Publications associées à Nuclear Quantum Effects in H+ and OH- Diffusion along Confined Water Wires

Room-Temperature Quantum Optomechanics and Free-Electron Quantum Optics

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

Membrane electrode assembly simulation of anion exchange membrane water electrolysis

Jan Van Herle, Zoé Mury, Suhas Nuggehalli Sampathkumar, Khaled Lawand

Anion exchange membrane water electrolysis (AEMWE) offers a green hydrogen production method that eliminates the need for platinum group metals (PGM) as electrocatalysts. This study employs a COMSOL (R) 6.0 model to simulate a 1x1 cm(2) Ni fibre - Raney (R ...

Elsevier2024

Membrane specificity of the human cholesterol transfer protein STARD4

Charlotte Julie Caroline Gehin

STARD4 regulates cholesterol homeostasis by transferring cholesterol between the plasma membrane and endoplasmic reticulum. The STARD4 structure features a helix-grip fold surrounding a large hydrophobic cavity holding the sterol. Its access is controlled ...

Academic Press Ltd- Elsevier Science Ltd2024

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

Advancements in Nanomechanical Characterization and Biomolecular Imaging with Atomic force Microscopy

Veronika Cencen

Atomic force microscopy (AFM) is a widely used imaging tool for obtaining a variety of information for a range of samples. Although it was initially intended to serve as a method of observing very flat solid surfaces, its use expanded into several other fi ...

EPFL2024

From Surfactants to 3D Printing: How Ion-Chelator Pair Interactions Affect the Mechanical Properties of Bioinspired Materials

Gaia De Angelis

The remarkable adaptability observed in marine ecosystems has often inspired researchers when developing new soft materials. The research undertaken in this thesis explores how ion chelator pair interactions influence the mechanical properties of bioinspir ...

EPFL2024

Hybrid ground-state quantum algorithms based on neural Schrödinger forging

Giuseppe Carleo, Sofia Vallecorsa

Entanglement forging based variational algorithms leverage the bipartition of quantum systems for addressing ground-state problems. The primary limitation of these approaches lies in the exponential summation required over the numerous potential basis stat ...

Amer Physical Soc2024

Electrochemical devices and computer science: water/thermal management of proton exchange membrane fuel cells and electrolyzers in different scales

Hossein Pourrahmani

The current restrictions on the registration of combustion engines in different countries and the harmful impacts of fossil fuels on the environment and human health have motivated decision-makers to use batteries and/or fuel cells as alternatives for comb ...

EPFL2023

Quantum Protocols for ML, Physics, and Finance

Grzegorz Adam Gluch

In this thesis, we give new protocols that offer a quantum advantage for problems in ML, Physics, and Finance. Quantum mechanics gives predictions that are inconsistent with local realism. The experiment proving this fact (Bell, 1964) gives a quantum proto ...

EPFL2024

Computational drug development for membrane protein targets

Henning Paul-Julius Stahlberg, Pierre Vogel, Shuguang Yuan, Dongchun Ni, Babatunde Edukpe Ekundayo

The application of computational biology in drug development for membrane protein targets has experienced a boost from recent developments in deep learning-driven structure prediction, increased speed and resolution of structure elucidation, machine learni ...

2024

Large Libraries of Structurally Diverse Macrocycles Suitable for Membrane Permeation

Christian Heinis, Alessandro Angelini, Mischa Schüttel, Ganesh Kumar Mothukuri, Manuel Leonardo Merz, Zsolt Bognár, Xinjian Ji, Edward Jeffrey Will, Alexander Lund Nielsen, Anne Sofie Luise Zarda

Macrocycles offer an attractive format for drug development due to their good binding properties and potential to cross cell membranes. To efficiently identify macrocyclic ligands for new targets, methods for the synthesis and screening of large combinator ...

Wiley-VCH Verlag GmbH2024

Excited State-Specific CASSCF Theory for the Torsion of Ethylene

State-specific complete active space self-consistent field (SS-CASSCF) theory has emerged as a promising route to accurately predict electronically excited energy surfaces away from molecular equilibria. However, its accuracy and practicality for chemical ...

Amer Chemical Soc2024

Applications of the thawed Gaussian approximation to electronic spectroscopy

Eriks Kletnieks

The exploration of electronically excited states and the study of diverse photochemical and photophysical processes are the main goals of molecular electronic spectroscopy. Exact quantum-mechanical simulation of such experiments is, however, beyond current ...

EPFL2024

A cut-cell method for the numerical simulation of 3D multiphase flows with strong interfacial effects

Alexandre Caboussat, Alexandre Masserey, Marco Picasso, Julien Hess

We present a numerical model for the approximation of multiphase flows with free surfaces and strong interfacial effects. The model relies on the multiphase incompressible Navier-Stokes equations, and includes surface tension effects on the interfaces betw ...

Academic Press Inc Elsevier Science2024

Surface segregation in high-entropy alloys from alchemical machine learning

Michele Ceriotti, Sandip De, Nataliya Lopanitsyna, Guillaume André Jean Fraux, Arslan Mazitov

High-entropy alloys (HEAs), containing several metallic elements in near-equimolar proportions, have long been of interest for their unique mechanical properties. More recently, they have emerged as a promising platform for the development of novel heterog ...

Iop Publishing Ltd2024

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

Scalable Quantum Algorithms for Noisy Quantum Computers

Julien Sebastian Gacon

Quantum computing not only holds the potential to solve long-standing problems in quantum physics, but also to offer speed-ups across a broad spectrum of other fields. Access to a computational space that incorporates quantum effects, such as superposition ...

EPFL2024

Fluorogenic polymethine dyes by intramolecular cyclization

Pablo Rivera Fuentes, Annabell Martin

Fluorescence imaging plays a pivotal role in the study of biological processes, and cell -permeable fluorogenic dyes are crucial to visualize intracellular structures with high specificity. Polymethine dyes are vitally important fluorophores in singlemolec ...

Elsevier Sci Ltd2024

Emergence of highly coherent two-level systems in a noisy and dense quantum network

Sandrine Gerber, Gabriel Aeppli

Quantum sensors and qubits are usually two-level systems (TLS), the quantum analogues of classical bits assuming binary values 0 or 1. They are useful to the extent to which superpositions of 0 and 1 persist despite a noisy environment. The standard prescr ...

Nature Portfolio2024

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