Publications associées à Structure-Correlation Principles Connecting Ground State Properties and Reaction Barrier Heights for the Cope Rearrangement of Semibullvalenes

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

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

Multi-machine benchmark of the self-consistent 1D scrape-off layer model DIV1D from stagnation point to target with SOLPS-ITER

Holger Reimerdes

This paper extends a 1D dynamic physics-based model of the scrape-off layer (SOL) plasma, DIV1D, to include the core SOL and possibly a second target. The extended model is benchmarked on 1D mapped SOLPS-ITER simulations to find input settings for DIV1D th ...

Iop Publishing Ltd2024

Machine-learning the electronic density of states: electronic properties without quantum mechanics

Chiheb Ben Mahmoud

The electronic density of states (DOS) quantifies the distribution of the energy levels that can be occupied by electrons in a quasiparticle picture and is central to modern electronic structure theory. It also underpins the computation and interpretation ...

EPFL2023

A recipe for cracking the quantum scaling limit with machine learned electron densities

Mario Geiger

A long-standing goal of science is to accurately simulate large molecular systems using quantum mechanics. The poor scaling of current quantum chemistry algorithms on classical computers, however, imposes an effective limit of about a few dozen atoms on tr ...

IOP Publishing Ltd2023

Advancing Computational Chemistry with Stochastic and Artificial Intelligence Approaches

Justin Villard

Computational chemistry aims to simulate reactions and molecular properties at the atomic scale, advancing the design of novel compounds and materials with economic, environmental, and societal implications. However, the field relies on approximate quantum ...

EPFL2023

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

Alfredo Pasquarello, Patrick Gono, Thomas Bischoff, Aleksei Tal, 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

Polarons free from many-body self-interaction in density functional theory

Alfredo Pasquarello, Stefano Falletta

We develop a unified theoretical framework encompassing one-body and many-body forms of self-interaction. We find an analytic expression for both the one-body and the many-body self-interaction energies, and quantitatively connect the two expressions throu ...

2022

Intrinsic Polarization Super Junctions: Design of Single and Multichannel GaN Structures

Elison de Nazareth Matioli, Catherine Erine, Luca Nela, Amirmohammad Miran Zadeh

Super junctions (SJs) have enabled unprecedented performance in Silicon power devices, which could be further improved by applying this concept to wide bandgap semiconductors like gallium nitride (GaN). Currently, polarization super junctions (PSJs) are th ...

2022

Impact of quantum-chemical metrics on the machine learning prediction of electron density

Anne-Clémence Corminboeuf, Alberto Fabrizio, Ksenia Briling

Machine learning (ML) algorithms have undergone an explosive development impacting every aspect of computational chemistry. To obtain reliable predictions, one needs to maintain a proper balance between the black-box nature of ML frameworks and the physics ...

AMER INST PHYSICS2021

Multi-scale approach for the prediction of atomic scale properties

Michele Ceriotti, Andrea Grisafi, Jigyasa Nigam

Electronic nearsightedness is one of the fundamental principles that governs the behavior of condensed matter and supports its description in terms of local entities such as chemical bonds. Locality also underlies the tremendous success of machine-learning ...

2021

Core-Valence Attosecond Transient Absorption Spectroscopy of Polyatomic Molecules

Jiri Vanicek, Nikolay Golubev

Tracing ultrafast processes induced by interaction of light with matter is often very challenging. In molecular systems, the initially created electronic coherence becomes damped by the slow nuclear rearrangement on a femtosecond timescale which makes real ...

2021

Learning the electronic density of states in condensed matter

Michele Ceriotti, Andrea Anelli, Chiheb Ben Mahmoud

The electronic density of states (DOS) quantifies the distribution of the energy levels that can be occupied by electrons in a quasiparticle picture and is central to modern electronic structure theory. It also underpins the computation and interpretation ...

AMER PHYSICAL SOC2020

Learning (from) the Electron Density: Transferability, Conformational and Chemical Diversity

Anne-Clémence Corminboeuf, Alberto Fabrizio, Andrea Grisafi, Ksenia Briling

Machine-learning in quantum chemistry is currently booming, with reported applications spanning all molecular properties from simple atomization energies to complex mathematical objects such as the many-body wavefunction. Due to its central role in density ...

2020

The ONETEP linear-scaling density functional theory program

Edward Baxter Linscott

We present an overview of the onetep program for linear-scaling density functional theory (DFT) calculations with large basis set (plane-wave) accuracy on parallel computers. The DFT energy is computed from the density matrix, which is constructed from spa ...

AMER INST PHYSICS2020

Magnetic exchange interactions in monolayer CrI3 from many-body wavefunction calculations

Oleg Yazyev, Michele Pizzochero, Ravi Yadav

The marked interplay between the crystalline, electronic, and magnetic structure of atomically thin magnets has been regarded as the key feature for designing next-generation magneto-optoelectronic devices. In this respect, a detailed understanding of the ...

IOP PUBLISHING LTD2020

Application of Thomson scattering to helicon plasma sources

Patrick Blanchard, Alan Howling, Ivo Furno, Yanis Andrebe, Alban Sublet, Rémy Jacquier, Riccardo Agnello

The possibility of performing electron density and temperature measurements in a high power helicon plasma is a crucial issue in the framework of the AWAKE (Advanced WAKefield Experiment) project, which demonstrates acceleration of particles using GeV m(-1 ...

Cambridge University Press2020

Functional Extrapolations to Tame Unbound Anions in Density-Functional Theory Calculations

Nicola Marzari, Oliviero Andreussi, Francesco Nattino

Standard flavors of density-functional theory (DFT) calculations are known to fail in describing anions, due to large self-interaction errors. The problem may be circumvented using localized basis sets of reduced size, leaving no variational flexibility fo ...

AMER CHEMICAL SOC2019

Building a Consistent and Reproducible Database for Adsorption Evaluation in Covalent-Organic Frameworks

Aliaksandr Yakutovich, Berend Smit, Daniele Ongari, Christoph Leopold Talirz

We present a workflow that traces the path from the bulk structure of a crystalline material to assessing its performance in carbon capture from coal's postcombustion flue gases. This workflow is applied to a database of 324 covalent-organic frameworks (CO ...

2019

Electron density learning of non-covalent systems

Anne-Clémence Corminboeuf, Alberto Fabrizio, Michele Ceriotti, Andrea Grisafi, Benjamin André René Meyer

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 ...

2019

Phonon origin and lattice evolution in charge density wave states

Helmuth Berger

Metallic transition metal dichalcogenides, such as tantalum diselenide (TaSe2), display quantum correlated phenomena of superconductivity and charge density waves (CDWs) at low temperatures. Here, the photophysics of 2H-TaSe2 during CDW transitions is reve ...

AMER PHYSICAL SOC2019