Unfolding the prospects of computational (bio)materials modelling

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Title: Unfolding the prospects of computational (bio)materials modelling
Authors: Sevink, G. J. AgurLiwo, Jozef AdamAsinari, PietroMacKernan, Donalet al.
Permanent link: http://hdl.handle.net/10197/12576
Date: 8-Sep-2020
Online since: 2021-10-26T11:47:09Z
Abstract: In this perspective communication, we briefly sketch the current state of computational (bio)materials research and discuss possible solutions for the four challenges that have been increasingly identified within this community: i) the desire to develop a unified framework for testing the consistency of implementation and of physical accuracy for newly developed methodologies, ii) the selection of a standard format that can deal with the diversity of simulation data and at the same time simplifies data storage, data exchange and data reproduction, iii) how to deal with the generation, storage and analysis of massive data, and iv) the benefits of efficient ’core’ engines. Expressed viewpoints are the result of discussions between computational stakeholders during a Lorentz Center workshop with the prosaic title Workshop on Multi-scale Modelling and are aimed at: i) improving validation, reporting and reproducibility of computational results, ii) improving data migration between simulation packages and with analysis tools, iii) popularising the use of coarse-grained and multi-scale computational tools among non-experts, opening up these modern computational developments to an extended user community.
Funding Details: Ministerio de Ciencia, Innovacion y Universidades
Generalitat de Catalunya
Swiss National Science Foundation
National Science Center of Poland
Italian National Project
Type of material: Journal Article
Publisher: AIP Publishing
Journal: Journal of Chemical Physics
Volume: 153
Issue: 10
Copyright (published version): 2020 the Authors
Keywords: Molecular dynamicsMachine learningCoarse-grained computational models
DOI: 10.1063/5.0019773
Language: en
Status of Item: Peer reviewed
ISSN: 0021-9606
This item is made available under a Creative Commons License: https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Appears in Collections:Physics Research Collection

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