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Titanium is the base material for a number of technologically important alloys for energy conversion and structural applications. Atomic-scale studies of Ti-based metals employing first-principles methods, such as density functional theory,…

Materials Science · Physics 2020-01-08 Alberto Ferrari , Malte Schröder , Yury Lysogorskiy , Jutta Rogal , Matous Mrovec , Ralf Drautz

Silica polymorphs and zeolites are fundamental to a wide range of industrial applications owing to their diverse structural characteristics, thermodynamic and mechanical stability under varying conditions and due to their geological…

The behaviour of partially ionized hot compressed matter is critical to the study of planetary interiors as well as for nuclear fusion studies. A recent quantum study of carbon in the 10-70 Gbar range and at a temperature of 100 eV used…

Plasma Physics · Physics 2021-07-07 M. W. C. Dharma-wardana

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

Recently, TersoffCG, a coarse grain potential for graphene based on Tersoff potential, has been developed. In this work, we explore this potential, applying it to the case study of a single wall carbon nanotube. We performed a series of…

Mesoscale and Nanoscale Physics · Physics 2018-07-05 Andrea Pedrielli

We develop and compare four interatomic potentials for iron: a simple machine-learned embedded atom method (EAM) potential, a potential with machine-learned two- and three-body-dependent terms, a potential with machine-learned EAM and…

Niobium (Nb) and its alloys are extensively used in various technological applications owing to their favorable mechanical, thermal and irradiation properties. Accurately modeling Nb under irradiation is essential for predicting…

Materials Science · Physics 2025-02-06 Utkarsh Bhardwaj , Vinayak Mishra , Suman Mondal , Manoj Warrier

This study utilises linear-scaling density functional theory (DFT) and develops a new machine-learning potential for carbon and nitrogen (GAP-CN), based on the carbon potential (GAP20), to investigate the interaction between carbon…

Computational Physics · Physics 2025-01-22 Guangzhao Chen , Joseph C. A. Prentice , Jason M. Smith

Motivated by recent experimental work, we use first-principles density functional theory methods to conduct an extensive search for low enthalpy structures of C$_6$Ca under pressure. As well as a range of buckled structures, which are…

Superconductivity · Physics 2007-05-23 Gabor Csanyi , Chris J. Pickard , B. D. Simons , R. J. Needs

Using molecular dynamics simulations we study the thermodynamic behavior of a single-component covalent material described by the recently proposed Environment-Dependent Interatomic Potential (EDIP). The parameterization of EDIP for silicon…

Materials Science · Physics 2009-11-07 P. Keblinski , M. Z. Bazant , R. K. Dash , M. M. Treacy

Accurately modeling the structural reconstruction and thermodynamic behavior of van der Waals (vdW) heterostructures remains a significant challenge due to the limitations of conventional force fields in capturing their complex mechanical,…

Computational Physics · Physics 2026-02-26 Hekai Bu , Wenwu Jiang , Penghua Ying , Ting Liang , Zheyong Fan , Wengen Ouyang

Computational modeling is usually applied to aid experimental exploration of advanced materials to better understand the fundamental plasticity mechanisms during mechanical testing. In this work, we perform Molecular dynamics (MD)…

Machine learning interatomic potentials (MLIPs) with broad chemical flexibility are important for atomistic simulations of compositionally complex materials such as high-entropy alloys. Here, we study two state-of-the-art MLIP frameworks,…

Materials Science · Physics 2026-04-06 Fei Shuang , Penghua Ying , Kai Liu , Zixiong Wei , Fengxian Liu , Zheyong Fan , Minqiang Jiang , Poulumi Dey

The vastness of the space of possible multicomponent metal alloys is hoped to provide improved structural materials but also challenges traditional, low-throughput materials design efforts. Computational screening could narrow this search…

Metal-organic frameworks (MOFs) are nanoporous compounds composed of metal ions and organic linkers. MOFs play an important role in industrial applications such as gas separation, gas purification, and electrolytic catalysis. Important MOF…

Machine Learning · Computer Science 2020-11-02 Shehtab Zaman , Christopher Owen , Kenneth Chiu , Michael Lawler

Interatomic potentials have been widely used in atomistic simulations such as molecular dynamics. Recently, frameworks to construct accurate interatomic potentials that combine a systematic set of density functional theory (DFT)…

Materials Science · Physics 2015-09-09 Atsuto Seko , Akira Takahashi , Isao Tanaka

Ti-N material system have range of compounds with different stoichiometry like Ti2N, Ti3N2, Ti6N5, Ti4N3 alongwith Ti , TiN and solid solutions of N in Ti with a maximum of 23% solubility. In this work, we develop an interatomic potential…

Materials Science · Physics 2025-07-28 Pradeep Kumar Rana , Atharva Vyawahare , Rohit Batra , Satyesh Kumar Yadav

Probing the ideal limit of interfacial thermal conductance (ITC) in two-dimensional (2D) heterointerfaces is of paramount importance for assessing heat dissipation in 2D-based nanoelectronics. Using graphene/hexagonal boron nitride…

To enable accurate molecular dynamics simulations of iron-chromium alloys with surfaces, we develop, based on density-functional-theory (DFT) calculations, a new interatomic Fe-Cr potential in the Tersoff formalism. Contrary to previous…

The use of pressure to obtain new materials that can be recovered under ambient conditions is a central problem in high-pressure physics. Despite decades of research, this goal has only been achieved in the laboratory for a few notable…

Materials Science · Physics 2025-08-19 Reetam Paul , Jonathan C. Crowhurst , Stanimir A. Bonev
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