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Publication in Nature Materials
A subtitle of this work: Machine learning without data!S. M. Moosavi, B. Á. Novotny, D. Ongari, E. Moubarak, M. Asgari, Ö. Kadioglu, C. Charalambous, A. Ortega-Guerrero, A. H. Farmahini, L. Sarkisov, S. Garcia, F. Noé, and B. Smit, A data-science approach to predict the heat capacity of nanoporous materials Nat Mater (2022) http://dx.doi.org/10.1038/s41563-022-01374-3 See the news (…)
Perspective in Nature Chemistry: Pancakes and Chemical Data
See the press release: https://actu.epfl.ch/news/chemical-data-management-an-open-way-forward-6/ Kevin and Luc have written their vision on Open Science and Chemical Data in: K. M. Jablonka, L. Patiny, and B. Smit, Making the collective knowledge of chemistry open and machine actionable Nat Chem 14 (4), 365 (2022) http://dx.doi.org/10.1038/s41557-022-00910-7
Publication in Nature Chemistry
Kevin, Daniele and Mohamad inspired by one of the life lines of “How to become a millionaire” for a model to predict oxidation states of MOFs.Interested:K. M. Jablonka, D. Ongari, S. M. Moosavi, and B. Smit, Using collective knowledge to assign oxidation states of metal cations in metal–organic frameworks Nat Chem (2021) http://dx.doi.org/10.1038/s41557-021-00717-y
Latest publications
Machine learning for industrial processes: Forecasting amine emissions from a carbon capture plant
K. M. Jablonka, C. Charalambous, E. Sanchez Fernandez, G. Wiechers, J. Monteiro, P. Moser, B. Smit, and S. Garcia, Machine learning for industrial processes: Forecasting amine emissions from a carbon capture plant Sci Adv 9 (1), eadc9576 (2023) doi: 10.1126/sciadv.adc9576Abstract: One of the main environmental impacts of amine-based carbon capture processes is the emission of the (…)
How to Decarbonize Our Energy Systems: Process-Informed Design of New Materials for Carbon Capture
S. Garcia and B. Smit, How to Decarbonize Our Energy Systems: Process-Informed Design of New Materials for Carbon Capture Chem Ing Tech (2023) doi: 10.1002/cite.202200179Abstract: Decarbonisation from a variety of industrial and power emission sectors highlights a marked need for capture technologies that can be optimized for different CO2 sources and integrated into an equally diverse range of (…)
Using genetic algorithms to systematically improve the synthesis conditions of Al-PMOF
N. P. Domingues, S. M. Moosavi, L. Talirz, K. M. Jablonka, C. P. Ireland, F. M. Ebrahim, and B. Smit, Using genetic algorithms to systematically improve the synthesis conditions of Al-PMOF Commun Chem 5 (1), 170 (2022) doi: 0.1038/s42004-022-00785-2Abstract: The synthesis of metal-organic frameworks (MOFs) is often complex and the desired structure is not always obtained. (…)