Publications associées à Performance of optimized atom-centered potentials for weakly bonded systems using density functional theory

Publications associées (41)

Lagnet: Better Electron Density Prediction for Lcao-based Data and Drug-like Substances

The electron density is an important object in quantum chemistry that is crucial for many downstream tasks in drug design. Recent deep learning approaches predict the electron density around a molecule from atom types and atom positions. Most of these meth ...

BMC2025

Cooperative promotion of electroreduction of CO to n-propanol by *CO enrichment and proton regulation

Jie Zhang

The CO2/CO electroreduction reaction (CO2RR/CORR) to liquid products presents an enticing pathway to store intermittent renewable electricity. However, the selectivity for desirable high-value C3 products, such as n-propanol, remains unsatisfactory in the ...

ROYAL SOC CHEMISTRY2025

Supramolecular Polymer Brushes Grafted via Atom Transfer Radical Polymerization from Surfaces Presenting Non-covalent, Host-Guest Complex-Based Initiators

Harm-Anton Klok, Friederike Katharina Metze

This paper describes the synthesis of supramolecular polymer brushes via surface-initiated polymerization from adamantane-functionalized initiators that are noncovalently bound to beta-cyclodextrin- or cucurbit[7]uril-modified substrates. Surface-initiated ...

American Chemical Society2025

Electron beam-based direct writing of nanostructures using a palladium β-ketoesterate complex

Chinmai Sai Jureddy, Patrik Willi Hoffmann

Gas-assisted focused electron beam-induced deposition (FEBID) as a direct, minimally invasive 3D nanopatterning tool offers many advantages in making nanostructures with complex shapes and novel compositions for evolving nanotechnological applications. In ...

BEILSTEIN-INSTITUT2025

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

Chalcogen bonding catalysis

Jieping Zhu

Catalysts play a major role in chemical synthesis, and catalysis is considered to be a green and economic process. Catalysis is dominated by covalent interactions between the catalyst and substrate. The design of non-covalent catalysts came into limelight ...

Royal Society of Chemistry2024

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

Dynamics of K2Ni2(SO4)3 governed by proximity to a 3D spin liquid model

Henrik Moodysson Rønnow, Arnaud Magrez, Ivica Zivkovic, Jian Rui Soh, Aman Sharma, Virgile Yves Favre

Quantum spin liquids (QSLs) have become a key area of research in magnetism due to their remarkable properties, such as long-range entanglement, fractional excitations, and topologically protected phenomena. Recently, the search for QSLs has expanded into ...

Nature Research2024

The energy landscape of magnetic materials

Nicola Marzari, Louis Maurice Ponet, Enrico Di Lucente

Magnetic materials can display many solutions to the electronic-structure problem, corresponding to different local or global minima of the energy functional. In Hartree-Fock or density-functional theory different single-determinant solutions lead to diffe ...

2024

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

A Cavity-Microscope for Quantum Simulations with Locally-Controllable All-to-All Interactions

Nick Jacob Sauerwein

This thesis presents the development, construction, and benchmark of an experimental platform that combines cold fermionic 6Li atoms with locally controllable light-matter interactions. To enable local control, a new device, the cavity-microscope, was crea ...

EPFL2024

Electronic Excited States from Physically Constrained Machine Learning

Michele Ceriotti, Jigyasa Nigam, Divya Suman

Data-driven techniques are increasingly used to replace electronic-structure calculations of matter. In this context, a relevant question is whether machine learning (ML) should be applied directly to predict the desired properties or combined explicitly w ...

2024

Magnetism of Single Surface Adsorbed Atoms Studied with Radio-Frequency STM

Clément Marie Soulard

This thesis investigates the magnetic properties of single atoms and molecules adsorbed on thin magnesium oxide decoupling layers, grown on a silver single crystal. To address these systems experimentally, we use a low temperature scanning tunneling micros ...

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

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

Ab-initio variational wave functions for the time-dependent many-electron Schrödinger equation

Giuseppe Carleo, Jannes Willy E. Nys, Gabriel Maria Pescia, Alessandro Sinibaldi

Understanding the real-time evolution of many-electron quantum systems is essential for studying dynamical properties in condensed matter, quantum chemistry, and complex materials, yet it poses a significant theoretical and computational challenge. Our wor ...

Nature Research2024

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

Range Separation of the Interaction Potential in Intermolecular and Intramolecular Symmetry-Adapted Perturbation Theory

Anne-Clémence Corminboeuf

Symmetry-adapted perturbation theory (SAPT) is a popular and versatile tool to compute and decompose noncovalent interaction energies between molecules. The intramolecular SAPT (ISAPT) variant provides a similar energy decomposition between two nonbonded f ...

2024

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

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