Theoretical Insight Into Factors Affecting Charge Dissociation At Donor/Acceptor Interface And Their Applications In Performance Prediction In Organic Solar Cells

Organic solar cells(OSCs)have been developed rapidly in recent years because of its low price,good flexibility,light weight,transparency and so on.The active layer,consisting of donor and acceptor materials,is one of the important components of OSC devices.The complex photophysical process in the active layer,especially the charge-separation(CS)ability at the donor/acceptor(D/A)interface,is one of the key factors affecting the power conversion efficiency(PCE)of OSC.However,the experimental and theoretical study of this process is controversial.In this paper,quantum chemistry,molecular dynamics and charge-transfer(CT)theory were used to analyze these underlying factors of the CS ability at the interface.At the same time,the correlations between these factors and the performance of OSCs were analyzed to further screen the descriptor combination suitable for the performance prediction of OSCs.In addition,the values of these factors in the nonfullerene(NFA)systems were considered to provide protocols for screening potential excellent NFA acceptors.1.Poly(3-hexylthiophene)(P3HT)-based OSCs have been developed in recent years.However,fewer NFAs with higher PCE than PC61 BM have been explored.In this contribution,the excited states were in-depth analyzed towards probing the particularities of superior P3HT/NFA systems.Multiple CT mechanisms involving intermolecular electric field(IEF),hot CT states and direct excitation of CT states were found,which suggests that more favorable CT pathways exist in these P3HT/NFA interfaces.Accordingly,the calculations on CT rates of all the investigated D/A interfaces further verified the positive effect of multiple CT pathways.In addition,the interesting hybrid Frenkel-CT states were found to be relevant with the stronger electrostatic surface potential(ESP)differences between donor and acceptor for these systems,which may provide a strategy for the design of high-efficiency OSCs.2.Charge dissociation in active layer is one of the key factors for the PCE of bulk heterojunction OSCs.Numerous CT mechanisms have been proposed based on one of few microscopic models.Here,this work explored possible CT mechanisms for 155 models of D/A interfaces,built via materials Dcv-1 and C60 as donor and acceptor,respectively.After the calculations of the key parameters related to the charge dissociation and statistical analysis for the correlation between these parameters,a more robust description of the charge dissociation in practical OSCs was obtained.The complicated relationship among the key parameters not only illustrates the important correlation between D/A stacking pattern and CT mechanism,but also suggests that different CT mechanisms become more likely depending on the specific arrangements of donor and acceptor.3.In this work,a dataset formed by 566 D/A pairs was analyzed,which are part of OSCs recently reported.Different descriptors in machine learning(ML)models were explored to predict the PCE of these cells.The investigated descriptors are classified into two main categories: structural(topology properties)and physical descriptors(energy-levels,molecular size,light absorption and mixing properties).The results suggest that ML predictions are more accurate when using both structural and physical descriptors,as opposed to only using one of them.The results suggest that ML predictions are also improved by using larger and more varied datasets.Importantly,the structural descriptors are the ones contributing the most to the ML models.Some physical properties are highly correlated with PCE,although they do not notably improve the ML prediction accuracy,as they carry information already encoded in the structural descriptors.Given that various descriptors have significantly different computational costs,the analysis presented here can be used as a guide to construct ML models that maximize predictive power and minimize computational costs for screening large sets of OSCs candidates.4.A large database of known organic semiconductors was considered and among them those compounds were identified with suitable computed electronic properties(orbital energies,excited-state energies,electron reorganization energies)determined from a set of experimentally characterized high-efficiency NFAs(such as Y6,ITIC and IDIC)and also they display ideal light absorption properties.This search leads to approximately 27 candidate compounds never before considered for OSC application.Then these compounds were modified to bring their computed solubility in line with that of the high-efficiency NFAs.This simple strategy,which relies on a few easily computable parameters and can be easily expanded to a larger set of molecules,enables the identification of completely new chemical families to be explored experimentally.