English
Related papers

Related papers: Comparison of permutationally invariant polynomial…

200 papers

We contribute to the vastly growing field of machine learning for engineering systems by demonstrating that equivariant graph neural networks have the potential to learn more accurate dynamic-interaction models than their non-equivariant…

Machine Learning · Computer Science 2023-04-04 Artur P. Toshev , Gianluca Galletti , Johannes Brandstetter , Stefan Adami , Nikolaus A. Adams

We explore by means of modeling how absorptive-dispersive mixing between the second- and third-order terms modify the imaginary chi(2)total responses from air/water interfaces under conditions of varying charge densities and ionic strength.…

Other Condensed Matter · Physics 2018-07-04 Paul Ohno , Hong-fei Wang , James Skinner , Francesco Paesani , Franz M. Geiger

Interatomic potentials approximate the potential energy of atoms as a function of their coordinates. Their main application is the effective simulation of many-atom systems. Here, we review empirical interatomic potentials designed to…

Materials Science · Physics 2022-11-11 Martin H. Muser , Sergey V. Sukhomlinov , Lars Pastewka

Aqueous lithium chloride solutions up to very high concentrations were investigated in classical molecular dynamics simulations. Various force fields based on the 12-6 Lennard-Jones model, parametrized for non-polarizable water solvent…

Soft Condensed Matter · Physics 2017-07-31 Ildikó Pethes

Constructing accurate, high dimensional molecular potential energy surfaces (PESs) for polyatomic molecules is challenging. Reproducing Kernel Hilbert space (RKHS) interpolation is an efficient way to construct such PESs. However, the…

Chemical Physics · Physics 2020-11-06 Debasish Koner , Markus Meuwly

We developed a multiscale approach (MultiSCAAL) that integrates the potential of mean force (PMF) obtained from all-atomistic molecular dynamics simulations with a knowledge-based energy function for coarse-grained molecular simulations in…

Biological Physics · Physics 2010-05-10 Antonios Samiotakis , Dirar Homouz , Margaret S. Cheung

The accurate modeling of non-covalent interactions between helium and graphitic materials is important for understanding quantum phenomena in reduced dimensions, with the helium-benzene complex serving as the fundamental prototype. However,…

Machine learning techniques including neural networks are popular tools for materials and chemical scientists with applications that may provide viable alternative methods in the analysis of structure and energetics of systems ranging from…

Statistical Mechanics · Physics 2022-03-02 James Andrews , Olga Gkountouna , Estela Blaisten-Barojas

The potential energy landscape (PEL) formalism is a tool within statistical mechanics that has been used in the past to calculate the equation of states (EOS) of classical rigid model liquids at low temperatures, where computer simulations…

Soft Condensed Matter · Physics 2024-01-18 Ali Eltareb , Gustavo E. Lopez , Nicolas Giovambattista

Water is a notoriously difficult substance to model both accurately and efficiently. Here, we focus on descriptions with a single coarse-grained particle per molecule using the so-called Approximate Non-Conformal (ANC) and generalized…

Soft Condensed Matter · Physics 2017-10-25 Tonalli Rodríguez-López , Yuriy Khalak , Mikko Karttunen

Molecular dynamics (MD) simulation, which is considered an important tool for studying physical and chemical processes at the atomic scale, requires accurate calculations of energies and forces. Although reliable energies and forces can be…

Materials Science · Physics 2021-12-06 Van-Quyen Nguyen , Viet-Cuong Nguyen , Tien-Cuong Nguyen , Tien-Lam Pham

Rational design of next-generation functional materials relied on quantitative predictions of their electronic structures beyond single building blocks. First-principles quantum mechanical (QM) modeling became infeasible as the size of a…

Materials Science · Physics 2024-11-05 Siqi Chen , Zhiqiang Wang , Xianqi Deng , Yili Shen , Cheng-Wei Ju , Jun Yi , Lin Xiong , Guo Ling , Dieaa Alhmoud , Hui Guan , Zhou Lin

Machine learning potentials (MLPs) are becoming powerful tools for performing accurate atomistic simulations and crystal structure optimizations. An approach to developing MLPs employs a systematic set of polynomial invariants including…

Computational Physics · Physics 2020-11-18 Atsuto Seko

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

Underwater explosion modeling faces a critical challenge of simultaneously resolving shock waves and gas-liquid interfaces, as traditional methods struggle to balance accuracy and computational efficiency. To address this, we develop a…

Fluid Dynamics · Physics 2025-08-12 Fulin Xing , Junjie Li , Ze Tao , Fujun Liu , Yong Tan

The conformational properties of linear alkanes, C$_n$H$_{2n+2}$, have been of intense interest for many years. Experiments and corresponding electronic structure calculations were first reported in the mid-2000s and continue to the present…

Chemical Physics · Physics 2025-09-24 Chen Qu , Thomas C. Allison , Apurba Nandi , Paul L. Houston , Qi Yu , Riccardo Conte , Joel M. Bowman

This paper presents results of numerical simulations of electron tunneling through water that extend our previous calculations on such systems in several ways. First, a tip-substrate configuration is used; second, calculations are carried…

Condensed Matter · Physics 2016-09-28 Michael Galperin , Abraham Nitzan , Ilan Benjamin

We report on an extensive study of the viscosity of liquid water at near-ambient conditions, performed within the Green-Kubo theory of linear response and equilibrium ab initio molecular dynamics (AIMD), based on density-functional theory…

Materials Science · Physics 2022-07-05 Cesare Malosso , Linfeng Zhang , Roberto Car , Stefano Baroni , Davide Tisi

This work constructs an advanced force field, the Completely Multipolar Model (CMM), to quantitatively reproduce each term of an energy decomposition analysis (EDA) for aqueous solvated alkali metal cations and halide anions and their ion…

Chemical Physics · Physics 2024-10-14 J. P. Heindel , L. Kim , M. Head-Gordon , T. Head-Gordon

The many-body expansion (MBE) of energies of molecular clusters or solids offers a way to detect and analyze errors of theoretical methods that could go unnoticed if only the total energy of the system was considered. In this regard, the…

Chemical Physics · Physics 2021-01-14 Marcin Modrzejewski , Sirous Yourdkhani , Szymon Śmiga , Jiří Klimeš