Publications of Lucas Foppa

Journal Article (8)

2024
Journal Article
Miyazaki, Ray, Kendra S. Belthle, Harun Tüysüz, Lucas Foppa and Matthias Scheffler: Materials Genes of CO2 Hydrogenation on Supported Cobalt Catalysts: An Artificial Intelligence Approach Integrating Theoretical and Experimental Data.
2023
Journal Article
Foppa, Lucas, Rüther Frederik, Michael Geske, Gregor Koch, Frank Girgsdies, Pierre Kube, Spencer Carey, Michael Hävecker, Olaf Timpe, Andrey Tarasov, Matthias Scheffler, Frank Rosowski, Robert Schlögl and Annette Trunschke: Data-Centric Heterogeneous Catalysis: Identifying Rules and Materials Genes of Alkane Selective Oxidation.
2022
Journal Article
Belthle, Kendra S., Tuğçe Beyazay, Cristina Ochoa-Hernández, Ray Miyazaki, Lucas Foppa, William F. Martin and Harun Tüysüz: Effects of Silica Modification (Mg, Al, Ca, Ti, and Zr) on Supported Cobalt Catalysts for H2-Dependent CO2 Reduction to Metabolic Intermediates.
Journal Article
Foppa, Lucas and Luca M. Ghiringhelli: Identifying Outstanding Transition‑Metal‑Alloy Heterogeneous Catalysts for the Oxygen Reduction and Evolution Reactions via Subgroup Discovery.
Journal Article
Foppa, Lucas, Thomas Purcell, Sergey V. Levchenko, Matthias Scheffler and Luca M. Ghiringhelli: Hierarchical Symbolic Regression for Identifying Key Physical Parameters Correlated with Bulk Properties of Perovskites.
Journal Article
Foppa, Lucas, Christopher A. Sutton, Luca M. Ghiringhelli, Sandip De, Patricia Löser, Stephan A. Schunk, Ansgar Schäfer and Matthias Scheffler: Learning Design Rules for Selective Oxidation Catalysts from High-Throughput Experimentation and Artificial Intelligence.
2021
Journal Article
Foppa, Lucas, Luca M. Ghiringhelli, Frank Girgsdies, Maike Hashagen, Pierre Kube, Michael Hävecker, Spencer Carey, Andrey Tarasov, Peter Kraus, Frank Rosowski, Robert Schlögl, Annette Trunschke and Matthias Scheffler: Materials genes of heterogeneous catalysis from clean experiments and artificial intelligence.

Talk (16)

2023
Talk
Foppa, Lucas: Identifying Rules and Materials Genes of Properties and Functions via AI.
(IOP-FHI workshop, Frontiers of Electronic Structure Theory and Materials Genomics, Beijing, China, Oct 2023).
Talk
Foppa, Lucas: The Catalyst "Genes" Identified by Artificial Intelligence.
(22nd Brazilian Congress on Catalysis, Bento Gonçalves, Brazil, Sep 2023).
Talk
Foppa, Lucas: The "Genes" of Materials Properties and Functions Identified by Symbolic Regression.
(9th International Summer School on AI and Big Data, Center for Scalable Data Analytics and Artificial Intelligence, Dresden, Germany, Jul 2023).
Talk
Foppa, Lucas: Data-Centric Materials Science: Identifying "Materials Genes" With AI.
(Seminar, Institute of Materials Chemistry, TU Wien, Vienna, Austria, Jun 2023).
Talk
Foppa, Lucas: Subgroup Discovery.
(School on Artificial Intelligence for Materials Science in the Exascale Era, Platja d’Aro, Spain, May 2023).
Talk
Foppa, Lucas: Identifying Materials Genes of Properties and Functions via AI.
(School on Artificial Intelligence for Materials Science in the Exascale Era, Platja d’Aro, Spain, May 2023).
Talk
Foppa, Lucas: Dentifying Rules and Materials Genes of Heterogeneous Catalysis via Artificial Intelligence.
(Seminar, School of Chemistry, University of Nottingham, Nottingham, UK, Mar 2023).
2022
Talk
Foppa, Lucas: Materials Genes of Heterogeneous Catalysis From Clean Experiments and Artificial Intelligence.
(8th UK Catalysis Conference (UKCC2022), Loughborough, UK, Jan 2022).
Talk
Foppa, Lucas: Hierarchical Symbolic Regression for Identifying Key Physical Parameters Correlated With Materials Properties.
(Seminar, Cardiff University, Online Event, Feb 2022).
Talk
Foppa, Lucas: Clean Experimental Data for Artificial Intelligence – A Key to Decoding Materials Genes in Heterogeneous Catalysis.
(The 27th North American Catalysis Society Meeting (NAM27), New York, NY, USA, May 2022).
Talk
Foppa, Lucas: Materials Genes of Selective Oxidation From Clean Experiments and Artificial Intelligence.
(Symposium, FUNCAT/Center2Center Meeting, Berlin, Germany, Apr 2022).
Talk
Foppa, Lucas: Hierarchical Symbolic Regression for Identifying Key Physical Parameters Correlated With Materials Properties.
(Machine Learning School for Materials @ ILUM, Online Event, Sep 2022).
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