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Metal-organic frameworks (MOFs) are crystalline materials composed of a metal node connected by an organic linker. By varying metal nodes and organic linkers, chemists can synthesize an almost limitless array of materials suited for applications such as gas separation, gas storage, sensing, and catalysis. This versatility makes MOFs an ideal playground for data science. In this seminar, we explore how data science approaches can assist in designing MOFs for carbon capture. We discuss how these methods can provide insights into questions that traditional theories do not fully address, including the oxidation state of metals and the heat capacity of MOFs. Additionally, we illustrate how data-driven analysis helps pinpoint the characteristics of the highest-performing materials for a carbon capture process.
Berend Smit received an MSc in Chemical Engineering in 1987 and an MSc in Physics from the Technical University in Delft (the Netherlands). He received in 1990 cum laude Ph.D. in Chemistry from Utrecht University (the Netherlands). He was a (senior) Research Physicist at Shell Research from 1988-1997, Professor of Computational Chemistry at the University of Amsterdam (the Netherlands) 1997-2007. In 2004, Berend Smit was elected Director of the European Center of Atomic and Molecular Computations (CECAM) in Lyon, France. In 2007 he was appointed Professor of Chemical Engineering and Chemistry at U.C. Berkeley and Faculty Chemist at the Materials Sciences Division, Lawrence Berkeley National Laboratory. Since July 2014, he is a full professor at EPFL. In 2024 was elected as a Foreign Member of the Royal Netherlands Academy of Arts and Sciences (KNAW).
Berend Smit’s research focuses on the application and development of novel molecular simulation techniques, with an emphasis on energy-related applications.