{"year":"2025","status":"public","ddc":["530"],"department":[{"_id":"GeKa"}],"arxiv":1,"date_published":"2025-10-22T00:00:00Z","_id":"20594","article_type":"original","publication":"Advanced Materials","publication_status":"epub_ahead","day":"22","publication_identifier":{"eissn":["1521-4095"],"issn":["0935-9648"]},"acknowledgement":"ICN2 acknowledged funding from Generalitat de Catalunya 2021SGR00457, 2021SGR00997 and 2021SGR01519. The authors thank support from the project AMaDE (PID2023-149158OB-C43), funded by MCIN/ AEI/10.13039/501100011033/. This study was part of the Advanced Materials programme and was supported by MCIN with funding from European Union NextGenerationEU (PRTR-C17.I1) and by Generalitat de Catalunya (In-CAEM Project). The authors acknowledged support from CSIC Interdisciplinary Thematic Platform (PTI+) on Quantum Technologies (PTI-QTEP+). This research work had been funded by the European Commission – NextGenerationEU (Regulation EU 2020/2094), through CSIC's Quantum Technologies Platform (QTEP). ICN2 was supported by the Severo Ochoa program from Spanish MCIN / AEI (Grant No.: CEX2021-001214-S) and was funded by the CERCA Programme / Generalitat de Catalunya. Part of the present work had been performed in the framework of Universitat Autònoma de Barcelona Materials Science PhD program. I.P.H. acknowledged funding from AGAUR-FI scholarship (2023FI-00268) Joan Oró of the Secretariat of Universities of the Generalitat of Catalonia and the European SocialPlus Fund. M.B. acknowledged support from SUR Generalitat de Catalunya and the EU Social Fund; project ref. 2020 FI 00103. This study was supported by EU HORIZON INFRA TECH 2022 project IMPRESS (Ref.: 101094299). Authors acknowledged the use of instrumentation as well as the technical advice provided by the Joint Electron Microscopy Center at ALBA (JEMCA). ICN2 acknowledged funding from Grant IU16-014206 (METCAM-FIB) funded by the European Union through the European Regional Development Fund (ERDF), with the support of the Ministry of Research and Universities, Generalitat de Catalunya. ICN2 was a founding member of e-DREAM.[135] S.R. was also supported by MICIN with European funds NextGenerationEU (PRTRC17.I1) funded by Generalitat de Catalunya. P.O. acknowledged support from the EU MaX CoE (Grant No. 101093374), Grants No. PCI2022-134972-2 and No. PID2022-139776NB-C62 funded by the Spanish MCIN/AEI/10.13039/501100011033 and by the ERDF, A way of making Europe.The authors thank the Catalan Quantum Academy for support. The authors acknowledged Dámaso Torres for his support in designing the graphical material.","citation":{"ama":"Botifoll M, Pinto-Huguet I, Rotunno E, et al. Artificial intelligence-assisted workflow for transmission electron microscopy: From data analysis automation to materials knowledge unveiling. <i>Advanced Materials</i>. 2025. doi:<a href=\"https://doi.org/10.1002/adma.202506785\">10.1002/adma.202506785</a>","ista":"Botifoll M, Pinto-Huguet I, Rotunno E, Galvani T, Coll C, Kavkani PH, Spadaro MC, Niquet YM, Eriksen MB, Martí-Sánchez S, Katsaros G, Scappucci G, Krogstrup P, Isella G, Cabot A, Merino G, Ordejón P, Roche S, Grillo V, Arbiol J. 2025. Artificial intelligence-assisted workflow for transmission electron microscopy: From data analysis automation to materials knowledge unveiling. Advanced Materials., e06785.","apa":"Botifoll, M., Pinto-Huguet, I., Rotunno, E., Galvani, T., Coll, C., Kavkani, P. H., … Arbiol, J. (2025). Artificial intelligence-assisted workflow for transmission electron microscopy: From data analysis automation to materials knowledge unveiling. <i>Advanced Materials</i>. Wiley. <a href=\"https://doi.org/10.1002/adma.202506785\">https://doi.org/10.1002/adma.202506785</a>","chicago":"Botifoll, Marc, Ivan Pinto-Huguet, Enzo Rotunno, Thomas Galvani, Catalina Coll, Payam Habibzadeh Kavkani, Maria Chiara Spadaro, et al. “Artificial Intelligence-Assisted Workflow for Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling.” <i>Advanced Materials</i>. Wiley, 2025. <a href=\"https://doi.org/10.1002/adma.202506785\">https://doi.org/10.1002/adma.202506785</a>.","short":"M. Botifoll, I. Pinto-Huguet, E. Rotunno, T. Galvani, C. Coll, P.H. Kavkani, M.C. Spadaro, Y.M. Niquet, M.B. Eriksen, S. Martí-Sánchez, G. Katsaros, G. Scappucci, P. Krogstrup, G. Isella, A. Cabot, G. Merino, P. Ordejón, S. Roche, V. Grillo, J. Arbiol, Advanced Materials (2025).","mla":"Botifoll, Marc, et al. “Artificial Intelligence-Assisted Workflow for Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling.” <i>Advanced Materials</i>, e06785, Wiley, 2025, doi:<a href=\"https://doi.org/10.1002/adma.202506785\">10.1002/adma.202506785</a>.","ieee":"M. Botifoll <i>et al.