scholarly journals Coarse Graining Nonisothermal Microswimmer Suspensions

2021 ◽  
Vol 9 ◽  
Author(s):  
Sven Auschra ◽  
Dipanjan Chakraborty ◽  
Gianmaria Falasco ◽  
Richard Pfaller ◽  
Klaus Kroy

We investigate coarse-grained models of suspended self-thermophoretic microswimmers. Upon heating, the Janus spheres, with hemispheres made of different materials, induce a heterogeneous local solvent temperature that causes the self-phoretic particle propulsion. Starting from molecular dynamics simulations that schematically resolve the molecular composition of the solvent and the microswimmer, we verify the coarse-grained description of the fluid in terms of a local molecular temperature field, and its role for the particle’s thermophoretic self-propulsion and hot Brownian motion. The latter is governed by effective nonequilibrium temperatures, which are measured from simulations by confining the particle position and orientation. They are theoretically shown to remain relevant for any further spatial coarse-graining towards a hydrodynamic description of the entire suspension as a homogeneous complex fluid.

Author(s):  
Łukasz Piotr Baran ◽  
Wojciech Rżysko ◽  
Dariusz Tarasewicz

In this study we have performed extensive coarse-grained molecular dynamics simulations of the self-assembly of tetra-substituted molecules. We have found that such molecules are able to form a variety of...


2015 ◽  
Vol 108 (2) ◽  
pp. 172a
Author(s):  
Valeria Marquez-Miranda ◽  
Iingrid Araya ◽  
Maria Belen Camarada ◽  
Lars Ratjen ◽  
Maria Carolina Otero ◽  
...  

Soft Matter ◽  
2021 ◽  
Author(s):  
Feng-Rui Xu ◽  
Rui Shi ◽  
XiangMeng Jia ◽  
Shengchao Chai ◽  
Haolong Li ◽  
...  

We use coarse-grained molecular dynamics simulations to study the self-assembly behavior of polyoxometalate (POM) nanoparticles (NPs) decorated with mobile polymer ligands in a melt condition. We demonstrate that due to...


2019 ◽  
Vol 5 (1) ◽  
Author(s):  
Wujie Wang ◽  
Rafael Gómez-Bombarelli

AbstractMolecular dynamics simulations provide theoretical insight into the microscopic behavior of condensed-phase materials and, as a predictive tool, enable computational design of new compounds. However, because of the large spatial and temporal scales of thermodynamic and kinetic phenomena in materials, atomistic simulations are often computationally infeasible. Coarse-graining methods allow larger systems to be simulated by reducing their dimensionality, propagating longer timesteps, and averaging out fast motions. Coarse-graining involves two coupled learning problems: defining the mapping from an all-atom representation to a reduced representation, and parameterizing a Hamiltonian over coarse-grained coordinates. We propose a generative modeling framework based on variational auto-encoders to unify the tasks of learning discrete coarse-grained variables, decoding back to atomistic detail, and parameterizing coarse-grained force fields. The framework is tested on a number of model systems including single molecules and bulk-phase periodic simulations.


Soft Matter ◽  
2018 ◽  
Vol 14 (24) ◽  
pp. 5019-5030 ◽  
Author(s):  
Eric J. Spangler ◽  
P. B. Sunil Kumar ◽  
Mohamed Laradji

The self-assembly of spherical nanoparticles, resulting from their adhesion on tensionless lipid membranes, is investigated through molecular dynamics simulations of a coarse-grained implicit-solvent model for self-assembled lipid membranes.


Soft Matter ◽  
2018 ◽  
Vol 14 (24) ◽  
pp. 5106-5120 ◽  
Author(s):  
Thiago Colla ◽  
Ronald Blaak ◽  
Christos N. Likos

Using molecular dynamics simulations, we investigate the self-assembly of a coarse-grained binary system of oppositely charged microgels, symmetric in size and concentration.


2020 ◽  
Author(s):  
Florencia Klein ◽  
Daniela Cáceres-Rojas ◽  
Monica Carrasco ◽  
Juan Carlos Tapia ◽  
Julio Caballero ◽  
...  

<p>Although molecular dynamics simulations allow for the study of interactions among virtually all biomolecular entities, metal ions still pose significant challenges to achieve an accurate structural and dynamical description of many biological assemblies. This is particularly the case for coarse-grained (CG) models. Although the reduced computational cost of CG methods often makes them the technique of choice for the study of large biomolecular systems, the parameterization of metal ions is still very crude or simply not available for the vast majority of CG- force fields. Here, we show that incorporating statistical data retrieved from the Protein Data Bank (PDB) to set specific Lennard-Jones interactions can produce structurally accurate CG molecular dynamics simulations. Using this simple approach, we provide a set of interaction parameters for Calcium, Magnesium, and Zinc ions, which cover more than 80% of the metal-bound structures reported on the PDB. Simulations performed using the SIRAH force field on several proteins and DNA systems show that using the present approach it is possible to obtain non-bonded interaction parameters that obviate the use of topological constraints. </p>


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