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Modeling the interaction between proteins and ligands and accurately predicting their binding structures is a critical yet challenging task in drug discovery. Recent advancements in deep learning have shown promise in addressing this…

机器学习 · 计算机科学 2024-01-10 Qizhi Pei , Kaiyuan Gao , Lijun Wu , Jinhua Zhu , Yingce Xia , Shufang Xie , Tao Qin , Kun He , Tie-Yan Liu , Rui Yan

The constant interplay and information exchange between cells and their micro-environment are essential to their survival and ability to execute biological functions. To date, a few leading technologies such as traction force microscopy,…

The combination of deep learning and ab initio materials calculations is emerging as a trending frontier of materials science research, with deep-learning density functional theory (DFT) electronic structure being particularly promising. In…

We have developed and implemented a new quantum molecular dynamics approximation that allows fast and accurate simulations of dense plasmas from cold to hot conditions. The method is based on a carefully designed orbital-free implementation…

等离子体物理 · 物理学 2015-06-22 Travis Sjostrom , Jerome Daligault

Quantum mechanical methods like Density Functional Theory (DFT) are used with great success alongside efficient search algorithms for studying kinetics of reactive systems. However, DFT is prohibitively expensive for large scale…

计算物理 · 物理学 2022-09-02 Mathias Schreiner , Arghya Bhowmik , Tejs Vegge , Peter Bjørn Jørgensen , Ole Winther

The fundamental quantity governing the mechanical and thermodynamic properties of a crystalline solid is its electronic charge density. Yet, its direct use for the rapid prediction of materials properties remains challenging due to its high…

材料科学 · 物理学 2026-05-11 Kammampati Sai Kumar , Albert Linda , Shubham Kumar Maurya , Somnath Bhowmick

Uranium-based materials are valuable assets in the energy, medical, and military industries. However, understanding their sensitivity to hydrogen embrittlement is particularly challenging due to the toxicity of uranium and computationally…

材料科学 · 物理学 2023-10-24 A. Soshnikov , R. K. Lindsey , A. Kulkarni , N. Goldman

A new, open source, parallel, stand-alone software package (Fortnet) has been developed, which implements Behler-Parrinello neural networks. It covers the entire workflow from feature generation to the evaluation of generated potentials,…

Dynamical Mean-Field Theory (DMFT) has opened new perspectives for the investigation of strongly correlated electron systems and greatly improved our understanding of correlation effects in models and materials. In contrast to…

强关联电子 · 物理学 2020-07-16 Dieter Vollhardt

We introduce a practical hybrid approach that combines orbital-free density functional theory (DFT) with Kohn-Sham DFT for speeding up first-principles molecular dynamics simulations. Equilibrated ionic configurations are generated using…

In dislocation dynamics (DD) simulations, the most computationally intensive step is the evaluation of the elastic interaction forces among dislocation ensembles. Because the pair-wise interaction between dislocations is long-range, this…

计算物理 · 物理学 2018-05-09 C. Chen , S. Aubry , T. Oppelstrup , A. Arsenlis , E. Darve

A fundamental assumption of the dynamical density functional theory (DDFT) of colloidal systems is that a grand-canonical free energy functional may be employed to generate the thermodynamic driving forces. Using one-dimensional hard-rods…

软凝聚态物质 · 物理学 2013-06-04 Johannes Reinhardt , Joseph Michael Brader

In the past decade, classical dynamical density functional theory (DDFT) has been developed and widely applied to the Brownian dynamics of interacting colloidal particles. One of the possible derivation routes of DDFT from the microscopic…

软凝聚态物质 · 物理学 2014-01-28 Raphael Wittkowski , Hartmut Löwen , Helmut R. Brand

Density functional theory (DFT) has emerged as one of the most versatile and lucrative approaches in electronic structure calculations of many-electron systems in past four decades. Here we give an account of the development of a…

化学物理 · 物理学 2019-04-19 Abhisek Ghosal , Amlan K. Roy

A variational formulation for the calculation of interacting fermion systems based on the density-matrix functional theory is presented. Our formalism provides for a natural integration of explicit many-particle effects into standard…

强关联电子 · 物理学 2013-05-29 Peter E. Bloechl , Christian F. J. Walther , Thomas Pruschke

For classical many-body systems subject to Brownian dynamics we develop a superadiabatic dynamical density functional theory (DDFT) for the description of inhomogeneous fluids out-of-equilibrium. By explicitly incorporating the dynamics of…

软凝聚态物质 · 物理学 2022-12-20 S. M. Tschopp , J. M. Brader

Real-Time Time-Dependent Density Functional Theory (TDDFT) has become an attractive tool to model quantum dynamics on a first-principles Density Functional Theory level. In recent years, several developments and applications in this field…

计算物理 · 物理学 2020-08-21 Joscha Hekele , Peter Kratzer

Current system thermal-hydraulic codes have limited credibility in simulating real plant conditions, especially when the geometry and boundary conditions are extrapolated beyond the range of test facilities. This paper proposes a…

机器学习 · 计算机科学 2020-01-14 Han Bao , Nam Dinh , Linyu Lin , Robert Youngblood , Jeffrey Lane , Hongbin Zhang

As density functional theory conventionally assumes that the density of a chosen model system (e.g., the Kohn-Sham system) is the same as the exact one, one might expect that approximations to the exact density introduce supplementary…

化学物理 · 物理学 2009-02-17 A. Savin

The formalism of density functional theory (DFT) can be easily extended to the time dependent case (TDDFT). However, while in the static case the theory is well established and is expected to be, at least in principle, an exact approach for…

凝聚态物理 · 物理学 2007-05-23 Sandro Stringari