</i>, “Artificial intelligence-assisted workflow for transmission electron microscopy: From data analysis automation to materials knowledge unveiling,” <i>Advanced Materials</i>. Wiley, 2025."},"language":[{"iso":"eng"}],"type":"journal_article","oa_version":"Published Version","article_number":"e06785","article_processing_charge":"Yes (in subscription journal)","date_updated":"2025-11-04T08:07:30Z","OA_place":"publisher","title":"Artificial intelligence-assisted workflow for transmission electron microscopy: From data analysis automation to materials knowledge unveiling","scopus_import":"1","doi":"10.1002/adma.202506785","tmp":{"short":"CC BY-NC-ND (4.0)","image":"/images/cc_by_nc_nd.png","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode","name":"Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)"},"month":"10","quality_controlled":"1","abstract":[{"text":"(Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of devices due to its time-intensive nature. To address this, an analytical workflow is introduced for the holistic characterization, modelling, and simulation of device heterostructures. This workflow automates the experimental (S)TEM data analysis, providing an in-depth characterization of crystallographic information, 3D orientation, elemental composition, and strain distribution. It reduces a process that typically takes days for a trained human into an automatic routine solved in minutes. Utilizing a physics-guided artificial intelligence model, it generates representative descriptions of materials and samples. The workflow culminates in creating digital twins of systems limited with at least one axis of translational invariance –3D finite element and atomic models of millions of atoms–enabling simulations that provide crucial insights into device behavior in practical applications. Demonstrated with SiGe planar heterostructures for scalable spin qubits, the workflow links digital twins to theoretical properties, revealing how atomic structure impacts materials and functional properties such as spatially-resolved phononic or electronic characteristics, or (inverse) spin orbit lengths. The versatility of the workflow is demonstrated through its application to a wide array of materials systems, device configurations, and sample morphologies.","lang":"eng"}],"OA_type":"hybrid","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publisher":"Wiley","author":[{"first_name":"Marc","full_name":"Botifoll, Marc","last_name":"Botifoll"},{"first_name":"Ivan","last_name":"Pinto-Huguet","full_name":"Pinto-Huguet, Ivan"},{"full_name":"Rotunno, Enzo","last_name":"Rotunno","first_name":"Enzo"},{"full_name":"Galvani, Thomas","last_name":"Galvani","first_name":"Thomas"},{"full_name":"Coll, Catalina","last_name":"Coll","first_name":"Catalina"},{"first_name":"Payam Habibzadeh","last_name":"Kavkani","full_name":"Kavkani, Payam Habibzadeh"},{"first_name":"Maria Chiara","last_name":"Spadaro","full_name":"Spadaro, Maria Chiara"},{"full_name":"Niquet, Yann Michel","last_name":"Niquet","first_name":"Yann Michel"},{"full_name":"Eriksen, Martin Børstad","last_name":"Eriksen","first_name":"Martin Børstad"},{"first_name":"Sara","last_name":"Martí-Sánchez","full_name":"Martí-Sánchez, Sara"},{"id":"38DB5788-F248-11E8-B48F-1D18A9856A87","first_name":"Georgios","last_name":"Katsaros","orcid":"0000-0001-8342-202X","full_name":"Katsaros, Georgios"},{"first_name":"Giordano","full_name":"Scappucci, Giordano","last_name":"Scappucci"},{"first_name":"Peter","last_name":"Krogstrup","full_name":"Krogstrup, Peter"},{"full_name":"Isella, Giovanni","last_name":"Isella","first_name":"Giovanni"},{"full_name":"Cabot, Andreu","last_name":"Cabot","first_name":"Andreu"},{"first_name":"Gonzalo","last_name":"Merino","full_name":"Merino, Gonzalo"},{"first_name":"Pablo","full_name":"Ordejón, Pablo","last_name":"Ordejón"},{"first_name":"Stephan","last_name":"Roche","full_name":"Roche, Stephan"},{"first_name":"Vincenzo","last_name":"Grillo","full_name":"Grillo, Vincenzo"},{"last_name":"Arbiol","full_name":"Arbiol, Jordi","first_name":"Jordi"}],"date_created":"2025-11-02T23:01:35Z","license":"https://creativecommons.org/licenses/by-nc-nd/4.0/","main_file_link":[{"url":"https://doi.org/10.1002/adma.202506785"}],"external_id":{"arxiv":["2411.01024"]},"has_accepted_license":"1"}