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Molecular design software is notable software for molecular modeling, that provides special support for developing molecular models de novo. In contrast to the usual molecular modeling programs, such as for molecular dynamics and quantum chemistry, such software directly supports the aspects related to constructing molecular models, including: Molecular graphics interactive molecular drawing and conformational editing building polymeric molecules, crystals, and solvated systems partial charges development g
Abalone is a general purpose molecular dynamics and molecular graphics program for simulations of bio-molecules in a periodic boundary conditions in explicit (flexible SPC water model) or in implicit water models. Mainly designed to simulate the protein folding and DNA-ligand complexes in AMBER force field. 3D molecular graphics Automatic Force Field generator for bioelements: H, C, N, O Building and editing chemical structures Library of building blocks Force fields: Assisted Model Building with Energy Re
GROMACS is a molecular dynamics package mainly designed for simulations of proteins, lipids, and nucleic acids. It was originally developed in the Biophysical Chemistry department of University of Groningen, and is now maintained by contributors in universities and research centers worldwide. GROMACS is one of the fastest and most popular software packages available, and can run on central processing units (CPUs) and graphics processing units (GPUs). It is free, open-source software released under the GNU General Public License (GPL), and starting with version 4.
In recent years, we have been witnessing a paradigm shift in computational materials science. In fact, traditional methods, mostly developed in the second half of the XXth century, are being complemented, extended, and sometimes even completely replaced by ...
Despite governing heat management in any realistic device, the microscopic mechanisms of heat transport in all-solid-state electrolytes are poorly known: existing calculations, all based on simplistic semi-empirical models, are unreliable for superionic co ...
We provide an introduction to Gaussian process regression (GPR) machinelearning methods in computational materials science and chemistry. The focus of the present review is on the regression of atomistic properties: in particular, on the construction of in ...
Explores Molecular Dynamics simulations for studying cement materials and diffusion processes, covering algorithms, force fields, data analysis, and recommended resources.
