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Drift-diffusion and Machine Learning for High Efficiency Perovskite-Perovskite based Tandem Solar Cells
SINGH, Ajay; Gagliardi, Alessio
2019 • Proceedings of International Conference on Hybrid and Organic Photovoltaics (HOPV19) (/HOPV19)
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Disciplines :
Physics
Author, co-author :
SINGH, Ajay ;  Department of Electrical and Computer Engineering, Technical University of Munich
Gagliardi, Alessio;  Department of Electrical and Computer Engineering, Technical University of Munich
External co-authors :
yes
Language :
English
Title :
Drift-diffusion and Machine Learning for High Efficiency Perovskite-Perovskite based Tandem Solar Cells
Publication date :
May 2019
Event name :
Proceedings of International Conference on Hybrid and Organic Photovoltaics (HOPV19) (/HOPV19)
Event organizer :
Prashant Kamat, Filippo De Angelis and Aldo Di Carlo
Event place :
Luxembourg, Italy
Event date :
from 12-05-2019 to 15-05.2019
Audience :
International
Focus Area :
Physics and Materials Science
Additional URL :
https://www.nanoge.org/proceedings/HOPV19/5c35fb65c551940ccd2f4349
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since 31 August 2021

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