Publications associées à Reproducibility in density functional theory calculations of solids

Efficient and insightful descriptors for representing molecular and material space

Data-driven approaches have been applied to reduce the cost of accurate computational studies on materials, by using only a small number of expensive reference electronic structure calculations for a representative subset of the materials space, and using ...

EPFL2024

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

Orbital-Resolved DFT plus U for Molecules and Solids

Nicola Marzari, Iurii Timrov, Eric Macke

We present an orbital-resolved extension of the Hubbard U correction to density-functional theory (DFT). Compared to the conventional shell-averaged approach, the prediction of energetic, electronic and structural properties is strongly improved, particula ...

Amer Chemical Soc2024

A Generalized Adjusted Min-Sum Decoder for 5G LDPC Codes: Algorithm and Implementation

Andreas Peter Burg, Alexios Konstantinos Balatsoukas Stimming, Yifei Shen, Yuqing Ren, Hassan Harb

5G New Radio (NR) has stringent demands on both performance and complexity for the design of low-density parity-check (LDPC) decoding algorithms and corresponding VLSI implementations. Furthermore, decoders must fully support the wide range of all 5G NR bl ...

Ieee-Inst Electrical Electronics Engineers Inc2024

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

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

Predicting Ion Diffusion from the Shape of Potential Energy Landscapes

Berend Smit, Senja Dominique Barthel, Amber Kashan Mace

We present an efficient method to compute diffusion coefficients of multiparticle systems with strong interactions directly from the geometry and topology of the potential energy field of the migrating particles. The approach is tested on Li-ion diffusion ...

Amer Chemical Soc2023

Towards high-throughput many-body perturbation theory: efficient algorithms and automated workflows

Giovanni Pizzi, Antimo Marrazzo, Miki Bonacci, Junfeng Qiao, Andrea Ferretti

The automation of ab initio simulations is essential in view of performing high-throughput (HT) computational screenings oriented to the discovery of novel materials with desired physical properties. In this work, we propose algorithms and implementations ...

NATURE PORTFOLIO2023

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

Murunskite - a new class of functional material

Davor Tolj

The subject of the present work is discovery and in-depth characterization of a new class of functional materials. Tuning of the bond polarity and orbital occupation with a goal of establishing balance between localization and delocalization of electrons - ...

EPFL2023

Modeling and characterization of the nucleation and growth of carbon nanostructures in physical synthesis

Kevin Rossi

Carbon nanostructures formed through physical synthesis come in a variety of sizes and shapes. With the end goal of rationalizing synthetic pathways of carbon nanostructures as a function of tunable parameters in the synthesis, we investigate how the initi ...

ELSEVIER2023

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

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

Microscopic picture of paraelectric perovskites from structural prototypes

Nicola Marzari, Giovanni Pizzi, Boris Kozinsky, Michele Kotiuga

We highlight with first-principles molecular dynamics the persistence of intrinsic < 111 > Ti off-centerings for BaTiO3 in its cubic paraelectric phase. Intriguingly, these are inconsistent with the Pm (3) over barm space group often used to atomistically ...

AMER PHYSICAL SOC2022

Spectral properties of extended systems from Koopmans-compliant functionals

Riccardo De Gennaro

Electronic-structure simulations have been impacting the study of materials properties thanks to the simplicity of density-functional theory, a method that gives access to the ground state of the system. Although very important, ground-state properties rep ...

EPFL2022

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

Koopmans Spectral Functionals in Periodic Boundary Conditions

Nicola Marzari, Nicola Colonna, Riccardo De Gennaro, Edward Baxter Linscott

Koopmans spectral functionals aim to describe simultaneously ground-state properties and charged excitations of atoms, molecules, nanostructures, and periodic crystals. This is achieved by augmenting standard density functionals with simple but physically ...

AMER CHEMICAL SOC2022

Efficient implementation of atom-density representations

Till Junge, Félix Benedito Clément Musil, Michele Ceriotti, Michael John Willatt, Max David Veit, Alexander Jan Goscinski, Guillaume André Jean Fraux

Physically motivated and mathematically robust atom-centered representations of molecular structures are key to the success of modern atomistic machine learning. They lie at the foundation of a wide range of methods to predict the properties of both materi ...

2021

Azole-Based Indoleamine 2,3-Dioxygenase 1 (IDO1) Inhibitors

Pierre Vogel, Olivier Michielin, Florence Pojer, Somi Reddy Majjigapu, George Coukos

The heme enzyme indoleamine 2,3-dioxygenase 1 (IDO1) plays an essential role in immunity, neuronal function, and aging through catalysis of the rate-limiting step in the kynurenine pathway of tryptophan metabolism. Many IDO1 inhibitors with different chemo ...

AMER CHEMICAL SOC2021

Ab Initio Electron-Phonon Interactions in Correlated Electron Systems

Nicola Marzari, Matteo Cococcioni, Iurii Timrov, Andrea Floris

Electron-phonon (e-ph) interactions are pervasive in condensed matter, governing phenomena such as transport, superconductivity, charge-density waves, polarons, and metal-insulator transitions. First-principles approaches enable accurate calculations of e- ...

AMER PHYSICAL SOC2021