English
Related papers

Related papers: A Gaussian Approximation Potential for Amorphous S…

200 papers

In this paper, we apply multi-task Gaussian Process (MT-GP) to show that the adsorption energy of small adsorbates on transition metal surfaces can be modeled to a high level of fidelity using data from multiple sources, taking advantage of…

Data Analysis, Statistics and Probability · Physics 2019-01-29 Huijie Tian , Srinivas Rangarajan

Density functional theory (DFT) underpins modern atomistic simulations of transition-metal surfaces. It can predict key properties linked to catalytic performance, such as adsorption energies and barrier heights, enabling new paradigms in…

Materials Science · Physics 2026-03-23 Benjamin X. Shi , Timothy C. Berkelbach

Silicon is a promising anode material for next-generation lithium-ion batteries due to its exceptionally high specific capacity (3600 mAh g$^{-1}$), significantly exceeding that of conventional graphite. However, its practical application…

Chemical Physics · Physics 2026-01-08 D Sugunan , Y Jiang , J Guo , H Wang , M Marinescu , G Offer

We show that a deep-learning neural network potential (DP) based on density functional theory (DFT) calculations can well describe Cu-Zr materials, an example of a binary alloy system that can coexist in several ordered intermetallics and…

Materials Science · Physics 2020-04-29 Christopher M. Andolina , Philip Williamson , Wissam A. Saidi

The electrified solid-liquid interface plays an essential role in many renewable energy-related applications, including hydrogen production and utilization. Limitations in computational modelling of the electrified solid-liquid interface…

Unraveling the atomistic and the electronic structure of solid-liquid interfaces is the key to the design of new materials for many important applications, from heterogeneous catalysis to battery technology. Density functional theory (DFT)…

Materials Science · Physics 2022-01-25 Marco Eckhoff , Jörg Behler

Graph neural networks (GNNs) have shown promise in learning the ground-state electronic properties of materials, subverting ab initio density functional theory (DFT) calculations when the underlying lattices can be represented as small…

The present work is essentially focused on the study of optical and structural properties of hydrogenated amorphous silicon thin films (a-Si:H) prepared by radio-frequency cathodic sputtering. We examine separately the influence of hydrogen…

Materials Science · Physics 2007-05-23 A. Barhdadi , M. Chafik El Idrissi

The prediction of atomistic fracture mechanisms in body-centred cubic (bcc) iron is essential for understanding its semi-brittle nature. Existing atomistic simulations of the crack-tip deformation mechanisms under mode-I loading based on…

Materials Science · Physics 2022-09-15 Lei Zhang , Gábor Csányi , Erik van der Giessen , Francesco Maresca

Physics simulation is paramount for modeling and utilizing 3D scenes in various real-world applications. However, integrating with state-of-the-art 3D scene rendering techniques such as Gaussian Splatting (GS) remains challenging. Existing…

Computer Vision and Pattern Recognition · Computer Science 2025-11-03 Piotr Borycki , Weronika Smolak , Joanna Waczyńska , Marcin Mazur , Sławomir Tadeja , Przemysław Spurek

We measure the adsorption height of hydrogen-intercalated quasi-free-standing monolayer graphene on the (0001) face of 6H silicon carbide by the normal incidence x-ray standing wave technique. A density functional calculation for the full…

Machine learning potentials (MLPs) have become an indispensable tool in large-scale atomistic simulations because of their ability to reproduce ab initio potential energy surfaces (PESs) very accurately at a fraction of computational cost.…

Computational Physics · Physics 2024-09-04 Tsz Wai Ko , Shyue Ping Ong

The heterogeneous integration of silicon with III-V materials provides a way to overcome silicon's limited optical properties toward a broad range of photonic applications. Hybrid modes are a promising way to make heterogeneous Si/III-V…

Recent advances have equipped 3D Gaussian Splatting with texture parameterizations to capture spatially varying attributes, improving the performance of both appearance modeling and downstream tasks. However, the added texture parameters…

Computer Vision and Pattern Recognition · Computer Science 2025-12-17 Meng Wei , Cheng Zhang , Jianmin Zheng , Hamid Rezatofighi , Jianfei Cai

Using a combination of quantum and classical computational approaches, we model the electronic structure in amorphous silicon in order gain understanding of the microscopic atomic configurations responsible for light induced degradation of…

Materials Science · Physics 2009-11-13 Lucas K. Wagner , Jeffrey C. Grossman

X-ray absorption spectroscopy yields direct access to the electronic and geometric structure of hybrid inorganic-organic interfaces formed upon adsorption of complex molecules at metal surfaces. The unambiguous interpretation of…

Chemical Physics · Physics 2017-06-19 Katharina Diller , Reinhard J. Maurer , Moritz Müller , Karsten Reuter

Kohn-Sham density functional theory (DFT) is nowadays widely used for electronic structure theory simulations, and the accuracy and efficiency of DFT rely on approximations of the exchange-correlation functional. By inclusion of the kinetic…

Materials Science · Physics 2023-06-01 Renxi Liu , Daye Zheng , Xinyuan Liang , Xinguo Ren , Mohan Chen , Wenfei Li

With advances in scientific computing and mathematical modeling, complex scientific phenomena such as galaxy formations and rocket propulsion can now be reliably simulated. Such simulations can however be very time-intensive, requiring…

Methodology · Statistics 2024-02-29 Yi Ji , Simon Mak , Derek Soeder , J-F Paquet , Steffen A. Bass

The theoretical investigation of gas adsorption, storage, separation, diffusion and related transport processes in porous materials relies on a detailed knowledge of the potential energy surface of molecules in a stationary environment. In…

Chemical Physics · Physics 2025-01-30 Johannes K. Krondorfer , Christian W. Binder , Andreas W. Hauser

Crystal structures can be predicted from first-principles using ab initio random structure searching AIRSS and density functional theory (DFT). AIRSS provides a method to sample the potential energy landscape and DFT provides a robust and…

Materials Science · Physics 2025-09-30 Lewis J. Conway , Chris J. Pickard