Publications associées à Accurate molecular polarizabilities with coupled cluster theory and machine learning

Publications associées (46)

Nonlinear Effects in Fluctuation Short Pulse Reflectometry

Stefano Coda, Stephan Brunner, Oleg Krutkin

The fluctuation short pulse reflectometry diagnostic is simulated with the full-wave CUWA code for ad-hoc turbulence and simplified geometry. The nonlinear effects on the measurements are investigated while accounting for the plasma curvature, probing angl ...

IOP Publishing Ltd2025

Dipolar Carbazole Ammonium for Broadened Electric Field Distribution in High-Performance Perovskite Solar Cells

Felix Thomas Eickemeyer, Likai Zheng, Jaeki Jeong

Perovskite solar cells (PSCs) with ammonium passivation exhibit superior device performance and stability. Beyond typical chemical passivation, ammonium salts control the electronic structure of perovskite surfaces, yet the molecular structure-property rel ...

2025

Three-Dimensional Atomic-Level Structure of an Amorphous Glucagon-Like Peptide-1 Receptor Agonist

David Lyndon Emsley, Manuel Cordova, Pinelopi Moutzouri, Daria Torodii, Jacob Brian Holmes

Amorphous formulations are increasingly used in the pharmaceutical industry due to their increased solubility, but their structural characterization at atomic-level resolution remains extremely challenging. Here, we characterize the complete atomic-level s ...

American Chemical Society (ACS)2025

Machine Learning-assisted Sustainable Mix Design of Waste Glass Powder Concrete with Strength-cost-co2 Emissions Trade-offs

Lei Xu

Glass powder, a non-degradable waste material, offers significant potential to reduce cement consumption and carbon emissions in concrete production. However, existing mix design methods for glass powder concrete (GPC) fail to systematically balance econom ...

MDPI2025

Machine learning-aided hysteretic response prediction of double skin composite wall under earthquake loads

Yongtao Wu

Accurately and rapidly simulating the hysteretic behavior of double skin composite wall (DSCW) under earthquake loads enhance the efficiency of seismic performance assessments for high-rise steel-concrete composite structures. The application of artificial ...

2025

Automated processing of eXplainable Artificial Intelligence outputs in deep learning models for fault diagnostics of large infrastructures

Olga Fink

Deep Learning (DL) models processing images to recognize the health state of large infrastructure components can exhibit biases and rely on non-causal shortcuts. eXplainable Artificial Intelligence (XAI) can address these issues but manually analyzing expl ...

2025

Computational Studies on the Stability of Organic-Inorganic Hybrid Halide Lead Perovskites

Mathias Dankl

Perovskite-based solar cells are currently the most rapidly advancing photovoltaic technology but concerns about their long-term stability are still impeding full-scale commercialization. This thesis provides computational insights into some of the stabili ...

EPFL2024

Emotion information recovery potential of wav2vec2 network fine-tuned for speech recognition task

Tilak Purohit

Fine-tuning has become a norm to achieve state-of-the-art performance when employing pre-trained networks like foundation models. These models are typically pre-trained on large-scale unannotated data using self-supervised learning (SSL) methods. The SSL-b ...

Institute of Electrical and Electronics Engineers Inc.2025

Photoinduced Second-Order Nonlinearities in Centrosymmetric Media

Ozan Yakar

The interaction of light and matter enables nonlinear frequency conversion and the creation of coherent currents. The optical control of electric currents is of fundamental relevance and prominent research focus in the last decades. These photocurrents ena ...

EPFL2024

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

Fate of Cadmium and Lead Nitrates in Water

Wanda Andreoni

Cadmium, lead, and the nitrate (NO3-) ions rank among the most hazardous water pollutants. Natural sources of these species include cadmium and lead nitrates, which are highly soluble in water. Experimental data on the corresponding aqueous solutions are s ...

American Chemical Society (ACS)2025

Spin-Reorientation-Driven Linear Magnetoelectric Effect in Topological Antiferromagnet Cu3TeO6

Helmuth Berger

The search for new materials for energy -efficient electronic devices has gained unprecedented importance. Among the various classes of magnetic materials driving this search are antiferromagnets, magnetoelectrics, and systems with topological spin excitat ...

Amer Physical Soc2024

Fusing Machine Learning Methods with Computational Fluid Dynamics and Sensor Data for Indoor Air Quality Monitoring

Athanasios Nenes

Monitoring indoor air quality is important nowdays, as noted by many researchers, since pollution potentially introduces a major impact on the health of people. There are many factors that increase the concentration of a pollutant in a room and there may e ...

Institute of Electrical and Electronics Engineers Inc.2025

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

Dielectric Properties of Aqueous Electrolytes at the Nanoscale

Maximilian Becker, Philip Robin Loche

Despite the ubiquity of aqueous electrolytes, the effect of salt on water organization remains controversial. We introduce a nonlocal and nonlinear field theory for the nanoscale polarization of ions and water and derive the electrolyte dielectric response ...

American Physical Society (APS)2025

Magnetism of Single Surface Adsorbed Atoms Studied with Radio-Frequency STM

Clément Marie Soulard

This thesis investigates the magnetic properties of single atoms and molecules adsorbed on thin magnesium oxide decoupling layers, grown on a silver single crystal. To address these systems experimentally, we use a low temperature scanning tunneling micros ...

EPFL2024

Meteorological information prediction using images from webcams

Demetri Psaltis, Christophe Moser, Luisa Lambertini, Roy Sarkis

One aspect of the present invention proposes a method of predicting meteorological information by using an artificial deep neural network. The present invention according to one example focuses on image processing, specifically on fusing a plurality of ima ...

2025

Measuring electrical properties in semiconductor devices by pixelated STEM and off-axis electron holography (or convergent beams vs. plane waves)

Victor Carle Adrien Boureau

We demonstrate the use of both pixelated differential phase contrast (DPC) scanning transmission electron microscopy (STEM) and off-axis electron holography (EH) for the measurement of electric fields and assess the advantages and limitations of each techn ...

Pergamon-Elsevier Science Ltd2024

Pyroresistive response of percolating conductive polymer composites

Claudio Grimaldi

The pyroresistive response of conductive polymer composites (CPCs) has attracted much interest because of its potential applications in many electronic devices requiring a significant responsiveness to changes in external physical parameters such as temper ...

Amer Physical Soc2024

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