Chapter 1: Machine Learning Methods for Predicting Adsorption in Metal-Organic Frameworks (MOFs)
Chapter 1: Machine Learning Methods for Predicting Adsorption in Metal-Organic Frameworks (MOFs)
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When I entered the Snurr lab at Northwestern, I was mentored by Dr. Benjamin J. Bucior, a fifth-year graduate student, and I learned about his fascinating research in machine learning (ML). I extended the adsorbate probe-framework energy-histogram machine learning approach to chain molecules and mixture separation. I authored a paper on this topic.
Z. Li, B. J. Bucior, H. Chen, M. Haranczyk, J. I. Siepmann, and R. Q. Snurr. Machine Learning Using Host/Guest Energy Histograms to Predict Adsorption in Metal–Organic Frameworks: Application to Short Alkanes and Xe/Kr Mixtures. J. Chem. Phys. 2021, 155 (1), 014701 (LINK)
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