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Review of current progress in hole-transporting materials for perovskite solar cells

Journal of Energy Chemistry 2022年第5期31卷 330-386页

作者： Prerna Mahajan Bhavya Padha Sonali Verma Vinay Gupta Ram Datt Wing Chung Tsoi soumitra satapathi Sandeep Arya Department of Physics University of JammuJammuJammu and Kashmir 180006India Department of Physics Khalifa University of Science and TechnologyAbu Dhabi 127788United Arab Emirates SPECIFIC College of EngineeringSwansea University Bay CampusFabian WaySA18ENSwanseaUnited Kingdom Department of Physics Indian Institute of Technology RoorkeeUttarakhand 247667India

Recent advancements in perovskites’ application as a solar energy harvester have been astonishing. The power conversion efficiency(PCE) of perovskite solar cells(PSCs) is currently reaching parity(>25 percent), an accomplishment attained over past decades. PSCs are seen as perovskites sandwiched between an electron transporting material(ETM) and a hole transporting material(HTM). As a primary component of PSCs, HTM has been shown to have a considerable effect on solar energy harvesting, carrier extraction and transport, crystallization of perovskite, stability, and price. In PSCs, it is still necessary to use a *** perovskites are capable of conducting holes, they are present in trace amounts, necessitating the use of an HTM layer for efficient charge extraction. In this review, we provide an understanding of the significant forms of HTM accessible(inorganic, polymeric and small molecule-based HTMs), to motivate further research and development of such materials. The identification of additional criteria suggests a significant challenge to high stability and affordability in PSC.

关键词： Hole transporting material Perovskite solar cells Power conversion efficiency Stability

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Is machine learning redefining the perovskite solar cells?

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Journal of Energy Chemistry 2022年第3期31卷 74-90,I0004页

作者： Nishi Parikh Meera Karamta Neha Yadav Mohammad Mahdi Tavakoli Daniel Prochowicz Seckin Akin Abul Kalam soumitra satapathi Pankaj Yadav Department of Science School of TechnologyPandit Deendayal Energy UniversityGandhinagar 382007GujaratIndia Department of Electrical Engineering School of TechnologyPandit Deendayal Energy UniversityGandhinagar 382007GujaratIndia Department of Telecommunication Ministry of CommunicationMumbai LSAMumbai 400072MaharashtraIndia Department of Electrical Engineering and Computer Science Massachusetts Institute of TechnologyCambridgeMA 02139USA Institute of Physical Chemistry Polish Academy of SciencesKasprzaka 44/5201-224 WarsawPoland Department of Metallurgical and Materials Engineering Karamanoglu Mehmetbey University70200 KaramanTurkey Department of Chemistry Faculty of ScienceKing Khalid UniversityAbha 61413P.O.Box 9004Saudi Arabia Department of Physics Indian Institute of Technology RoorkeeRoorkeeHaridwarUttarakhand 247667India Department of Solar Energy School of TechnologyPandit Deendayal Energy UniversityGandhinagar 382007GujaratIndia

Development of novel materials with desirable properties remains at the forefront of modern scientific *** learning(ML),a branch of artificial intelligence,has recently emerged as a powerful technology in optoelectronic devices for the prediction of various properties and rational design of *** halide perovskites(MHPs)have been at the centre of attraction owing to their outstanding photophysical properties and rapid development in solar cell ***,the application of ML in the field of MHPs is also getting much attention to optimize the fabrication process and reduce the cost of ***,we comprehensively reviewed different applications of ML in the designing of both MHP absorber layers as well as complete perovskite solar cells(PSCs).At the end,the challenges of ML along with the possible future direction of research are *** believe that this review becomes an indispensable roadmap for optimizing materials composition and predicting design strategies in the field of perovskite technology in the future.

关键词： Machine learning Metal halide perovskites Perovskite solar cell Lead free perovskites

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