Publications associées à QMMMW: A wrapper for QM/MM simulations with QUANTUM ESPRESSO and LAMMPS

Publications associées (36)

zkSNARKs in the ROM with Unconditional UC-Security

The universal composability (UC) framework is a “gold standard” for security in cryptography. UC-secure protocols achieve strong security guarantees against powerful adaptive adversaries, and retain these guarantees when used as part of larger protocols. Z ...

Springer Science and Business Media Deutschland GmbH2025

Oxidative Defect Detection Within Free and Packed DNA Systems: A Quantum Mechanical/Molecular Mechanics (QM/ MM) Approach

Ursula Röthlisberger, Sophia Kathryn Johnson

Base excision repair enzymes (BERs) detect and repair oxidative DNA damage with efficacy despite the small size of the defects and their often only minor structural impact. A charge transfer (CT) model for rapid scanning of DNA stretches has been evoked to ...

Swiss Chemical Soc2024

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

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

Machine learning-aided generative molecular design

Philippe Schwaller, Jeff Guo

Machine learning has provided a means to accelerate early-stage drug discovery by combining molecule generation and filtering steps in a single architecture that leverages the experience and design preferences of medicinal chemists. However, designing mach ...

Nature Portfolio2024

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

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

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

High-order geometric integrators for the variational Gaussian wavepacket dynamics and application to vibronic spectra at finite temperature

Roya Moghaddasi Fereidani

Molecular quantum dynamics simulations are essential for understanding many fundamental phenomena in physics and chemistry. They often require solving the time-dependent Schrödinger equation for molecular nuclei, which is challenging even for medium-sized ...

EPFL2024

DBFS: Dynamic Bitwidth-Frequency Scaling for Efficient Software-defined SIMD

Giovanni Ansaloni, Alexandre Sébastien Julien Levisse, Flavio Ponzina, Pengbo Yu

Machine learning algorithms such as Convolutional Neural Networks (CNNs) are characterized by high robustness towards quantization, supporting small-bitwidth fixed-point arithmetic at inference time with little to no degradation in accuracy. In turn, small ...

IEEE2024

Exciton migration in two-dimensional materials

Giovanni Consalvo Cistaro

Excitons play an essential role in the optical response of two-dimensional materials. These are bound states showing up in the band gaps of many-body systems and are conceived as quasiparticles formed by an electron and a hole. By performing real-time simu ...

Nature Portfolio2024

Highly Parallel RTL Simulation

Seyedmahyar Emami

Verification and testing of hardware heavily relies on cycle-accurate simulation of RTL. As single-processor performance is growing only slowly, conventional, single-threaded RTL simulation is becoming impractical for increasingly complex chip designs and ...

EPFL2024

Lightcone Modular Bootstrap and Tauberian Theory: A Cardy-Like Formula for Near-Extremal Black Holes

Jiaxin Qiao

We show that for a unitary modular invariant 2D CFT withcentral charge c >1 and having a nonzero twist gap in the spectrum ofVirasoro primaries, for sufficiently large spinJ, there always exist spin-Joperators with twist falling in the interval (c-1\12 -ep ...

Cham2024

2023 Roadmap on molecular modelling of electrochemical energy materials

Alfredo Pasquarello, Chunmin Zhang, Assil Bouzid

New materials for electrochemical energy storage and conversion are the key to the electrification and sustainable development of our modern societies. Molecular modelling based on the principles of quantum mechanics and statistical mechanics as well as em ...

Iop Publishing Ltd2023

Weighted Matching in the Random-Order Streaming and Robust Communication Models

Diba Hashemi

We study the maximum weight matching problem in the random-order semi-streaming model and in the robust communication model. Unlike many other sublinear models, in these two frameworks, there is a large gap between the guarantees of the best known algorith ...

Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing2024

The role of Zn in C-S-H atomic structure, nucleation and growth

Anna Morales Melgares

The most promising solution towards cementitious materials with a lower carbon footprint is the partial substitution of the clinker by supplementary cementitious materials (SCMs) such as fly ash, blast furnace slag, limestone and calcined clays. The produc ...

EPFL2023

Coupled Rotary and Oscillatory Motion in a Second-Generation Molecular Motor Pd Complex

Lukas Pfeifer

Molecular machines offer many opportunities for the development of responsive materials and introduce autono-mous motion in molecular systems. While basic molecular switches and motors carry out one type of motion upon being exposed to an external stimulus ...

AMER CHEMICAL SOC2023

Magnetostriction-Driven Muon Localization in an Antiferromagnetic Oxide

Nicola Marzari, Iurii Timrov, Lorenzo Monacelli

Magnetostriction results from the coupling between magnetic and elastic degrees of freedom. Though it is associated with a relatively small energy, we show that it plays an important role in determining the site of an implanted muon, so that the energetica ...

Amer Physical Soc2024

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

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