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Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/173616
Unfolding the prospects of computational (bio)materials modelling
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In this perspective communication, we briefly sketch the current state of computational (bio)material 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 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 Modeling 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) popularizing the use of coarse-grained and multi-scale computational tools among non-experts and opening up these modern computational developments to an extended user community.
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SEVINK, Geert Jan Agur, et al. Unfolding the prospects of computational (bio)materials modelling. Journal of Chemical Physics. 2020. Vol. 153, num. 100901. ISSN 0021-9606. [consulted: 7 of June of 2026]. Available at: https://hdl.handle.net/2445/173616