Organic photovoltaics(OPVs)suitable for application in indoor lighting environments can power a wide range of internet of things(Io T)related electronic devices.The ternary structure has huge advantages in improving t...Organic photovoltaics(OPVs)suitable for application in indoor lighting environments can power a wide range of internet of things(Io T)related electronic devices.The ternary structure has huge advantages in improving the photovoltaic performance of OPVs,including broadening the light absorption,improving the charge transport,manipulating the energy loss(E_(loss))and so on.Herein,we use wide-bandgap photo-active materials,including the benzotriazole-based polymer donor(J52-F),chlorinated polymer donor(PM7)and A_(2)-A_1-D-A_1-A_(2)-structured acceptor(BTA3),to construct ternary OPVs for indoor light applications.Benefitting from the introduction of PM7 as the third component in J52-F:BTA3-based blend,a gratifying PCE of 20.04%with a high V_(OC)of 1.00 V can be obtained under the test conditions with an illumination of 300 lx from an LED lighting source with a color temperature of 3000 K.The excellent device performance is inseparable from the matched spectrum,enhanced light absorption and the reduced E_(loss),while the improved charge transport capability and suppression of carrier recombination also play an indelible role.Our work shows a potential material system to meet the requirement of devices applied under indoor light.Moreover,these findings demonstrate that designing multi-component OPVs is indeed a feasible way to further improve the performances of the photovoltaic energy conversion system for indoor applications.展开更多
The excellent ability of dye-sensitized solar cells(DSSCs)to capture ambient light and convert it into electric current makes them attractive power sources for indoor applications,including powering Internet of Things...The excellent ability of dye-sensitized solar cells(DSSCs)to capture ambient light and convert it into electric current makes them attractive power sources for indoor applications,including powering Internet of Things(IoT)devices.In this context,substantial research efforts have been devoted to the discovery of novel organic dyes able to harvest energy from a wide range of indoor light sources at different intensities.However,such activities are often based on trial-and-error procedures which are frequently expensive and time-consuming.Here,Machine Learning(ML)techniques and Density Functional Theory(DFT)methods have been combined in a two-stage approach,with the aim to accelerate the design of new,synthetically accessible organic dyes for indoor DSSC applications.By predicting the power conversion efficiency(PCE)under different indoor light sources and intensities,potentially high-performance organic dyes have been identified.展开更多
基金supported by the National Natural Science Foundation of China(51873007,51961165102,and 21835006)the Fundamental Research Funds for the Central Universities in China(2019MS025,2018MS032,2017MS027,2017XS084)。
文摘Organic photovoltaics(OPVs)suitable for application in indoor lighting environments can power a wide range of internet of things(Io T)related electronic devices.The ternary structure has huge advantages in improving the photovoltaic performance of OPVs,including broadening the light absorption,improving the charge transport,manipulating the energy loss(E_(loss))and so on.Herein,we use wide-bandgap photo-active materials,including the benzotriazole-based polymer donor(J52-F),chlorinated polymer donor(PM7)and A_(2)-A_1-D-A_1-A_(2)-structured acceptor(BTA3),to construct ternary OPVs for indoor light applications.Benefitting from the introduction of PM7 as the third component in J52-F:BTA3-based blend,a gratifying PCE of 20.04%with a high V_(OC)of 1.00 V can be obtained under the test conditions with an illumination of 300 lx from an LED lighting source with a color temperature of 3000 K.The excellent device performance is inseparable from the matched spectrum,enhanced light absorption and the reduced E_(loss),while the improved charge transport capability and suppression of carrier recombination also play an indelible role.Our work shows a potential material system to meet the requirement of devices applied under indoor light.Moreover,these findings demonstrate that designing multi-component OPVs is indeed a feasible way to further improve the performances of the photovoltaic energy conversion system for indoor applications.
基金the hpc@dbcf for providing computational resources and Regione Toscana for granting the Project INSIEME(Approcci di INtelligenza artificiale,Sintesi Innovative e valutazione di sostenibilitàEconomico-ambientale per lo sviluppo di nuovi Materiali per la conversione e stoccaggio dell’Energia solare)-Progetti di alta formazione-Fondo Sociale Europeo+2021-207(FSE+2021-2027).
文摘The excellent ability of dye-sensitized solar cells(DSSCs)to capture ambient light and convert it into electric current makes them attractive power sources for indoor applications,including powering Internet of Things(IoT)devices.In this context,substantial research efforts have been devoted to the discovery of novel organic dyes able to harvest energy from a wide range of indoor light sources at different intensities.However,such activities are often based on trial-and-error procedures which are frequently expensive and time-consuming.Here,Machine Learning(ML)techniques and Density Functional Theory(DFT)methods have been combined in a two-stage approach,with the aim to accelerate the design of new,synthetically accessible organic dyes for indoor DSSC applications.By predicting the power conversion efficiency(PCE)under different indoor light sources and intensities,potentially high-performance organic dyes have been identified.
