A data-science approach to predict the heat capacity of nanoporous materials
Seyed Mohamad Moosavi(École Polytechnique Fédérale de Lausanne), Berend Smit(Hôpital de Sion), Özge Kadioglu(École Polytechnique Fédérale de Lausanne), Amir H. Farmahini(University of Manchester), Charithea Charalambous(Heriot-Watt University), Susana García(Heriot-Watt University), Lev Sarkisov(University of Edinburgh), Balázs Álmos Novotny(École Polytechnique Fédérale de Lausanne), Frank Noé(Microsoft (United States)), Daniele Ongari(École Polytechnique Fédérale de Lausanne), Andres Ortega‐Guerrero(École Polytechnique Fédérale de Lausanne), Elias Moubarak(École Polytechnique Fédérale de Lausanne), Mehrdad Asgari(University of Cambridge)
Cited by 124
Related Papers
Towards a molecular understanding of shape selectivity
|Nature|2008|573
Computer simulations of vapor–liquid phase equilibria of <i>n</i>-alkanes
|The Journal of Chemical Physics|1995|495
The Role of Machine Learning in the Understanding and Design of Materials
|Journal of the American Chemical Society|2020|413
Post-combustion CO2 capture with a commercial activated carbon: Comparison of different regeneration strategies
|Chemical Engineering Journal|2010|358