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Benjamin André René Meyer

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Publications associées (14)

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The application of machine learning to theoretical chemistry has made it possible to combine the accuracy of quantum chemical energetics with the thorough sampling of finite-temperature fluctuations. To reach this goal, a diverse set of methods has been pr ...

2022

Hamiltonian-Reservoir Replica Exchange and Machine Learning Potentials for Computational Organic Chemistry

Alberto Fabrizio, Benjamin André René Meyer, Raimon Fabregat I De Aguilar-Amat, Daniel Hollas

This work combines a machine learning potential energy function with a modular enhanced sampling scheme to obtain statistically converged thermodynamical properties of flexible medium-size organic molecules at high ab initio level. We offer a modular envir ...

AMER CHEMICAL SOC2020

Machine learning models of the energy curvature vs particle number for optimal tuning of long-range corrected functionals

Alberto Fabrizio, Benjamin André René Meyer

The average energy curvature as a function of the particle number is a molecule-specific quantity, which measures the deviation of a given functional from the exact conditions of density functional theory. Related to the lack of derivative discontinuity in ...

AMER INST PHYSICS2020

Data-Driven Advancement of Homogeneous Nickel Catalyst Activity for Aryl Ether Cleavage

Matthew Wodrich, Benjamin André René Meyer, Manuel Cordova, Boodsarin Sawatlon

The increasing urgency to make chemical processes more environmentally friendly while continuing to derive the chemicals required for modern society from renewable resources requires the development of a forthcoming generation of synthetic processes and th ...

AMER CHEMICAL SOC2020

Seroprevalence of anti-SARS-CoV-2 IgG antibodies in Geneva, Switzerland (SEROCoV-POP): a population-based study

Didier Trono, Idris Guessous, Benjamin André René Meyer, David Nicolas De Ridder, Dusan Petrovic

Assessing the burden of COVID-19 on the basis of medically attended case numbers is suboptimal given its reliance on testing strategy, changing case definitions, and disease presentation. Population-based serosurveys measuring anti-severe acute respiratory ...

2020

Transferable Machine-Learning Model of the Electron Density

Michele Ceriotti, Alberto Fabrizio, David Mark Wilkins, Benjamin André René Meyer, Andrea Grisafi

The electronic charge density plays a central role in determining the behavior of matter at the atomic scale, but its computational evaluation requires demanding electronic-structure calculations. We introduce an atom-centered, symmetry-adapted framework t ...

2019

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Chemists continuously harvest the power of non-covalent interactions to control phenomena in both the micro- and macroscopic worlds. From the quantum chemical perspective, the strategies essentially rely upon an in-depth understanding of the physical origi ...

ROYAL SOC CHEMISTRY2019

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The speed and precision of machine-learning (ML) techniques in determining quantum chemical properties has resulted in a considerable computational speed up in comparison to traditional quantum chemical methods, and now allows a desired property of thousan ...

2019

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The study of organic molecular crystals under high pressure provides fundamental insight into crystal packing distortions and reveals mechanisms of phase transitions and the crystallization of polymorphs. These solid-state transformations can be monitored ...

AMER CHEMICAL SOC2019

The coupling of the crystallographic refinement technique Hirshfeld atom refinement (HAR) with the recently constructed libraries of extremely localized molecular orbitals (ELMOs) gives rise to the new quantum-crystallographic method HAR-ELMO. This method ...

AMER CHEMICAL SOC2019