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Unlocking 3D nanoparticle shapes from 2D HRTEM images: A Deep Learning breakthrough

Title: Unlocking 3D nanoparticle shapes from 2D HRTEM images: A Deep Learning breakthrough
Authors: Moreau, Romain; Amara, Hakim; Moreaud, Maxime; Nelayah, Jaysen; Moncomble, Adrien; D., Alloyeau; Ricolleau, Christian; Gatti, Riccardo
Contributors: Université Paris Saclay, ONERA, CNRS, Laboratoire d'étude des microstructures (LEM); ONERA-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS); DMAS, ONERA, Université Paris Saclay Châtillon; ONERA-Université Paris-Saclay; Laboratoire Matériaux et Phénomènes Quantiques (MPQ (UMR_7162)); Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité); IFP Energies nouvelles (IFPEN); EDP Sciences
Source: BIO Web Conf. ; 17th European Microscopy Congress (EMC 2024) ; https://hal.science/hal-04835955 ; 17th European Microscopy Congress (EMC 2024), Aug 2024, Copenhague, Germany. pp.10030, ⟨10.1051/bioconf/202412910030⟩ ; https://www.bio-conferences.org/articles/bioconf/abs/2024/48/bioconf_emc2024_10030/bioconf_emc2024_10030.html
Publisher Information: CCSD
Publication Year: 2024
Subject Terms: atomistic simulation; TEM; nanoparticle; DL; [PHYS]Physics [physics]; [CHIM]Chemical Sciences; [SPI]Engineering Sciences [physics]
Subject Geographic: Copenhague; Germany
Description: International audience
Document Type: conference object
Language: English
DOI: 10.1051/bioconf/202412910030
Availability: https://hal.science/hal-04835955; https://hal.science/hal-04835955v1/document; https://hal.science/hal-04835955v1/file/bioconf_emc2024_10030.pdf; https://doi.org/10.1051/bioconf/202412910030
Rights: info:eu-repo/semantics/OpenAccess
Accession Number: edsbas.56DC8B70
Database: BASE