The modification of the perovskite surface using functional additives is one of the most promising strategies to reduce nonradiative recombination and improve the stability of perovskite solar cells(PSCs).In this work...The modification of the perovskite surface using functional additives is one of the most promising strategies to reduce nonradiative recombination and improve the stability of perovskite solar cells(PSCs).In this work,a novel quaternary pyridinium-based halide salt,1-ethyl-4-(methoxycarbonyl)pyridinium iodide(EMCP-I),is introduced as an effective post-treatment molecule to improve the quality of the perovskite film.EMCP-I exhibits dual functionality to passivate both negatively and positively charged defects and improve the film morphology.Furthermore,the treatment fine-tunes energy level alignment between the perovskite layer and the hole transport layer(HTL),facilitating more efficient charge transport.Consequently,EMCP-I-treated devices achieve a remarkable power conversion efficiency(PCE)improvement from 20.5% to 22.6%,driven primarily by an enhanced open-circuit voltage(VOC).Beyond efficiency gains,the treatment significantly enhances the environmental and operational stabilities of solar cells.This work provides a guide for tailoring quaternary pyridinium-based molecules for simultaneous improvement of the efficiency and stability of PSCs.展开更多
We introduce a dual distribution of relaxation(DRT)based approach for analyzing electrochemical impedance spectroscopy(EIS)data in perovskite solar cells(PSCs),combining regression and classification with Bayesian mod...We introduce a dual distribution of relaxation(DRT)based approach for analyzing electrochemical impedance spectroscopy(EIS)data in perovskite solar cells(PSCs),combining regression and classification with Bayesian model selection and Havriliak-Negami(HN)modeling to resolve spectra into discrete,Lorentzian-like peaks.This time-domain decomposition offers a powerful alternative for identifying underlying physical processes,such as charge transfer,trap-assisted recombination,and ionic migration by directly extracting characteristic relaxation times(τ).In contrast to traditional equivalent circuit fitting or conventional DRT methods,which often yield broad and overlapping Gaussian-like peaks,our method enables sharper resolution of individual electrochemical signatures.Furthermore,we validated the framework using simulated EIS spectra for two distinct system types,determining the optimal number of peaks(Q)through statistical model selection.Applied to experimental PSC data under varying bias conditions,the approach helps to identify the voltage-dependent relaxation processes,including fast charge transfer(τ~10^(-6)s),intermediate trap-mediated recombination(τ~10^(-2)s),and slow ionic motion(τ~1 s).Lower-Q models fail to capture low-frequency features such as polarization and charge accumulation,while optimal Q yields accurate,physically meaningful representations of device behavior.This data-driven methodology highlights time-domain DRT as a rigorous and insightful tool for dissecting the complex kinetics that govern PSC performance.展开更多
Development of novel materials with desirable properties remains at the forefront of modern scientific research.Machine learning(ML),a branch of artificial intelligence,has recently emerged as a powerful technology in...Development of novel materials with desirable properties remains at the forefront of modern scientific research.Machine 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 materials.Metal halide perovskites(MHPs)have been at the centre of attraction owing to their outstanding photophysical properties and rapid development in solar cell application.Therefore,the application of ML in the field of MHPs is also getting much attention to optimize the fabrication process and reduce the cost of processing.Here,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 discussed.We 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.展开更多
The extensive research and development in perovskite solar cells (PSCs) have rekindled the hopes of converting solar energy into electricity.An elusive understanding of underlying mechanisms is required for the develo...The extensive research and development in perovskite solar cells (PSCs) have rekindled the hopes of converting solar energy into electricity.An elusive understanding of underlying mechanisms is required for the development of efficient PSCs.Over the years,Impedance Spectroscopy (IS) characterization,along with complementary techniques,has proven to be an effective way to understand and analyze the charge transport and recombination at interface and bulk of PSCs.The IS of PSCs have been analyzed,interpreted,and improvised continuously,revealing intricate details about the work.However,there is a lack of centralized source of these details,which make it tougher to account for the generalized approach to understand the device properties.The present work is focused on compiling the research done on various PSC device architectures via IS to construct a comprehensive foundation of information on impedance plots,equivalent circuits,and associated processes.展开更多
基金financially supported by The Scientific and Technological Research Council of Türkiye(TüBITAK)under Project No.119F185the support of the Interdisciplinary Centre for Mathematical and Computational Modelling at the University of Warsaw(ICM UW)under computational allocation no.g93-1617。
文摘The modification of the perovskite surface using functional additives is one of the most promising strategies to reduce nonradiative recombination and improve the stability of perovskite solar cells(PSCs).In this work,a novel quaternary pyridinium-based halide salt,1-ethyl-4-(methoxycarbonyl)pyridinium iodide(EMCP-I),is introduced as an effective post-treatment molecule to improve the quality of the perovskite film.EMCP-I exhibits dual functionality to passivate both negatively and positively charged defects and improve the film morphology.Furthermore,the treatment fine-tunes energy level alignment between the perovskite layer and the hole transport layer(HTL),facilitating more efficient charge transport.Consequently,EMCP-I-treated devices achieve a remarkable power conversion efficiency(PCE)improvement from 20.5% to 22.6%,driven primarily by an enhanced open-circuit voltage(VOC).Beyond efficiency gains,the treatment significantly enhances the environmental and operational stabilities of solar cells.This work provides a guide for tailoring quaternary pyridinium-based molecules for simultaneous improvement of the efficiency and stability of PSCs.
