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The current capacity of computers makes it possible to perform simulations of small systems with portable, explicit-solvent potentials achieving high degree of accuracy. However, simplified models must be employed to exploit the behaviour…

Biomolecules · Quantitative Biology 2015-06-18 R. Capelli , C. Paissoni , P. Sormanni , G. Tiana

A new approach for efficiently exploring the configuration space and computing the free energy of large atomic and molecular systems is proposed, motivated by an analogy with reinforcement learning. There are two major components in this…

Chemical Physics · Physics 2018-04-18 Linfeng Zhang , Han Wang , Weinan E

A new self-learning algorithm for accelerated dynamics, reconnaissance metadynamics, is proposed that is able to work with a very large number of collective coordinates. Acceleration of the dynamics is achieved by constructing a bias…

Computational Physics · Physics 2010-10-15 Gareth A. Tribello , Michele Ceriotti , Michele Parrinello

One-dimensional ideal diatomic gas is simulated through possible types of motion of a molecule. Energy of each type of its motion is calculated from theory and numerical method. Calculation of kinetic energy of an atom in…

Chemical Physics · Physics 2014-02-11 Siti Nurul Khotimah , Sparisoma Viridi , Widayani , Abdul Waris

We present a novel approach to investigate the long-time stochastic dynamics of multi-dimensional classical systems, in contact with a heat-bath. When the potential energy landscape is rugged, the kinetics displays a decoupling of short and…

Soft Condensed Matter · Physics 2013-05-29 O. Corradini , P. Faccioli , H. Orland

Simulations at the atomic scale provide a direct and effective way to understand the mechanical properties of materials. In the regime of classical mechanics, simulations for the thermodynamic properties of metals and alloys can be done by…

Computational Physics · Physics 2019-11-05 Ka-Ming Tam , Nicholas Walker , Samuel Kellar , Mark Jarrell

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

Adaptive precision molecular dynamics simulations have developed along energy- and force-coupling approaches, which allow for a continuous transition between different particle descriptions or interaction potentials. Most approaches…

Computational Physics · Physics 2025-12-09 David Immel , Ralf Drautz , Godehard Sutmann

This communication is both a pedagogical note for understanding polyatomic modelling in kinetic theory and a ''cheat sheet'' for a series of corresponding concepts and formulas. We explain, detail and relate three possible approaches for…

Analysis of PDEs · Mathematics 2025-01-31 Marzia Bisi , Thomas Borsoni , Maria Groppi

The increasing number of protein-based metamaterials demands reliable and efficient theoretical and computational methods to study the physicochemical properties they may display. In this regard, we develop a simulation strategy based on…

Soft Condensed Matter · Physics 2020-06-23 J. A. Campos Gonzalez Angulo , G. Wiesehan , R. F. Ribeiro , J. Yuen-Zhou

Atomistic simulations using accurate energy functions can provide molecular-level insight into functional motions of molecules in the gas- and in the condensed phase. Together with recently developed and currently pursued efforts in…

Chemical Physics · Physics 2022-01-12 M. Meuwly

We present a method to search low energy configurations of polar molecules in the complex potential energy surfaces associated with dense fluids. The search is done in the configurational space of the translational and rotational degrees of…

Chemical Physics · Physics 2016-09-08 Gianni De Fabritiis , Rafael Delgado-Buscalioni , Peter V. Coveney

We present a coupled atomistic-continuum method for the modeling of defects and interface dynamics of crystalline materials. The method uses atomistic models such as molecular dynamics near defects and interfaces, and continuum models away…

Materials Science · Physics 2009-11-07 Weinan E , Zhongyi Huang

Empirical force fields employed in molecular dynamics simulations of complex systems can be optimised to reproduce experimentally determined structural and thermodynamic properties. In contrast, experimental knowledge about the rates of…

Statistical Mechanics · Physics 2022-07-12 P. G. Bolhuis , Z. F. Brotzakis , B. G. Keller

Molecular dynamics simulations are an important tool for describing the evolution of a chemical system with time. However, these simulations are inherently held back either by the prohibitive cost of accurate electronic structure theory…

Chemical Physics · Physics 2018-12-20 Michael Gastegger , Philipp Marquetand

Active contour models based on local region fitting energy can segment images with intensity inhomogeneity effectively, but their segmentation results are easy to error if the initial contour is inappropriate. In this paper, we present a…

Computer Vision and Pattern Recognition · Computer Science 2018-03-20 Keyan Ding , Linfang Xiao

A machine learning technique is proposed for quantifying uncertainty in power system dynamics with spatiotemporally correlated stochastic forcing. We learn one-dimensional linear partial differential equations for the probability density…

Machine Learning · Computer Science 2023-12-19 Tyler E. Maltba , Vishwas Rao , Daniel Adrian Maldonado

While offering unprecedented resolution of atomic and electronic structure, Scanning Probe Microscopy techniques have found greater challenges in providing reliable electrostatic characterization at the same scale. In this work, we…

During a crossover via a switching mechanism from one 2-body potential to another as might be applied in modeling (chemical) reactions in the vicinity of bond formation, energy violations would occur due to finite step size which determines…

Computational Physics · Physics 2007-05-23 Christopher G Jesudason

The use of machine learning to estimate the energy of a group of atoms, and the forces that drive them to more stable configurations, has revolutionized the fields of computational chemistry and materials discovery. In this domain, rigorous…

Chemical Physics · Physics 2025-10-28 Filippo Bigi , Marcel Langer , Michele Ceriotti
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