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Computation of sensitivity coefficients in fixed source simulations with SERPENT2

Andreas Pautz, Mathieu Hursin

Within the scope of the implementation of a nuclear data pipeline aiming at producing the best possible evaluated nuclear data files, a major point is the production of relevant sensitivity coefficients when including integral benchmark information. Thanks ...
Lausanne2024

Supplementary datasets for the manuscript "Generative machine learning produces kinetic models that accurately characterize intracellular metabolic states" -Part 2

Vassily Hatzimanikatis, Ljubisa Miskovic, Michaël Roger Germain Moret

Supplementary files containing datasets needed to reproduce the results of the manuscript "Generative machine learning produces kinetic models that accurately characterize intracellular metabolic states" by S. Choudhury et al. The code to use with these da ...
EPFL Infoscience2023

Dataset for the publication "Reversal of nanomagnets by propagating magnons in ferrimagnetic yttrium iron garnet enabling nonvolatile magnon memory"

Dirk Grundler, Korbinian Baumgärtl

Raw data associated to the manuscript ‘’Reversal of nanomagnets by propagating magnons in ferrimagnetic yttrium iron garnet enabling nonvolatile magnon memory‘’, Nature Communications (2023); doi: https://doi.org/10.1038/s41467-023-37078-8 Information abou ...
EPFL Infoscience2023

Reproducibility Dataset for CRYOWRF v1.0

Varun Sharma, Michael Lehning, Franziska Gerber

This repository contains data required for reproducibility of the results to be published in the associated manuscript. Apart from reproducibility, the attached datasets also serve as templates for new users to adopt CRYOWRF in their research. The datasets ...
2023

Supplementary datasets for the manuscript "Generative machine learning produces kinetic models that accurately characterize intracellular metabolic states" - Part 3

Vassily Hatzimanikatis, Ljubisa Miskovic, Michaël Roger Germain Moret

Supplementary files containing datasets needed to reproduce the results of the manuscript "Generative machine learning produces kinetic models that accurately characterize intracellular metabolic states" by S. Choudhury et al (https://doi.org/10.1101/2023. ...
EPFL Infoscience2023

Coherent Hole Transport in Selective Area Grown Ge Nanowire Networks

Alok Rudra, Andrea Giunto, Santhanu Panikar Ramanandan, Nicholas Paul Morgan

This document contains all the raw data files used for the manuscript. ...
EPFL Infoscience2022

Persistence of the isotopic signature of pentavalent uranium in magnetite

Rizlan Bernier-Latmani, Barbora Bártová, Zezhen Pan

Original data pertaining to the manuscript 'Persistence of the isotopic signature of pentavalent uranium in magnetite' published in Environmental Science and Technology by Zezhen Pan, Yvonne Roebbert, Aaron Beck, Barbora Bartova, Tonya Vitova, Stefan Weyer ...
EPFL Infoscience2022

Design, prototyping, and thermo-mechanical modelling of a neutron spallation target impacted by high-energy proton-beam pulses in the n_TOF facility at CERN

Raffaele Esposito

This manuscript describes the design work and the R&D activities carried out for the third-generation neutron production target in the neutron Time-Of-Flight (n_TOF) facility at the European Laboratory for Particle Physics (CERN). The facility is composed ...
EPFL2022

Supplemental Data - Intact Drosophila Whole Brain Cellular Quantitation reveals Sexual Dimorphism

Wei Jiao

Supplemental Figures, Datasets and Movies supporting the manuscript - Intact Drosophila Whole Brain Cellular Quantitation reveals Sexual Dimorphism. Wei Jiao, Gard Spreemann, Evelyne Ruchti, Soumya Banerjee, Ying Shi, R. Steven Stowers, Ka ...
EPFL Infoscience2021

Propulsion and energetics of a minimal magnetic microswimmer

Ignacio Pagonabarraga Mora

In this manuscript we describe the realization of a minimal hybrid microswimmer, composed of a ferromagnetic nanorod and a paramagnetic microsphere. The unbounded pair is propelled in water upon application of a swinging magnetic field that induces a perio ...
ROYAL SOC CHEMISTRY2020

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