AI Article Synopsis
- Finding the right material for a specific application is a key goal in materials discovery, but there's also a need to explore potential applications for newly discovered materials.
- Advances in computational modeling, driven by increased computing power and collaborative improvements in workflows, can help predict how materials will perform in various applications.
- The discussion highlights the importance of reproducibility and automation in modeling gas adsorption in nanoporous crystals, with a vision for creating a platform that effectively connects new materials to industrial uses.
Article Abstract
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.
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Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7706098 | PMC |
| http://dx.doi.org/10.1021/acscentsci.0c00988 | DOI Listing |
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