundred years. We summarize experimental methods to characterize the…

Chemical Physics · Physics 2021-09-23 Yuki Uematsu