3 citations · 4 across the 4 of their papers we have counts for
4 papers
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,…
Are nonequilibrium effects relevant for chiral molecule discrimination?
Federico Ravera, Leonardo Medrano Sandonas, Rafael Gutierrez +2
Sensing and discriminating between enantiomers of chiral molecules remains a significant challenge in the design of sensor platforms. In the case of chemoresistive sensors, where d…
Enabling Inverse Design in Chemical Compound Space: Mapping Quantum Properties to Structures for Small Organic Molecules
Alessio Fallani, Leonardo Medrano Sandonas, Alexandre Tkatchenko
Computer-driven molecular design combines the principles of chemistry, physics, and artificial intelligence to identify novel chemical compounds and materials with desired properti…
Molecules in Environments: Towards Systematic Quantum Embedding of Electrons and Drude Oscillators
Matej Ditte, Matteo Barborini, Leonardo Medrano Sandonas +1
We develop a quantum embedding method that enables accurate and efficient treatment of interactions between molecules and an environment, while explicitly including many-body corre…