An Ecosystem for Digital Reticular Chemistry
K. M. Jablonka, A. S. Rosen, A. S. Krishnapriyan, and B. Smit, An Ecosystem for Digital Reticular Chemistry ACS Cent. Sci. (2023) doi: 10.1021/acscentsci.2c01177 Abstract: The vastness of the materials design space makes it impractical to explore using traditional brute-force methods, particularly in reticular chemistry. However, machine learning has shown promise in expediting and guiding (…)
MOF-based oxygen carriers with antioxidant activity resulting from the incorporation of gold nanozymes
X. Liu, N. P. Domingues, E. Oveisi, C. Coll-Satue, M. M. T. Jansman, B. Smit, and L. Hosta-Rigau, Metal–organic framework-based oxygen carriers with antioxidant activity resulting from the incorporation of gold nanozymes Biomater. Sci. (2023) doi: 10.1039/D2BM01405J Abstract: Blood transfusions are a life-saving procedure since they can preserve the body’s oxygen levels in patients suffering (…)
CO2 photoreduction to CO on MOF-derived TiO2
M. Garvin, W. A. Thompson, J. Z. Y. Tan, S. Kampouri, C. P. Ireland, B. Smit, A. Brookfield, D. Collison, L. Negahdar, A. M. Beale, M. M. Maroto-Valer, R. D. McIntosh, and S. Garcia, Highly selective CO2 photoreduction to CO on MOF-derived TiO2 RSC Sustainability (2023) Doi: 10.1039/D2SU00082B Abstract Metal–Organic Framework (MOF)-derived TiO2, synthesised through (…)
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.adc9576 Abstract: One of the main environmental impacts of amine-based carbon capture processes is the emission of (…)
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.202200179 Abstract: 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 (…)
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/s42004-022-00785-2 Abstract: The synthesis of metal-organic frameworks (MOFs) is often complex and the desired structure is not always (…)
J. Young, F. McIlwaine, B. Smit, S. Garcia, and M. van der Spek, Process-informed adsorbent design guidelines for direct air capture Chem Eng J, 141035 (2022) doi: 10.1016/j.cej.2022.141035 Abstract: Direct air capture using solid adsorbents is a proven technology critical to reducing our net greenhouse gas emissions to zero and beyond. Currently, academic research into the (…)
Mechanically robust mesoporous merged-net MOFs
H. Jiang, S. M. Moosavi, J. Czaban-Jóźwiak, B. Torre, A. Shkurenko, Z. O. Ameur, J. Jia, N. Alsadun, O. Shekhah, E. Di Fabrizio, B. Smit, and M. Eddaoudi, Reticular chemistry for the rational design of mechanically robust mesoporous merged-net metal-organic frameworks Matter-Us (2022) doi: 10.1016/j.matt.2022.10.004 Abstract: Access to metal-organic frameworks (MOFs) with enhanced mechanical stability (…)
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 (…)
A data-science approach to predict the heat capacity of nanoporous materials
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) doi: 10.1038/s41563-022-01374-3 Abstract: The heat capacity of a material is a (…)