43 citations · 54 across the 2 of their papers we have counts for
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cond-mat.mtrl-sci2025★ 5 cited
Predicting neutron experiments from first principles: A workflow powered by machine learning
Eric Lindgren, Adam J. Jackson, Erik Fransson +6
Machine learning has emerged as a powerful tool in materials discovery, enabling the rapid design of novel materials with tailored properties for countless applications, including…
cond-mat.mtrl-sci2021★ 43 cited
Green reconstruction of MIL-100 (Fe) in water for high crystallinity and enhanced guest encapsulation
Barbara E. Souza, Annika F. Möslein, Kirill Titov +3
MIL-100 (Fe) is a highly porous metal-organic framework (MOF), considered as a promising carrier for drug delivery, and for gas separation and capture applications. However, this f…