SESSION 4: TOWARDS LONGER LENGTH SCALES
The Nanoporous Materials Genome in Action: Capturing CO2, Similarity, and Intuition
Laboratory of molecular simulation (LSMO), Institut des Sciences et Ingénierie Chimiques, Valais
Ecole Polytechnique Fédérale de Lausanne (EPFL), Rue de l’Industrie 17, CH-1951 Sion, Switzerland
Keywords: materials genomics, metal-organic frameworks, molecular qimulation, carbon capture, machine learning
The attractive feature of Metal Organic Frameworks (MOFs) isthat by changing the ligand and/or metal, theycan be chemically tuned to perform optimally for agiven application. This unique chemical tunability allows us to tailor-make materials that are optimal for a given application. The promise of finding just the right material seems remote however: because of practical limitations we can only ever synthesize, characterize, and test a tiny fraction of all possible materials. To take full advantage of this development, therefore, we need to develop alternative techniques, collectively referred to as Materials Genomics,[1] to rapidly screen large numbers of materials and obtain fundamental insights into the chemical nature of the ideal material for a given application. These computational materials genomics initiatives have been so successful that we have created a new problem: what to do with so much data? In this presentation we will discuss different computational strategies to dealwith a large amount of data. We illustrate on the use of these strategies by addressing the following questions: How the find the best material for a given application? How to find materials with similar pore shape?[2] How to design a material that optimally binds CO2? And, what can we learn from failed experiments?[3]
[1] P. G. Boyd, Y. Lee, and B. Smit, Computational development of the nanoporous materials genome, Nat. Rev. Mater., 2, 17037, 2017
[2] Y. Lee, S. D. Barthel, P. Dlotko, S. M. Moosavi, K. Hess, and B. Smit, Quantifying similarity of pore-geometry in nanoporous materials, Nat. Commun., 8, 15396, 2017
[3] S. M. Moosavi, A. Chidambaram, L. Talirz, M. Haranczyk, K. C. Stylianou, and B. Smit, Capturing chemical intuition in synthesis of metal-organic frameworks, Nat. Commun., 10, 539, 2019