Unfolding the prospects of computational (bio)materials modelling

DC FieldValueLanguage
dc.contributor.authorSevink, G. J. Agur-
dc.contributor.authorLiwo, Jozef Adam-
dc.contributor.authorAsinari, Pietro-
dc.contributor.authorMacKernan, Donal-
dc.contributor.authoret al.-
dc.date.accessioned2021-10-26T11:47:09Z-
dc.date.available2021-10-26T11:47:09Z-
dc.date.copyright2020 the Authorsen_US
dc.date.issued2020-09-08-
dc.identifier.citationJournal of Chemical Physicsen_US
dc.identifier.issn0021-9606-
dc.identifier.urihttp://hdl.handle.net/10197/12576-
dc.description.abstractIn 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.en_US
dc.language.isoenen_US
dc.publisherAIP Publishingen_US
dc.subjectMolecular dynamicsen_US
dc.subjectMachine learningen_US
dc.subjectCoarse-grained computational modelsen_US
dc.titleUnfolding the prospects of computational (bio)materials modellingen_US
dc.typeJournal Articleen_US
dc.internal.authorcontactotherdonal.mackernan@ucd.ieen_US
dc.statusPeer revieweden_US
dc.identifier.volume153en_US
dc.identifier.issue10en_US
dc.citation.otherArticle number: 100901en_US
dc.identifier.doi10.1063/5.0019773-
dc.neeo.contributorSevink|G. J. Agur|aut|-
dc.neeo.contributorLiwo|Jozef Adam|aut|-
dc.neeo.contributorAsinari|Pietro|aut|-
dc.neeo.contributorMacKernan|Donal|aut|-
dc.neeo.contributoret al.||aut|-
dc.description.othersponsorshipMinisterio de Ciencia, Innovacion y Universidadesen_US
dc.description.othersponsorshipGeneralitat de Catalunyaen_US
dc.description.othersponsorshipSwiss National Science Foundationen_US
dc.description.othersponsorshipNational Science Center of Polanden_US
dc.description.othersponsorshipItalian National Projecten_US
dc.date.updated2020-09-03T14:38:16Z-
dc.identifier.grantid676531-
dc.identifier.grantidPGC2018-098373-B-100)-
dc.identifier.grantid2017SGR-884-
dc.identifier.grantid200021-175719-
dc.identifier.grantidMO-2017/25/B/ST4/01026-
dc.identifier.grantidUMO-2017/26/M/ST4/00044-
dc.identifier.grantid2017F7KZWS-
dc.rights.licensehttps://creativecommons.org/licenses/by-nc-nd/3.0/ie/en_US
item.fulltextWith Fulltext-
item.grantfulltextopen-
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