Publications associées à Azole-Based Indoleamine 2,3-Dioxygenase 1 (IDO1) Inhibitors

Efficient and insightful descriptors for representing molecular and material space

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

A lunar reconnaissance drone for cooperative exploration and high-resolution mapping of extreme locations

Erik Uythoven, Thomas Pfeiffer, Daniel Tataru, David Rodriguez Martinez

An efficient characterization of scientifically significant locations is essential prior to the return of humans to the Moon. The highest resolution imagery acquired from orbit of south-polar shadowed regions and other relevant locations remains, at best, ...

Pergamon-Elsevier Science Ltd2024

Gaia's brightest very metal-poor (VMP) stars Metallicity catalogue of a thousand VMP stars from Gaia's radial velocity spectrometer spectra

Nicolas Lawrence Etienne Longeard

Context. Gaia DR3 has offered the scientific community a remarkable dataset of approximately one million spectra acquired with the radial velocity spectrometer (RVS) in the calcium II triplet region, which is well suited to identify very metal-poor (VMP) s ...

Edp Sciences S A2024

Lake surface cooling drives littoral-pelagic exchange of dissolved gases

Alfred Johny Wüest, Damien Bouffard, Tomy Doda, Hugo Nicolás Ulloa Sánchez, Cintia Luz Ramon Casanas

The extent of littoral influence on lake gas dynamics remains debated in the aquatic science community due to the lack of direct quantification of lateral gas transport. The prevalent assumption of diffusive horizontal transport in gas budgets fails to exp ...

Amer Assoc Advancement Science2024

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

Single-Photon Avalanche Diode Image Sensors for Harsh Radiation Environments

Ming-Lo Wu

The space industry has experienced substantial growth in recent years, leading to rapid advancements in space exploration and space-based technologies. Consequently, the study of electronics and sensor performance in extreme environments has become crucial ...

EPFL2024

Precision luminosity measurement at hadron colliders

Joanna Malgorzata Wanczyk

This thesis links two realms of particle accelerator dynamics and precision particle physics. The achievement of precise luminosity measurement at hadron colliders is enabled with dedicated luminometers. For the Run 3 period, the luminometer upgrade was ...

EPFL2024

Mesh-based topology, shape and sizing optimization of ribbed plates

In this paper, we present a new parameterization and optimization procedure for minimizing the weight of ribbed plates. The primary goal is to reduce embodied CO2 in concrete floors as part of the effort to diminish the carbon footprint of the construction ...

Springer2024

Orbital-Resolved DFT plus U for Molecules and Solids

Nicola Marzari, Iurii Timrov, Eric Macke

We present an orbital-resolved extension of the Hubbard U correction to density-functional theory (DFT). Compared to the conventional shell-averaged approach, the prediction of energetic, electronic and structural properties is strongly improved, particula ...

Amer Chemical Soc2024

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

A Geometric Transformer for Structural Biology: Development and Applications of the Protein Structure Transformer

Lucien Fabrice Krapp

Proteins, the central building blocks of life, play pivotal roles in nearly every biological function. To do so, these macromolecular structures interact with their surrounding environment in complex ways, leading to diverse functional behaviors. The predi ...

EPFL2023

De novo design of protein interactions with learned surface fingerprints

Henning Paul-Julius Stahlberg, Didier Trono, Priscilla Turelli, Charlène Mireille Raymonde Raclot, Sandrine Madeleine Suzanne Georgeon, Beat Fierz, Aaron Simone Petruzzella, Anthony Marchand, Bruno Emanuel Ferreira De Sousa Correia, Elisa Oricchio, Zander Harteveld, Pablo Gainza Cirauqui, Freyr Sverrisson, Andreas Scheck, Sarah Wehrle, Stéphane Rosset, Alexandra Krina Van Hall-Beauvais, Alexandra Teslenko, Jane Marsden, Michael Bronstein, Casper Alexander Goverde, Stephen Michael Buckley, Dongchun Ni, Martin Pacesa

Physical interactions between proteins are essential for most biological processes governing life. However, the molecular determinants of such interactions have been challenging to understand, even as genomic, proteomic and structural data increase. This k ...

2023

Toward a brightness upgrade to the SwissFEL: A high gradient traveling-wave rf photogun

Anastasiya Magazinik, Mike Seidel, Paolo Craievich, Sven Reiche

The first generation of S-band injectors for free-electron lasers has illustrated high reliability and performance by driving the latest generation of high brightness machines. However, the ultimate electron beam brightness of these devices is limited by t ...

Amer Physical Soc2023

Transfer learning application of self-supervised learning in ARPES

Gabriel Aeppli

There is a growing recognition that electronic band structure is a local property of materials and devices, and there is steep growth in capabilities to collect the relevant data. New photon sources, from small-laboratory-based lasers to free electron lase ...

IOP Publishing Ltd2023

Structural topology exploration through policy-based generation of equilibrium representations

Corentin Jean Dominique Fivet, Ioannis Mirtsopoulos

Mainstream approaches to design spatial architectural forms that are structurally relevant consist either in adapting well-known and catalogued conventional types or in searching for close-to-optimum solutions of well-defined problems. Few means exist to e ...

2023

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

Predicting Ion Diffusion from the Shape of Potential Energy Landscapes

Berend Smit, Senja Dominique Barthel, Amber Kashan Mace

We present an efficient method to compute diffusion coefficients of multiparticle systems with strong interactions directly from the geometry and topology of the potential energy field of the migrating particles. The approach is tested on Li-ion diffusion ...

Amer Chemical Soc2023

Single-Well Pore Pressure Preconditioning for Enhanced Geothermal System Stimulation

Marie Estelle Solange Violay, Barnaby Padraig Fryer, Mathias Alexandre David Lebihain

The stress state is an important parameter in terms of both earthquake nucleation and rupture. Here, a new stimulation technique is proposed for Enhanced Geothermal Systems (EGSs), which have previously been burdened with a number of high-profile incidence ...

2023

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

Gaia Focused Product Release: Radial velocity time series of long-period variables

Stephan Morgenthaler, Shuangqing Liao

Context. The third Gaia Data Release (DR3) provided photometric time series of more than 2 million long-period variable (LPV) candidates. Anticipating the publication of full radial-velocity data planned with Data Release 4, this Focused Product Release (F ...

Edp Sciences S A2023