Roadmap on artificial intelligence and big data techniques for superconductivity
Yazdani-Asrami, Mohammad; Song, Wenjuan; Morandi, Antonio; De Carne, Giovanni; Murta-Pina, Joao; 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 (2023-04)
04 / 2023
Superconductor Science and Technology
043501
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-202304053473
https://urn.fi/URN:NBN:fi:tuni-202304053473
Kuvaus
Peer reviewed
Tiivistelmä
This paper presents a roadmap to the application of AI techniques and big data (BD) for different modelling, design, monitoring, manufacturing and operation purposes of different superconducting applications. To help superconductivity researchers, engineers, and manufacturers understand the viability of using AI and BD techniques as future solutions for challenges in superconductivity, a series of short articles are presented to outline some of the potential applications and solutions. These potential futuristic routes and their materials/technologies are considered for a 10-20 yr time-frame.
Kokoelmat
- TUNICRIS-julkaisut [24420]