Publications associées à Implicit solvation

Solvation Free Energies from Machine Learning Molecular Dynamics

Nicola Marzari, Nicéphore Arthur François Bonnet

The present work proposes an extension to the approach of [Xi, C; et al. J. Chem. Theory Comput. 2022, 18, 6878] to calculate ion solvation free energies from first-principles (FP) molecular dynamics (MD) simulations of a hybrid solvation model. The approa ...

Amer Chemical Soc2024

A continuum approximation approach to the depot location problem in a crowd-shipping system

Nikolaos Geroliminis, Patrick Stefan Adriaan Stokkink

Last-mile delivery in the logistics chain contributes to congestion in urban networks due to frequent stops. Crowd-shipping is a sustainable and low-cost alternative to traditional delivery but relies heavily on the availability of occasional couriers. In ...

PERGAMON-ELSEVIER SCIENCE LTD2023

Effects of surface wettability on (001)-WO3 and (100)-WSe2: A spin-polarized DFT-MD study

Kevin Sivula, Rangsiman Ketkaew

An extensive understanding of WO3 and WSe2 bulk crystalline structures and explicit solvent effects on (001)-WO3 and (100)-WSe2 facets are essential for design of efficient (photo) electrocatalysts. The atomistic level understanding of both WO(3 )and WSe2 ...

ELSEVIER2022

Modeling non-covalent interactions in condensed phase

Veronika Juraskova

The modeling of non-covalent interactions, solvation effects, and chemical reactions in complex molecular environment is a challenging task. Current state-of-the-art approaches often rely on static computations using implicit solvent models and harmonic ap ...

EPFL2022

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

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

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

High-Throughput Nanopore Fabrication and Classification Using Xe-Ion Irradiation and Automated Pore-Edge Analysis

Aleksandra Radenovic, Andras Kis, Martina Lihter, Mukesh Kumar Tripathi, Mukeshchand Thakur, Sanjin Marion, Michal Daniel Macha

Large-area nanopore drilling is a major bottleneck in state-of-the-art nanoporous 2D membrane fabrication protocols. In addition, high-quality structural and statistical descriptions of as-fabricated porous membranes are key to predicting the corresponding ...

AMER CHEMICAL SOC2022

On the durability of surgical masks after simulated handling and wear

Véronique Michaud, Vincent Marc Varanges, Jian Wang, Baris Çaglar, Yann Albert Gérard Lebaupin, René M. Rossi

After the spread of COVID-19, surgical masks became highly recommended to the public. They tend to be handled and used multiple times, which may impact their performance. To evaluate this risk, surgical masks of Type IIR were submitted to four simulated tr ...

Nature Research2022

Machine Learning-Guided Approach for Studying Solvation Environments

Sandip De, Yasemin Basdogan

Molecular-level understanding and characterization of solvation environments are often needed across chemistry, biology, and engineering. Toward practical modeling of local solvation effects of any solute in any solvent, we report a static and all-quantum ...

AMER CHEMICAL SOC2020

Simulating Solvation and Acidity in Complex Mixtures with First-Principles Accuracy: The Case of CH3SO3H and H2O2 in Phenol

Michele Ceriotti, Anne-Clémence Corminboeuf, Kevin Rossi, Veronika Juraskova

We present a generally applicable computational framework for the efficient and accurate characterization of molecular structural patterns and acid properties in an explicit solvent using H2O2 and CH3SO3H in phenol as an example. To address the challenges ...

AMER CHEMICAL SOC2020

Hamiltonian-Reservoir Replica Exchange and Machine Learning Potentials for Computational Organic Chemistry

Anne-Clémence Corminboeuf, Alberto Fabrizio, Benjamin André René Meyer, Raimon Fabregat I De Aguilar-Amat, Daniel Hollas

This work combines a machine learning potential energy function with a modular enhanced sampling scheme to obtain statistically converged thermodynamical properties of flexible medium-size organic molecules at high ab initio level. We offer a modular envir ...

AMER CHEMICAL SOC2020

Prediction of aqueous free energies of solvation using coupled QM and MM explicit solvent simulations

Jeremy Samuel Arey, Daniel David Sadowsky

A method based on molecular dynamics simulations which employ two distinct levels of theory is proposed and tested for the prediction of Gibbs free energies of solvation for non-ionic solutes in water. The method consists of two additive contributions: (i) ...

ROYAL SOC CHEMISTRY2020

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

Role of OH Intermediates during the Au Oxide Electro-Reduction at Low pH Elucidated by Electrochemical Surface-Enhanced Raman Spectroscopy and Implicit Solvent Density Functional Theory

Nicola Marzari, Francesco Nattino

Molecular understanding of the electrochemical oxidation of metals and the electro-reduction of metal oxides is of pivotal importance for the rational design of catalyst-based devices where metal(oxide) electrodes play a crucial role. Operando monitoring a ...

AMER CHEMICAL SOC2020

Effect of solute-solute interactions on strengthening of random alloys from dilute to high entropy alloys

William Curtin, Shankha Nag

The yield strength of random metal alloys, i.e. alloys with random occupation of the crystalline lattice sites by the elemental constituent atoms all considered as solutes, is primarily understood as controlled by solute/dislocation interactions. Solute-so ...

PERGAMON-ELSEVIER SCIENCE LTD2020

Modelling long-range interactions in multiscale simulations of ferromagnetic materials

Doghonay Arjmand

Atomistic-continuum multiscale modelling is becoming an increasingly popular tool for simulating the behaviour of materials due to its computational efficiency and reliable accuracy. In the case of ferromagnetic materials, the atomistic approach handles th ...

SPRINGER2020

Accelerating materials discovery for solid state electrolytes

Matthieu Gilles Mottet

The development of new solid-state electrolytes is a key step in improving the performance and safety of battery technology. Although the use of first-principle methods has proved invaluable in better understanding the process at play in these materials, ...

EPFL2020

Absolute band alignment at semiconductor-water interfaces using explicit and implicit descriptions for liquid water

Alfredo Pasquarello, Nicola Marzari, Francesco Ambrosio, Oliviero Andreussi, Zhendong Guo

Quantum mechanical simulations that include the effects of the liquid environment are highly relevant for the characterization of solid-liquid interfaces, which is crucial for the design of a wide range of devices. In this work we present a rigorous and sy ...

2019

Solvent-Aware Interfaces in Continuum Solvation

Nicola Marzari, Oliviero Andreussi, Francesco Nattino, Nicolas Georg Hörmann

Continuum models to handle solvent and electrolyte effects in an effective way have a long tradition in quantum-chemistry simulations and are nowadays also being introduced in computational condensed-matter and materials simulations. A key ingredient of co ...

AMER CHEMICAL SOC2019

Grand canonical simulations of electrochemical interfaces in implicit solvation models

Nicola Marzari, Oliviero Andreussi, Nicolas Georg Hörmann

We discuss grand canonical simulations based on density-functional theory to study the thermodynamic properties of electrochemical interfaces of metallic electrodes in aqueous environments. Water is represented using implicit solvation, here via the self-c ...

AMER INST PHYSICS2019

Applications of Artificial Intelligence to Computational Chemistry

Nicholas John Browning

The calculation of the electronic structure of chemical systems, necessitates computationally expensive approximations to the time-independent electronic Schrödinger equation in order to yield static properties in good agreement with experimental results. ...

EPFL2019