346 citations · 4.4k across the 109 of their papers we have counts for
111 papers
Toward the Rational Design of Molecular Field-Coupled Nanocomputing Candidates
Federico Ravera, Leonardo Medrano Sandonas, Andrea Vezzoli +4
Molecular Field-Coupled Nanocomputing (MolFCN) is a promising beyond-CMOS paradigm in which information is propagated electrostatically rather than through charge transport, enabli…
Data-Driven Thermal and Mechanical Modeling of Defective Covalent Organic Frameworks
Aleksander Szewczyk, Leonardo Medrano Sandonas, David Bodesheim +2
Covalent Organic Frameworks (COFs) are versatile two-dimensional (2D) materials for flexible electronics, catalysis, and sensing, owing to their tunable architectures and large sur…
Interpretable Machine Learning for Quantum-Informed Property Predictions in Artificial Sensing Materials
Li Chen, Leonardo Medrano Sandonas, Shirong Huang +2
Digital sensing faces challenges in developing sustainable methods to extend the applicability of customized e-noses to complex body odor volatilome (BOV). To address this challeng…
On-the-Fly Machine Learning of Interatomic Potentials for Elastic Property Modeling in Al-Mg-Zr Solid Solutions
Lukas Volkmer, Leonardo Medrano Sandonas, Philip Grimm +2
The development of resilient and lightweight Aluminum alloys is central to advancing structural materials for energy-efficient engineering applications. To address this challenge,…
What do Large Language Models know about materials?
Adrian Ehrenhofer, Thomas Wallmersperger, Gianaurelio Cuniberti
Large Language Models (LLMs) are increasingly applied in the fields of mechanical engineering and materials science. As models that establish connections through the interface of l…
Vanadium-doped HfO, multiferroic uncompromised
Vincenzo Fiorentini, Paola Alippi, Gianaurelio Cuniberti
Ab initio density-functional calculations show that orthorhombic Pca21 hafnia HfO2 mixed with vanadium at low concentration is a ferroelectric and ferromagnetic insulator. The mult…