Publications associées à Thermomechanical properties of honeycomb lattices from internal-coordinates potentials: the case of graphene and hexagonal boron nitride

Publications associées (39)

2D Metalorganic Ferromagnets

Diego Radillo Ochoa, Céline Hensky, Christian Wäckerlin, Quy Hien Le

Low-dimensional materials exhibiting stable magnetic ordering are interesting from a fundamental point of view as well as for future application in information technologies. Metalorganic magnets, created by linking metal atoms with specific organic molecul ...

WILEY2025

Engineering Spin Interaction Channels of FePc on Au(111)

Wolf-Dieter Schneider

We demonstrate the reversible control of interactions between a local molecular spin, hosted within an iron phthalocyanine (FePc) molecule, and the conduction electrons of a supporting Au(111) surface. Using the tip of a scanning tunneling microscope, we d ...

American Chemical Society (ACS)2025

The Chemical Nature of the Oxide Directs the Stability and Reactivity of Copper|Oxide Interfaces in the Electrochemical CO2 Reduction Reaction

Raffaella Buonsanti, Petru Pasquale Albertini, Jari Leemans, Coline Marie Agathe Boulanger, Krishna Kumar

Understanding the impact of composition and interfaces between metals and oxides is a goal of interest for many chemical reactions. Herein, we propose a framework to map correlations between the electrochemical behavior of the oxide and the stability and r ...

American Chemical Society (ACS)2025

Machine-learned interatomic potentials: Recent developments and prospective applications

William Curtin

High-throughput generation of large and consistent ab initio data combined with advanced machine-learning techniques are enabling the creation of interatomic potentials of near ab initio quality. This capability has the potential of dramatically impacting ...

Springer Heidelberg2023

Universal machine learning for the response of atomistic systems to external fields

Yaolong Zhang

Machine learned interatomic interaction potentials have enabled efficient and accurate molecular simulations of closed systems. However, external fields, which can greatly change the chemical structure and/or reactivity, have been seldom included in curren ...

Nature Portfolio2023

Predicting Ion Diffusion from the Shape of Potential Energy Landscapes

Berend Smit, Senja Dominique Barthel

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

Efficient and insightful descriptors for representing molecular and material space

Alexander Jan Goscinski

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

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

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

Thermal transport of glasses via machine learning driven simulations

Federico Grasselli, Paolo Pegolo

Accessing the thermal transport properties of glasses is a major issue for the design of production strategies of glass industry, as well as for the plethora of applications and devices where glasses are employed. From the computational standpoint, the che ...

Frontiers Media Sa2024

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

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

Kevin Rossi

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

High throughput wide field second harmonic imaging of giant unilamellar vesicles

Sylvie Roke, Maksim Eremchev, David Roesel, Pierre-Marc Jean Marie Dansette

Cell-sized giant unilamellar vesicles (GUVs) are an ideal tool for understanding lipid membrane structure and properties. Label-free spatiotemporal images of their membrane potential and structure would greatly aid the quantitative understanding of membran ...

AIP Publishing2023

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

Integrated chirped photonic-crystal cavities in gallium phosphide for broadband soliton generation

Tobias Kippenberg, Johann Emmeram Riemensberger, Miles Henry Anderson, Nikolai Kuznetsov, Alisa Davydova

Chirped mirrors have underpinned advances in ultra-fast lasers based on bulk optics but have yet to be fully exploited in integrated photonics, where they could provide a means to engineer otherwise unattainable dispersion profiles for a range of nonlinear ...

2024

Advancing first principle-based molecular dynamics of biological systems with machine learning

François Louis Mouvet

Molecular dynamics (MD) simulations have emerged as a transformative approach to analyse molecular systems at the atomic level, offering valuable insights into complex biological processes. Many biological phenomena can only accurately be described by inco ...

EPFL2023

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

The OpenMolcas Web: A Community-Driven Approach to Advancing Computational Chemistry

Francesco Aquilante

The developments of the open-source OpenMolcas chemistry software environment since spring 2020 are described, with a focus on novel functionalities accessible in the stable branch of the package or via interfaces with other packages. These developments sp ...

Washington2023

Effects of thermal, mechanical, and electrostatic perturbations on lipid membrane hydration investigated by second harmonic imaging

Seonwoo Lee

Hydrated lipid bilayer membranes are crucial components of cells and organelles, serving as the outer boundary that separates the cellular components from the extracellular environment. Lipid membranes regulate their structures and functions by dynamically ...

EPFL2023

Structure and dynamics of liquid water from ab initio simulations: adding Minnesota density functionals to Jacob's ladder

Ursula Röthlisberger, Martin Peter Bircher, Justin Villard

The accurate representation of the structural and dynamical properties of water is essential for simulating the unique behavior of this ubiquitous solvent. Here we assess the current status of describing liquid water using ab initio molecular dynamics, wit ...

Royal Soc Chemistry2024