Ph.D. in Energetica , 36th cycle (2020-2023)
Ph.D. obtained in 2024
Dissertation:
Artificial Intelligence based screening of materials for energy storage applications (Abstract)
Tutors:
Eliodoro Chiavazzo Matteo FasanoTeaching
Teachings
Master of Science
- Energy storage. A.A. 2020/21, INGEGNERIA ENERGETICA E NUCLEARE. Collaboratore del corso
- Energy storage. A.A. 2021/22, INGEGNERIA ENERGETICA E NUCLEARE. Collaboratore del corso
- Energy storage. A.A. 2022/23, INGEGNERIA ENERGETICA E NUCLEARE. Collaboratore del corso
- Energy storage. A.A. 2023/24, INGEGNERIA ENERGETICA E NUCLEARE. Collaboratore del corso
- Applicazioni energetiche dei materiali. A.A. 2021/22, INGEGNERIA ENERGETICA E NUCLEARE. Collaboratore del corso
- Applicazioni energetiche dei materiali. A.A. 2022/23, INGEGNERIA ENERGETICA E NUCLEARE. Collaboratore del corso
- Applicazioni energetiche dei materiali. A.A. 2023/24, INGEGNERIA ENERGETICA E NUCLEARE. Collaboratore del corso
Publications
Works published during the Ph.D. View all publications in Porto@Iris
- Barletta, Giulio; Trezza, Giovanni; Chiavazzo, Eliodoro (2024)
Learning Effective Good Variables from Physical Data. In: MACHINE LEARNING AND KNOWLEDGE EXTRACTION, vol. 6, pp. 1597-1618. ISSN 2504-4990
Contributo su Rivista - Trezza, G; Bergamasco, L; Fasano, M; Chiavazzo, E (2024)
Optimizing MOF properties for seasonal heat storage: a machine learning approach. In: Eurotherm 2024, Bled, Slovenia. ISSN 1742-6588
Contributo in Atti di Convegno (Proceeding) - Bonke, Shannon A.; Trezza, Giovanni; Bergamasco, Luca; Song, Hongwei; Rodríguez-Jiménez, ... (2024)
Multi-Variable Multi-Metric Optimization of Self-Assembled Photocatalytic CO2 Reduction Performance Using Machine Learning Algorithms. In: JOURNAL OF THE AMERICAN CHEMICAL SOCIETY, vol. 146. ISSN 0002-7863
Contributo su Rivista - Trezza, Giovanni (2024)
Artificial Intelligence based screening of materials for energy storage applications. relatore: CHIAVAZZO, ELIODORO; FASANO, MATTEO; , 36. XXXVI Ciclo, P.: 145
Doctoral Thesis - Trezza, Giovanni; Chiavazzo, Eliodoro (2023)
Leveraging composition-based energy material descriptors for machine learning models. In: MATERIALS TODAY COMMUNICATIONS, vol. 36. ISSN 2352-4928
Contributo su Rivista - Trezza, Giovanni; Bergamasco, Luca; Fasano, Matteo; Chiavazzo, Eliodoro (2022)
Minimal crystallographic descriptors of sorption properties in hypothetical MOFs and role in sequential learning optimization. In: NPJ COMPUTATIONAL MATERIALS, vol. 8. ISSN 2057-3960
Contributo su Rivista