139 citations · 196 across the 6 of their papers we have counts for
9 papers
QUPEX: A Streamlit-Based Framework for Visualizing Quantum-Mechanical Property Spaces of Organic Molecules
Mirtha Pillaca Quispe, Alejandra Hinostroza Caldas, Leonardo Medrano Sandonas
The growing availability of quantum-mechanical (QM) datasets offers new opportunities to investigate structure-property and property-property relationships in drug-like molecules u…
QALPA: Property-guided diffusion modeling for efficient exploration of chemical spaces of flexible molecules
Michael Hanna, Julian Cremer, Zekiye Erarslan +1
Exploring the chemical space of flexible molecules remains challenging because the vast number of possible compounds and conformations, together with the increasing cost and limite…
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…
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…
Accurate Machine Learned Quantum-Mechanical Force Fields for Biomolecular Simulations
Oliver T. Unke, Martin Stöhr, Stefan Ganscha +8
Molecular dynamics (MD) simulations allow atomistic insights into chemical and biological processes. Accurate MD simulations require computationally demanding quantum-mechanical ca…
QM7-X: A comprehensive dataset of quantum-mechanical properties spanning the chemical space of small organic molecules
Johannes Hoja, Leonardo Medrano Sandonas, Brian G. Ernst +3
We introduce QM7-X, a comprehensive dataset of 42 physicochemical properties for 4.2 M equilibrium and non-equilibrium structures of small organic molecules with up to se…
Thermal bridging of graphene nanosheets via covalent molecular junctions. a Non-Equilibrium Green Functions Density Functional Tight-Binding study
Diego Martinez, Alessandro di Pierro, Alessandro Pecchia +7
Despite the uniquely high thermal conductivity of graphene is well known, the exploitation of graphene into thermally conductive nanomaterials and devices is limited by the ineffic…