Modelling of framework materials at multiple scales: current practices and open questions

18 February 2019, Version 3
This content is a preprint and has not undergone peer review at the time of posting.


The last decade has seen an explosion of the family of framework materials and their study, both from the experimental and computational point of view. We propose here a short highlight of the current state of methodologies for modelling framework materials at multiple scales, putting together a brief review of new methods and recent endeavours in this area, as well as outlining some of the open challenges in this field. We will detail advances in atomistic simulation methods, the development of materials databases, and the growing use of machine learning for properties prediction.


molecular simulation
framework materials
machine learning


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