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Heterogeneous multiscale methods (HMM) combine molecular accuracy of particle-based simulations with the computational efficiency of continuum descriptions to model flow in soft matter liquids. In these schemes, molecular simulations…

Multiscale and inhomogeneous molecular systems are challenging topics in the field of molecular simulation. In particular, modeling biological systems in the context of multiscale simulations and exploring material properties are driving a…

Computational Physics · Physics 2017-12-06 Horacio V. Guzman , Christoph Junghans , Kurt Kremer , Torsten Stuehn

Developing physics-based models for molecular simulation requires fitting many unknown parameters to diverse experimental datasets. Traditionally, this process is piecemeal and difficult to reproduce, leading to a fragmented landscape of…

Biological Physics · Physics 2025-04-10 Ryan K. Krueger , Megan C. Engel , Ryan Hausen , Michael P. Brenner

The development of reliable and extensible molecular mechanics (MM) force fields -- fast, empirical models characterizing the potential energy surface of molecular systems -- is indispensable for biomolecular simulation and computer-aided…

This paper presents several strategies to tune the parameters of metaheuristic methods for (discrete) design optimization of reinforced concrete (RC) structures. A novel utility metric is proposed, based on the area under the average…

Neural and Evolutionary Computing · Computer Science 2021-10-13 Iván Negrin , Dirk Roose , Ernesto Chagoyén

The emergence and understanding of new design paradigms that exploit flow induced mechanical instabilities for propulsion or energy harvesting demands robust and accurate flow structure interaction numerical models. In this context, we…

Fluid Dynamics · Physics 2019-05-22 Caroline Bernier , Mattia Gazzola , Renaud Ronsse , Philippe Chatelain

Accurate prediction of energy and forces for 3D molecular systems is one of fundamental challenges at the core of AI for Science applications. Many powerful and data-efficient neural networks predict molecular energies and forces from…

Chemical Physics · Physics 2026-04-23 Ali Mollahosseini , Mohammed Haroon Dupty , Wee Sun Lee

Force fields developed with machine learning methods in tandem with quantum mechanics are beginning to find merit, given their (i) low cost, (ii) accuracy, and (iii) versatility. Recently, we proposed one such approach, wherein, the…

Materials Science · Physics 2016-11-01 Venkatesh Botu , Rohit Batra , James Chapman , Rampi Ramprasad

We consider Adaptively Restrained Langevin dynamics, in which the kinetic energy function vanishes for small velocities. Properly parameterized, this dynamics makes it possible to reduce the computational complexity of updating…

Statistical Mechanics · Physics 2017-03-28 Zofia Trstanova , Stephane Redon

At the Institute for Thermodynamics and Thermal Process Engineering (ITT) about 100 molecular models for pure substances have been developed so far. These models reproduce vapor pressure, saturated liquid density, and enthalpy of…

Computational Physics · Physics 2009-04-22 Bernhard Eckl , Martin Horsch , Jadran Vrabec , Hans Hasse

Molecular dynamics simulations at a constant electric potential are an essential tool to study electrochemical processes, providing microscopic information on the structural, thermodynamic, and dynamical properties. Despite the numerous…

This work introduces ParAMS -- a versatile Python package that aims to make parameterization workflows in computational chemistry and physics more accessible, transparent and reproducible. We demonstrate how ParAMS facilitates the parameter…

Chemical Physics · Physics 2021-05-18 Leonid Komissarov , Robert Rüger , Matti Hellström , Toon Verstraelen

We report the improvement of five argon force fields by scaling Lennard-Jones energy ($\epsilon$) and distance ($\sigma$) parameters to reproduce liquid-vapor phase diagram and surface tension simultaneously, with molecular dynamics.…

We study the problem of automatically computing the controllable region of a Linear Hybrid Automaton, with respect to a safety objective. We describe the techniques that are needed to effectively and efficiently implement a…

Logic in Computer Science · Computer Science 2011-06-08 Massimo Benerecetti , Marco Faella , Stefano Minopoli

The Martini 3 force field is a full re-parametrization of the Martini coarse-grained model for biomolecular simulations. Due to the improved interaction balance it allows for more accurate description of condensed phase systems. In the…

Parameter tuning for vehicle controllers remains a costly and time-intensive challenge in automotive development. Traditional approaches rely on extensive real-world testing, making the process inefficient. We propose a multi-fidelity…

Systems and Control · Electrical Eng. & Systems 2025-06-11 Yongpeng Zhao , Maik Pfefferkorn , Maximilian Templer , Rolf Findeisen

We propose a method to efficiently determine the optimal coarse-grained force field in mesoscopic stochastic simulations of Newtonian fluid and polymer melt systems modeled by dissipative particle dynamics (DPD) and energy conserving…

Computational Physics · Physics 2017-01-04 Huan Lei , Xiu Yang , Zhen Li , George Karniadakis

Thermoplastics injection molding allows the production of complex parts in large series. Industrial quality requirements are increasing. The injection molding process needs to be regulate in order to maintain a working point. There is…

Systems and Control · Computer Science 2017-07-07 Pierre Nagorny , Eric Pairel , Maurice Pillet

Metal-organic frameworks (MOFs) are an incredibly diverse group of highly porous hybrid materials, which are interesting for a wide range of possible applications. For a reliable description of many of their properties accurate…

Materials Science · Physics 2024-11-26 Sandro Wieser , Egbert Zojer

This paper develops and analyzes an accelerated proximal descent method for finding stationary points of nonconvex composite optimization problems. The objective function is of the form $f+h$ where $h$ is a proper closed convex function,…

Optimization and Control · Mathematics 2024-07-02 Weiwei Kong
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