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2 Publications visible to you, out of a total of 2

Abstract (Expand)

The Simulation Foundry (SF) is a modular workflow for the automated creation of molecular modeling (MM) data. MM allows for the reliable prediction of the microscopic and macroscopic properties of multicomponent systems from first principles. The SF makes MM repeatable, replicable, and findable, accessible, interoperable, and reusable (F.A.I.R.). The SF uses a standardized data structure and file naming convention, allowing for replication on different supercomputers and re-entrancy. We focus on keeping the SF simple by basing it on scripting languages that are widely used by the MM community (bash, Python) and making it reusable and re-editable. The SF was developed to assist expert users in performing parameter studies of multicomponent systems by high throughput molecular dynamics simulations. The usability of the SF is demonstrated by simulations of thermophysical properties of binary mixtures. A standardized data exchange format enables the integration of simulated data with data from experiments. The SF also provides a complete documentation of how the results were obtained, thus assigning provenance. Increasing computational power facilitates the intensification of the simulation process and requires automation and modularity. The SF provides a community platform on which to integrate new methods and create data that is reproducible and transparent (https://fairdomhub.org/studies/639/snapshots/1, https://fairdomhub.org/studies/639/snapshots/2).

Authors: Gudrun Gygli, Juergen Pleiss

Date Published: 27th Apr 2020

Publication Type: Journal

Abstract

Not specified

Authors: Xinmeng Xu, Jan Range, Gudrun Gygli, Jürgen Pleiss

Date Published: 12th Mar 2020

Publication Type: Journal

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