基金the ORSP of Pandit Deendayal Energy University and DST SERB(IPA/2021/96)for the financial supportthe Deanship of Research and Graduate Studies at King Khalid University for funding this work through the Large Research Project under grant number RGP 2/345/45。
文摘We introduce a dual distribution of relaxation(DRT)based approach for analyzing electrochemical impedance spectroscopy(EIS)data in perovskite solar cells(PSCs),combining regression and classification with Bayesian model selection and Havriliak-Negami(HN)modeling to resolve spectra into discrete,Lorentzian-like peaks.This time-domain decomposition offers a powerful alternative for identifying underlying physical processes,such as charge transfer,trap-assisted recombination,and ionic migration by directly extracting characteristic relaxation times(τ).In contrast to traditional equivalent circuit fitting or conventional DRT methods,which often yield broad and overlapping Gaussian-like peaks,our method enables sharper resolution of individual electrochemical signatures.Furthermore,we validated the framework using simulated EIS spectra for two distinct system types,determining the optimal number of peaks(Q)through statistical model selection.Applied to experimental PSC data under varying bias conditions,the approach helps to identify the voltage-dependent relaxation processes,including fast charge transfer(τ~10^(-6)s),intermediate trap-mediated recombination(τ~10^(-2)s),and slow ionic motion(τ~1 s).Lower-Q models fail to capture low-frequency features such as polarization and charge accumulation,while optimal Q yields accurate,physically meaningful representations of device behavior.This data-driven methodology highlights time-domain DRT as a rigorous and insightful tool for dissecting the complex kinetics that govern PSC performance.
基金the Deanship of Scientific Research at King Khalid University for funding this work through research groups program under grant number RGP2/86/42the ORSP of Pandit Deendayal Petroleum University for financial support+1 种基金the financial support from DST SERB(CRG/2018/000714)DST Nano Mission(DST/NM/NT/2018/174)。
文摘Development of novel materials with desirable properties remains at the forefront of modern scientific research.Machine 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 materials.Metal halide perovskites(MHPs)have been at the centre of attraction owing to their outstanding photophysical properties and rapid development in solar cell application.Therefore,the application of ML in the field of MHPs is also getting much attention to optimize the fabrication process and reduce the cost of processing.Here,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 discussed.We 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.
基金the ORSP of Pandit Deendayal Energy University and DST SERB(IPA/2021/96)for the financial support.
文摘The extensive research and development in perovskite solar cells (PSCs) have rekindled the hopes of converting solar energy into electricity.An elusive understanding of underlying mechanisms is required for the development of efficient PSCs.Over the years,Impedance Spectroscopy (IS) characterization,along with complementary techniques,has proven to be an effective way to understand and analyze the charge transport and recombination at interface and bulk of PSCs.The IS of PSCs have been analyzed,interpreted,and improvised continuously,revealing intricate details about the work.However,there is a lack of centralized source of these details,which make it tougher to account for the generalized approach to understand the device properties.The present work is focused on compiling the research done on various PSC device architectures via IS to construct a comprehensive foundation of information on impedance plots,equivalent circuits,and associated processes.
