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Too Many Materials and Too Many Applications: An Experimental Problem Waiting for a Computational Solution

[Image: see text] Finding the best material for a specific application is the ultimate goal of materials discovery. However, there is also the reverse problem: when experimental groups discover a new material, they would like to know all the possible applications this material would be promising for...

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Detalles Bibliográficos
Autores principales: Ongari, Daniele, Talirz, Leopold, Smit, Berend
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2020
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7706098/
https://www.ncbi.nlm.nih.gov/pubmed/33274268
http://dx.doi.org/10.1021/acscentsci.0c00988
Descripción
Sumario:[Image: see text] Finding the best material for a specific application is the ultimate goal of materials discovery. However, there is also the reverse problem: when experimental groups discover a new material, they would like to know all the possible applications this material would be promising for. Computational modeling can aim to fulfill this expectation, thanks to the sustained growth of computing power and the collective engagement of the scientific community in developing more efficient and accurate workflows for predicting materials’ performances. We discuss the impact that reproducibility and automation of the modeling protocols have on the field of gas adsorption in nanoporous crystals. We envision a platform that combines these tools and enables effective matching between promising materials and industrial applications.