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Concept

Méthode quantique semi-empirique

Publications associées (32)

Encoding quantum-chemical knowledge into machine-learning models of complex molecular properties

Ksenia Briling

Statistical (machine-learning, ML) models are more and more often used in computational chemistry as a substitute to more expensive ab initio and parametrizable methods. While the ML algorithms are capable of learning physical laws implicitly from data, ad ...

EPFL2024

Thermal conductivity of Li 3 PS 4 solid electrolytes with ab initio accuracy

Michele Ceriotti, Federico Grasselli, Davide Tisi, Lorenzo Gigli

The vast amount of computational studies on electrical conduction in solid-state electrolytes is not mirrored by comparable efforts addressing thermal conduction, which has been scarcely investigated despite its relevance to thermal management and (over)he ...

Amer Physical Soc2024

Domain adaptation via alignment of operation profile for Remaining Useful Lifetime prediction

Olga Fink, Ismail Nejjar, Mengjie Zhao

Effective Prognostics and Health Management (PHM) relies on accurate prediction of the Remaining Useful Life (RUL). Data-driven RUL prediction techniques rely heavily on the representativeness of the available time-to-failure trajectories. Therefore, these ...

Elsevier2024

Seebeck Coefficient of Ionic Conductors from Bayesian Regression Analysis

Paolo Pegolo

We propose a novel approach to evaluating the ionic Seebeck coefficient in electrolytes from relatively short equilibrium molecular dynamics simulations, based on the Green-Kubo theory of linear response and Bayesian regression analysis. By exploiting the ...

Amer Chemical Soc2024

Factorized structure of the long-range two-electron integrals tensor and its application in quantum chemistry

Laura Grigori

We introduce two new approximation methods for the numerical evaluation of the long-range component of the range-separated Coulomb potential and the approximation of the resulting high dimensional Two-Electron Integrals tensor (TEI) with long-range interac ...

Academic Press Inc Elsevier Science2023

Salt Bridge Structure of Microhydrated Arginine Kinetically Trapped in the Gas Phase by Evaporative Cooling

Oleg Boyarkine, Andrei Zviagin

Aminoacids and peptides generally exhibit zwitterionic forms withsalt bridge (SB) structures in solution but charge-solvated (CS) motifsin the gas phase. Here, we report a study of non-covalent complexesof the protonated amino acid arginine, ArgH(+)(H2O)( ...

2023

Multiphysics model for assessing photoelectrochemical phenomena under concentrated irradiation

Sophia Haussener, Isaac Thomas Holmes-Gentle, Franky Esteban Bedoya Lora

A multiphysics model was developed for a photoelectrochemical (PEC) cell at the device level to simulate water splitting operating under concentrated irradiation (between 50 to 600 kW m−2). The 2D model couples charge, heat, mass, photon, and momentum tran ...

2023

Visualizing Chiral Interactions in Carbohydrates Adsorbed on Au(111) by High-Resolution STM Imaging

Klaus Kern, Stephan Rauschenbach, Uta Schlickum

Carbohydrates are the most abundant organic material on Earth and the structural "material of choice" in many living systems. Nevertheless, design and engineering of synthetic carbohydrate materials presently lag behind that for protein and nucleic acids. ...

Wiley-VCH Verlag GmbH2023

Spectral and thermodynamic properties of interacting electrons with dynamical functionals

Tommaso Chiarotti

Empowered by ever-increasing computational power and algorithmic developments, electronic-structure simulations continue to drive research and innovation in materials science. In this context, ab-initio calculations offer an unbiased platform for the under ...

EPFL2023

Assessing the persistence of chalcogen bonds in solution with neural network potentials

Anne-Clémence Corminboeuf, Rubén Laplaza Solanas, Veronika Juraskova, Frédéric Célerse

Non-covalent bonding patterns are commonly harvested as a design principle in the field of catalysis, supramolecular chemistry, and functional materials to name a few. Yet, their computational description generally neglects finite temperature and environme ...

2022

cell2mol: encoding chemistry to interpret crystallographic data

Anne-Clémence Corminboeuf, Rubén Laplaza Solanas, Sergio Vela Llausi, Yuri Cho

The creation and maintenance of crystallographic data repositories is one of the greatest data-related achievements in chemistry. Platforms such as the Cambridge Structural Database host what is likely the most diverse collection of synthesizable molecules ...

NATURE PORTFOLIO2022

Real space and reciprocal space investigations of the spin dynamics in skyrmion-hosting materials

Le Yu

Magnetic skyrmions are whirl-like spin configurations with particle-like properties protected by non-trivial topology. Due to their unique spin structures and dynamical properties, they have attracted tremendous interests over the past decade, from fundame ...

EPFL2022

Accurate and efficient band-gap predictions for metal halide perovskites at finite temperature

Alfredo Pasquarello, Patrick Gono, Thomas Bischoff, Haiyuan Wang

We develop a computationally efficient scheme to accurately determine finite-temperature band gaps for metal halide perovskites belonging to the class ABX(3) (A = Rb, Cs; B = Ge, Sn, Pb; and X = F, Cl, Br, I). First, an initial estimate of the band gap is ...

NATURE PORTFOLIO2022

Ultrafast Resonant Interatomic Coulombic Decay Induced by Quantum Fluid Dynamics

Marcel Drabbels, Andrew Daniel Bonnar Clark, Verónica Oliver Álvarez de Lara

Interatomic processes play a crucial role in weakly bound complexes exposed to ionizing radiation; therefore, gaining a thorough understanding of their efficiency is of fundamental importance. Here, we directly measure the timescale of interatomic Coulombi ...

American Physical Society2021

Atom-surface van der Waals potentials of topological insulators and semimetals from scattering measurements

Davide Campi

The phenomenology of resonant scattering has been known since the earliest experiments upon scattering of atomic beams from surfaces and is a means of obtaining experimental information about the fundamentals of weak adsorption systems in the van der Waals ...

2021

Transferable machine-learning models of complex materials: the case of GaAs

Giulio Imbalzano

Molecular simulations allow to investigate the behaviour of materials at the atomistic level, shedding light on phenomena that cannot be directly observed in experiments. Accurate results can be obtained with ab initio methods, while simulations of large-s ...

EPFL2021

A general and efficient framework for atomistic machine learning

Félix Benedito Clément Musil

Over the last two decades, many technological and scientific discoveries, ranging from the development of materials for energy conversion and storage through the design of new drugs, have been accelerated by the use of preliminary in silico experiments, to ...

EPFL2021

Modeling the Ga/As binary system across temperatures and compositions from first principles

Michele Ceriotti, Giulio Imbalzano

Materials composed of elements from the third and fifth columns of the periodic table display a very rich behavior, with the phase diagram usually containing a metallic liquid phase and a polar semiconducting solid. As a consequence, it is very hard to ach ...

AMER PHYSICAL SOC2021

Physics-enhanced machine learning with symmetry-adapted and long-range representations

Andrea Grisafi

Theoretical and computational approaches to the study of materials and molecules have, over the last few decades, progressed at an exponential rate. Yet, the possibility of producing numerical predictions that are on par with experimental measurements is t ...

EPFL2021

Extensive Benchmarking of DFT+U Calculations for Predicting Band Gaps

Iurii Timrov

Accurate computational predictions of band gaps are of practical importance to the modeling and development of semiconductor technologies, such as (opto)electronic devices and photoelectrochemical cells. Among available electronic-structure methods, densit ...

2021