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Publication . Article . Other literature type . 2020

Unfolding the prospects of computational (bio)materials modelling

G. J. Agur Sevink; Jozef A. Liwo; Pietro Asinari; Donal MacKernan; Giuseppe Milano; Ignacio Pagonabarraga;
Open Access   English  
Published: 08 Sep 2020
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. Ministerio de Ciencia, Innovacion y Universidades Generalitat de Catalunya Swiss National Science Foundation National Science Center of Poland Italian National Project
Subjects by Vocabulary

Microsoft Academic Graph classification: State (computer science) Computer data storage business.industry business Consistency (database systems) Selection (linguistics) Data exchange Viewpoints Data migration Computer science Systems engineering Sketch

Subjects

Molecular dynamics, Machine learning, Coarse-grained computational models, Physical and Theoretical Chemistry, General Physics and Astronomy, biomolecular systems, force-field, potentials, Dinàmica molecular, Aprenentatge automàtic, modelling, (bio)materials

Funded by
EC| E-CAM
Project
E-CAM
An e-infrastructure for software, training and consultancy in simulation and modelling
  • Funder: European Commission (EC)
  • Project Code: 676531
  • Funding stream: H2020 | RIA
Validated by funder