Publication

Ab initio-driven trajectory-based nuclear quantum dynamics in phase space

Publications associées (31)

Comparing transferability in neural network approaches and linear models for machine-learning interaction potentials

Atomic simulations using machine learning interatomic potential (MLIP) have gained a lot of popularity owing to their accuracy in comparison to conventional empirical potentials. However, the transferability of MLIP to systems outside the training set pose ...

AMER PHYSICAL SOC2023

Tuning the reactivity of uranium towards small molecules in multimetallic complexes

Nadir Jori

One of the main goals of organometallic chemistry in the last decades was the activation of small molecule in mild reaction conditions. Even though multiple examples of catalytic cycles able to produce fine chemicals from cheap and abundant sources using t ...

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

NMR Crystallography in the Big Data Era: New Methods and Applications Powered by Machine Learning

Manuel Cordova

Structure determination of materials is key to understanding their physical properties. While single-crystal X-ray diffraction is the gold standard for structures displaying long-range order, many materials of interest are polycrystalline and/or disordered ...

EPFL2023

DFT plus U-type functional derived to explicitly address the flat plane condition

Edward Baxter Linscott

A DFT+U-type corrective functional is derived from first principles to enforce the flat plane condition on localized subspaces, thus dispensing with the need for an ad hoc derivation from the Hubbard model. Small, molecular test systems at the dissociated ...

AMER PHYSICAL SOC2023

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

Two antagonistic response regulators control Pseudomonas aeruginosa polarization during mechanotaxis

Lorenzo Anton-Louis Talà, Alexandre Louis André Persat, Xavier Jean-Yves Pierrat, Marco Julian Kühn, Joanne Netter Engel

The opportunistic pathogen Pseudomonas aeruginosa adapts to solid surfaces to enhance virulence and infect its host. Type IV pili (T4P), long and thin filaments that power surface-specific twitching motility, allow single cells to sense surfaces and contro ...

WILEY2023

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

Bridging Native and Intrinsic Structures of Microhydrated Biomolecules by Cold Ion Spectroscopy

Andrei Zviagin

Solving native structures of such large molecules, like biomolecules, is often challenging, particularly due to the potentially infinite number of non-covalent interactions with water. In this thesis, we report the use of cold ion gas-phase action spectros ...

EPFL2023

Computer-implemented design of peptide:receptor signaling complexes for enhanced chemotaxis

Patrick Daniel Barth, Robert Everett Jefferson

The present invention relates to a computer-implemented method for engineering the interaction between a protein and a cognate peptide that are capable of forming a molecular complex, wherein the method comprises (a) preparing in silico a library of test p ...

2023

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