Roadmap on artificial intelligence and big data techniques for superconductivity

• Autor(a) principal: Yazdani-Asrami, Mohammad
• Data de Publicação: 2023
• Outros Autores: Song, Wenjuan, Morandi, Antonio, de Carne, Giovanni, Murta-Pina, João, Pronto, Anabela, Oliveira, Roberto, Grilli, Francesco, Pardo, Enric, Parizh, Michael, Shen, Boyang, Coombs, Tim, Salmi, Tiina, Wu, Di, Coatanea, Eric, Moseley, Dominic A., Badcock, Rodney A., Zhang, Mengjie, Marinozzi, Vittorio, Tran, Nhan, Wielgosz, Maciej, Skoczeń, Andrzej, Tzelepis, Dimitrios, Meliopoulos, Sakis, Vilhena, Nuno, Sotelo, Guilherme, Jiang, Zhenan, Große, Veit, Bagni, Tommaso, Mauro, Diego, Senatore, Carmine, Mankevich, Alexey, Amelichev, Vadim, Samoilenkov, Sergey, Yoon, Tiem Leong, Wang, Yao, Camata, Renato P., Chen, Cheng Chien, Madureira, Ana Maria, Abraham, Ajith
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10362/155114
• topic: applied superconductivity; artificial intelligence; big data; deep learning; machine learning; neural network; Ceramics and Composites; Condensed Matter Physics; Metals and Alloys; Electrical and Electronic Engineering; Materials Chemistry

Funding Information: Financial support was provided by the Swiss National Science Foundation (Grant No. 200021_184940). Funding Information: Networking support provided by the European Cooperation in Science and Technology, COST Action CA19108 (Hi-SCALE) is acknowledged. Funding Information: A part of this work was supported by the Russian National Technology Initiative Foundation (Grant ID 0000000007418QR20002). Funding Information: The research was also supported by the European Synchrotron Radiation Facility (Grant No. MA-2767). Funding Information: This work was supported in part by the New Zealand Ministry of Business, Innovation and Employment (MBIE) by the Strategic Science Investment Fund ‘‘Advanced Energy Technology Platforms’’ under Contract RTVU2004. Funding Information: Y Wang acknowledges support from the National Science Foundation (NSF) Award DMR-2132338. R P Camata and C-C Chen are supported by the FTPP Program funded by NSF EPSCoR RII Track-1 Cooperative Agreement OIA-2148653. C-C Chen also acknowledges support from the NSF Award DMR-2142801. Publisher Copyright: © 2023 The Author(s). Published by IOP Publishing Ltd.