5 papers
Hyper-Dimensional Fingerprints as Molecular Representations
Jonas Teufel, Luca Torresi, André Eberhard +1
Computational molecular representations underpin virtual screening, property prediction, and materials discovery. Conventional fingerprints are efficient and deterministic but lose…
Generative Models for Crystalline Materials
Houssam Metni, Laura Ruple, Lauren N. Walters +13
Understanding structure-property relationships in materials is fundamental in condensed matter physics and materials science. Over the past few years, machine learning (ML) has eme…
Multi-stage Bayesian optimisation for dynamic decision-making in self-driving labs
Luca Torresi, Pascal Friederich
Self-driving laboratories (SDLs) are combining recent technological advances in robotics, automation, and machine learning based data analysis and decision-making to perform autono…
A self-driving lab for solution-processed electrochromic thin films
Selma Dahms, Luca Torresi, Shahbaz Tareq Bandesha +5
Solution-processed electrochromic materials offer high potential for energy-efficient smart windows and displays. Their performance varies with material choice and processing condi…
Symmetry-Aware Bayesian Flow Networks for Crystal Generation
Laura Ruple, Luca Torresi, Henrik Schopmans +1
The discovery of new crystalline materials is essential to scientific and technological progress. However, traditional trial-and-error approaches are inefficient due to the vast se…