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Chemotaxis is the response of a particle to a gradient in the chemical composition of the environment. While it was originally observed for biological organisms, it is of great interest in the context of synthetic active particles such as…

Soft Condensed Matter · Physics 2017-05-02 Laurens Deprez , Pierre de Buyl

Frontal polymerization is a promising energy-saving method for rapid fabrication of polymer components with good mechanical properties. In these systems, a small energy input is sufficient to convert monomers, from a liquid or soft solid…

Soft Condensed Matter · Physics 2023-10-04 Xuanhe Li , Tal Cohen

Prediction and optimisation of a wheel loader's dynamic behaviour is a challenge due to tightly coupled, non-linear subsystems of different technical domains. Furthermore, a simulation regarding performance, efficiency, and operability…

Computational Engineering, Finance, and Science · Computer Science 2011-08-30 Reno Filla

Catalysis-driven synthetic molecular motors operate in a loose mechanochemical coupling regime, one in which a decomposition of a fuel molecule does not reliably produce a forward step. In that regime, stochastic backward steps can…

Statistical Mechanics · Physics 2026-01-16 Geyao Gu , Drew Alvarez , John Strahan , Alex Albaugh , Emanuele Penocchio , Todd R. Gingrich

It is shown that probabilistic treatment of quantum mechanics can be coordinated with causality of all physical processes. The physical interpretation of quantum-mechanical phenomena such as process of measurement and collapse of quantum…

Quantum Physics · Physics 2007-05-23 Slavnov D. A

The fabrication of synthetic self-propelled particles and the experimental investigations of their dynamics have stimulated interest in self-generated phoretic effects that propel nano- and micron-scale objects. Theoretical modeling of…

Soft Condensed Matter · Physics 2014-10-10 Pierre de Buyl , Raymond Kapral

The stochastic driving force exerted by a single molecular motor (e.g., a kinesin, or myosin) moving on a periodic molecular track (microtubule, actin filament, etc.) is discussed from a general viewpoint open to experimental test. An…

Statistical Mechanics · Physics 2009-10-31 Michael E. Fisher , Anatoly B. Kolomeisky

Biomolecular force fields have been traditionally derived based on a mixture of reference quantum chemistry data and experimental information obtained on small fragments. However, the possibility to run extensive molecular dynamics…

Computational Physics · Physics 2020-06-19 Thorben Fröhlking , Mattia Bernetti , Nicola Calonaci , Giovanni Bussi

The concept of molecular mechanics force field has been widely accepted nowadays for studying various processes in biomolecular systems. In this paper, we suggest a modification for the standard CHARMM force field that permits simulations…

Complex biochemical pathways or regulatory enzyme kinetics can be reduced to chains of elementary reactions, which can be described in terms of chemical kinetics. This discipline provides a set of tools for quantifying and understanding the…

Quantitative Methods · Quantitative Biology 2018-01-08 Elena Agliari , Adriano Barra , Giulio Landolfi , Sara Murciano , Sarah Perrone

Synthetic active colloidal systems are being studied extensively because of the diverse and often unusual phenomena these nonequilibrium systems manifest, and their potential applications in fields ranging from biology to material science.…

Soft Condensed Matter · Physics 2023-02-16 Jiang-Xing Chen , Jia-Qi Hu , Raymond Kapral

The dynamics of a spherical chemically-powered synthetic colloidal motor that operates by a self-diffusiophoretic mechanism and has a catalytic domain of arbitrary shape is studied using both continuum theory and particle-based simulations.…

Soft Condensed Matter · Physics 2019-12-17 Shang Yik Reigh , Mu-Jie Huang , Hartmut Löwen , Eric Lauga , Raymond Kapral

Machine learning techniques applied to chemical reactions has a long history. The present contribution discusses applications ranging from small molecule reaction dynamics to platforms for reaction planning. ML-based techniques can be of…

Chemical Physics · Physics 2021-01-12 M. Meuwly

Molecular Dynamics simulations are becoming a powerful tool for examining and predicting atomic and molecular processes in various environment. The present review shows how, in the fields of plasma physics, chemistry and interactions with…

Plasma Physics · Physics 2023-12-14 Pascal Brault

A stochastic model for the dynamics of enzymatic catalysis in explicit, effective solvents under physiological conditions is presented. Analytically-computed first passage time densities of a diffusing particle in a spherical shell with…

Biomolecules · Quantitative Biology 2015-06-04 Jeremy Schofield , Paul Inder , Raymond Kapral

The output of a motor is work, while the output of a clock is information. Here it is discussed how a molecular motor can produce both, work and information, depending on the load. If the ratio of the backward and forward stepping rates of…

Chemical Physics · Physics 2022-04-13 Henry Hess

We examine the stochastic dynamics of two enzymes that are mechanically coupled to each other, e.g., through an elastic substrate or a fluid medium. The enzymes undergo conformational changes during their catalytic cycle, which itself is…

Statistical Mechanics · Physics 2021-11-16 Jaime Agudo-Canalejo , Tunrayo Adeleke-Larodo , Pierre Illien , Ramin Golestanian

Dispersions of immiscible liquids, such as emulsions and polymer blends, are at the core of many industrial applications which makes the understanding of their properties (morphology, stability, etc.) of great interest. A wide range of…

Chemical Physics · Physics 2017-08-10 Anaïs Giustiniani , Wiebke Drenckhan , Christophe Poulard

Chemical affinities are responsible for driving active matter systems out of equilibrium. At the nano-scale, molecular machines interact with the surrounding environment and are subjected to external forces. The mechano-chemical coupling…

Soft Condensed Matter · Physics 2025-01-03 Michalis Chatzittofi , Jaime Agudo-Canalejo , Ramin Golestanian

Machine learning (ML) has emerged as a pervasive tool in science, engineering, and beyond. Its success has also led to several synergies with molecular dynamics (MD) simulations, which we use to identify and characterize the major…

Biomolecules · Quantitative Biology 2022-05-09 Christopher Kolloff , Simon Olsson