Publications of Lucas Foppa
All genres
Talk (35)
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).
Talk
Foppa, Lucas: Identifying Materials Genes of Properties and Functions via Artificial Intelligence.
(NOMAD Meeting, Revealing New and Novel Materials, Mechanisms, and Insights (a Perspective), Potsdam, Germany, Oct 2022).
Talk
Foppa, Lucas: Beyond a Single Description in Subgroup Discovery of Exceptional Materials: Coherent Collections of Rules Clustered by Similarity.
(NOMAD Workshop, Data-centric Cruising for New and Novel Materials, Mechanisms, and Insights, Kiel, Germany, Sep 2022).
Talk
Foppa, Lucas: Identifying Materials Genes of Properties and Functions via Artificial Intelligence.
(DPG Meeting of the Condensed Matter Section (SKM) 2022, Regensburg, Germany, Oct 2022).
2021
Talk
Foppa, Lucas: Identifying the Materials Genes of Heterogeneous Catalysis With Clean Experiments and Tailored Artificial Intelligence.
(Colloquium, ETH Zurich, Department of Chemistry and Applied Biosciences, Online Event, Dec 2021).
Working Paper (7)
2025
Working Paper
, , , , , , Matthias Scheffler and Lucas Foppa: Modelling the Time-Dependent Reactivity of Catalysts by Experiments and Artificial Intelligence.
Working Paper
Nair, Akhil Sugathan, Lucas Foppa and Matthias Scheffler: Materials Database from All-electron Hybrid Functional DFT Calculations.
2024
Working Paper
, , Lucas Foppa, Kisung Kang, , , Akhil Sugathan Nair, , , Matthias Scheffler, , , and : Workflows for Artificial Intelligence.
Working Paper
Foppa, Lucas and Matthias Scheffler: Coherent Collections of Rules Describing Exceptional Materials Identified with a Multi-Objective Optimization of Subgroups.
Working Paper
Sugathan Nair, Akhil, Lucas Foppa and Matthias Scheffler: Materials-Discovery Workflows Guided by Symbolic Regression: Identifying Acid-Stable Oxides for Electrocatalysis.
2023
Working Paper
, , , , Lucas Foppa and Matthias Scheffler: From Prediction to Action: The Critical Role of Proper Performance Estimation for Machine-Learning-Driven Materials Discovery.
Working Paper
Foppa, Lucas and Matthias Scheffler: Towards a Multi-Objective Optimization of Subgroups for the Discovery of Materials with Exceptional Performance.