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Leonardo Medrano Sandonas

Showing results (1-10 of 30) with videos related to

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The Journal of Physical Chemistry Letters|August 14, 2020
Accurate Many-Body Repulsive Potentials for Density-Functional Tight Binding from Deep Tensor Neural NetworksMartin Stöhr, Leonardo Medrano Sandonas, Alexandre Tkatchenko
Nature Communications|July 18, 2024
Inverse mapping of quantum properties to structures for chemical space of small organic moleculesAlessio Fallani, Leonardo Medrano Sandonas, Alexandre Tkatchenko
Physical Review Letters|December 15, 2023
Molecules in Environments: Toward Systematic Quantum Embedding of Electrons and Drude OscillatorsMatej Ditte, Matteo Barborini, Leonardo Medrano Sandonas, et al.
Physical Chemistry Chemical Physics : PCCP|August 11, 2023
Data-driven tailoring of molecular dipole polarizability and frontier orbital energies in chemical compound spaceSzabolcs Góger, Leonardo Medrano Sandonas, Carolin Müller, et al.
Advanced Science (Weinheim, Baden-Wurttemberg, Germany)|April 6, 2018
First-Principle-Based Phonon Transport Properties of Nanoscale Graphene Grain BoundariesLeonardo Medrano Sandonas, Hâldun Sevinçli, Rafael Gutierrez, et al.
Digital Discovery|January 23, 2026
Assessing the performance of quantum-mechanical descriptors in physicochemical and biological property predictionAlejandra Hinostroza Caldas, Artem Kokorin, Alexandre Tkatchenko, et al.
Journal of Physics. Condensed Matter : an Institute of Physics Journal|June 14, 2019
Exploring the write-in process in molecular quantum cellular automata: a combined modelingand first-principle approachAlejandro Santana-Bonilla, Leonardo Medrano Sandonas, Rafael Gutierrez, et al.
Entropy (Basel, Switzerland)|December 3, 2020
Quantum Phonon Transport in Nanomaterials: Combining Atomistic with Non-Equilibrium Green's Function TechniquesLeonardo Medrano Sandonas, Rafael Gutierrez, Alessandro Pecchia, et al.
Journal of Cheminformatics|May 29, 2026
Towards the design of artificial sensing materials via quantum-informed explainable AILi Chen, Leonardo Medrano Sandonas, Shirong Huang, et al.
Journal of Chemical Theory and Computation|April 20, 2026
Machine-Learned Electrostatic Potentials for Accurate Hydration Free Energy CalculationsMathias Hilfiker, Leonardo Medrano Sandonas, Alexandre Tkatchenko, et al.
Pageof 3

Showing results (1-10 of 30) with videos related to

Sort By:
Pageof 3
The Journal of Physical Chemistry Letters|August 14, 2020
Accurate Many-Body Repulsive Potentials for Density-Functional Tight Binding from Deep Tensor Neural NetworksMartin Stöhr, Leonardo Medrano Sandonas, Alexandre Tkatchenko
Nature Communications|July 18, 2024
Inverse mapping of quantum properties to structures for chemical space of small organic moleculesAlessio Fallani, Leonardo Medrano Sandonas, Alexandre Tkatchenko
Physical Review Letters|December 15, 2023
Molecules in Environments: Toward Systematic Quantum Embedding of Electrons and Drude OscillatorsMatej Ditte, Matteo Barborini, Leonardo Medrano Sandonas, et al.
Physical Chemistry Chemical Physics : PCCP|August 11, 2023
Data-driven tailoring of molecular dipole polarizability and frontier orbital energies in chemical compound spaceSzabolcs Góger, Leonardo Medrano Sandonas, Carolin Müller, et al.
Advanced Science (Weinheim, Baden-Wurttemberg, Germany)|April 6, 2018
First-Principle-Based Phonon Transport Properties of Nanoscale Graphene Grain BoundariesLeonardo Medrano Sandonas, Hâldun Sevinçli, Rafael Gutierrez, et al.
Digital Discovery|January 23, 2026
Assessing the performance of quantum-mechanical descriptors in physicochemical and biological property predictionAlejandra Hinostroza Caldas, Artem Kokorin, Alexandre Tkatchenko, et al.
Journal of Physics. Condensed Matter : an Institute of Physics Journal|June 14, 2019
Exploring the write-in process in molecular quantum cellular automata: a combined modelingand first-principle approachAlejandro Santana-Bonilla, Leonardo Medrano Sandonas, Rafael Gutierrez, et al.
Entropy (Basel, Switzerland)|December 3, 2020
Quantum Phonon Transport in Nanomaterials: Combining Atomistic with Non-Equilibrium Green's Function TechniquesLeonardo Medrano Sandonas, Rafael Gutierrez, Alessandro Pecchia, et al.
Journal of Cheminformatics|May 29, 2026
Towards the design of artificial sensing materials via quantum-informed explainable AILi Chen, Leonardo Medrano Sandonas, Shirong Huang, et al.
Journal of Chemical Theory and Computation|April 20, 2026
Machine-Learned Electrostatic Potentials for Accurate Hydration Free Energy CalculationsMathias Hilfiker, Leonardo Medrano Sandonas, Alexandre Tkatchenko, et al.
Pageof 3