PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
December 14, 2025ChemSusChem3 citations

Thermal Management of Perovskite Solar Cells

View Full Paper
QZQinfang ZhangPCPisin ChenXZXiaohu Zhao

Key Points

  • The review aims to analyze the impact of thermal management on the performance of perovskite solar cells.
  • Assessment of temperature coefficients for various solar cells.
  • Comparison of thermal management strategies including passive and active cooling methods.
  • Evaluation of thermal issues such as thermal decomposition and phase transition behavior.
  • Identified significant effects of temperature on perovskite solar cells' performance.
  • Highlighted diverse thermal management strategies to mitigate negative effects of high temperatures.
  • Noted the potential role of machine learning in enhancing thermal management.

Abstract

This article presents a thorough review of perovskite solar cells (PSCs) thermal management. It starts with an analysis of solar cells’ temperature coefficients, emphasizing temperature's substantial effect on PSCs’ performance. The review includes a comparison of thermal coefficients across various solar cells: monocrystalline silicon, CIGS, perovskite, and tandem perovskite/silicon cells. The temperature sensitivity of PSCs is linked to perovskite materials’ thermal instability and temperature‐sensitive components like the organic hole transport layer. The review explores the negative effects of high temperatures on PSCs’ performance, such as thermal stress, thermal decomposition, and phase transition behavior. To tackle these issues, diverse thermal management strategies are assessed, including passive cooling (radiative cooling, phase change materials, heat pipe cooling, and passive evaporative cooling) and active cooling methods (fluid circulation cooling, jet impingement cooling, and spectral filtering). The review also underlines the significance of thermal management for PSCs in various applications, such as extreme space conditions, reverse solar cells, and building‐integrated photovoltaics. Furthermore, it discusses the potential of machine learning in aiding thermal management and the prospects of thermophotovoltaic cells. The review concludes by underscoring the crucial role of effective thermal management in improving PSCs’ efficiency and stability, which is vital for their large‐scale energy production.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Zhang et al. (2025) studied this question.

synapsesocial.com/papers/6941aaa70f5af7fd17df4b56https://doi.org/10.1002/cssc.202501649
Ask AI
Helpful
Bookmark
Share
View Full Paper