Drift-diffusion and Machine Learning for High Efficiency Perovskite-Perovskite based Tandem Solar Cells

SINGH, Ajay; Gagliardi, Alessio

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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

Available on ORBilu :

since 31 August 2021

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