Publications associées à Polarizable embedding with a multiconfiguration short-range density functional theory linear response method

Seebeck Coefficient of Ionic Conductors from Bayesian Regression Analysis

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

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

Data-Driven Control Synthesis using Koopman Operator: A Robust Approach

Alireza Karimi, Mert Eyuboglu, Nathan Russell Powell

This paper proposes a data-driven control design method for nonlinear systems that builds upon the Koopman operator framework. In particular, the Koopman operator is used to lift the nonlinear dynamics to a higher-dimensional space where the so-called obse ...

2024

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

Ursula Röthlisberger

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

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

Room-Temperature Quantum Optomechanics and Free-Electron Quantum Optics

Guanhao Huang

Quantum optics studies how photons interact with other forms of matter, the understanding of which was crucial for the development of quantum mechanics as a whole. Starting from the photoelectric effect, the quantum property of light has led to the develop ...

EPFL2024

Plasmonically enhanced molecular junctions for investigation of atomic-scale fluctuations in self-assembled monolayers

Sakthi Priya Amirtharaj

Molecular junctions represent a fascinating frontier in the realm of nanotechnology and are one of the smallest optoelectronic devices possible, consisting of individual molecules or a group of molecules that serve as the active element sandwiched between ...

EPFL2024

Valence can control the nonexponential viscoelastic relaxation of multivalent reversible gels

Hugo Camille Valentin Le Roy

Gels made of telechelic polymers connected by reversible cross-linkers are a versatile design platform for biocompatible viscoelastic materials. Their linear response to a step strain displays a fast, near-exponential relaxation when using low-valence cros ...

Amer Assoc Advancement Science2024

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

Nanomechanical resonators with low dissipation for quantum optomechanics

Alberto Beccari

Fields of technology as diverse as microwave filter construction, characterization of material interfaces with atomic precision, and detection of gravitational waves from astronomical sources employ mechanical resonators at their core. The utility of mecha ...

EPFL2023

Data-driven 1D wave propagation for site response analysis

Jean-François Molinari, Sacha Zenon Wattel, Antonio Joaquin Garcia Suarez

Prediction of ground motion triggered by earthquakes is a prime concern for both the seismology community and geotechnical earthquake engineering one. The subfield occupied with such a problem is termed site response analysis (SRA), its one-dimensional fla ...

WILEY2023

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

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

Achieving Optimal Performance With Data-Driven Frequency-Based Control Synthesis Methods

Alireza Karimi, Philippe Louis Schuchert

Frequency Response Function (FRF)-based control synthesis methods for Linear Time-Invariant (LTI) systems have been widely used in control theory and industry. Recently, there has been renewed interest in these methods, employing numerical optimization too ...

Ieee-Inst Electrical Electronics Engineers Inc2023

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

A squeezed mechanical oscillator with millisecond quantum decoherence

Tobias Kippenberg, Amir Youssefi, Mahdi Chegnizadeh, Shingo Kono

An enduring challenge in constructing mechanical-oscillator-based hybrid quantum systems is to ensure engineered coupling to an auxiliary degree of freedom and maintain good mechanical isolation from the environment, that is, low quantum decoherence, consi ...

NATURE PORTFOLIO2023

HP - A code for the calculation of Hubbard parameters using density-functional perturbation theory

Nicola Marzari, Matteo Cococcioni, Iurii Timrov

We introduce HP, an implementation of density-functional perturbation theory, designed to compute Hubbard parameters (on-site U and inter-site V ) in the framework of DFT+U and DFT+U+V. The code does not require the use of computationally expensive superce ...

ELSEVIER2022

Perimeter Modes of Nanomechanical Resonators Exhibit Quality Factors Exceeding 10(9) at Room Temperature

Tobias Kippenberg, Sergey Fedorov, Nils Johan Engelsen, Alberto Beccari, Amirali Arabmoheghi, Guanhao Huang

Systems with low mechanical dissipation are extensively used in precision measurements such as gravitational wave detection, atomic force microscopy, and quantum control of mechanical oscillators via optomechanics and electromechanics. The mechanical quali ...

American Physical Society2022

Label-Free C-Reactive Protein Si Nanowire FET Sensor Arrays With Super-Nernstian Back-Gate Operation

Mihai Adrian Ionescu, Yann Christophe Sprunger, Luca Capua, Ron Gill, Aristea Grammoustianou, Felix Risch

We present a CMOS-compatible double gate and label-free C-reactive protein (CRP) sensor, based on silicon on insulator (SOI) silicon nanowires arrays. We exploit a reference subtracted detection method and a super-Nernstian internal amplification given by ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022