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© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

Perovskite solar cells (PSCs) have revolutionized the field of photovoltaics, achieving certified power conversion efficiencies reaching 26% at the laboratory scale. High performance, enhanced stability, and long lifetime are prerequisites for the industrialization and commercialization of this class of third-generation photovoltaic technology. Toward the development of well-performing and robust PSCs against environmental stresses, advanced engineering strategies have been employed, targeting the preparation of perovskite absorbing layers with minimal defects and energy-level fine-tuning hydrophobic contacts. Focusing on both the electron transport layer/perovskite and perovskite/hole transport layer interfaces, this review work encompasses some of the most promising engineering methodologies that were recently proposed in order to optimize the device architecture. Machine learning approaches have also been used to validate experimental data and predict with accuracy solar cell parameters, further confirming the significance and justifying the application potential of the proposed innovative interface functionalization approaches.

Details

Title
Performance Enhancement and Stability Improvement in Perovskite Solar Cells via Interface Functionalization
Author
Falaras, Christos; Stathatos, Elias  VIAFID ORCID Logo 
First page
3319
Publication year
2023
Publication date
2023
Publisher
MDPI AG
e-ISSN
20799292
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2848994786
Copyright
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.