Alkoxy side chain engineering on the ß-position of the thienothiophene units of Y6 derivatives plays a vital role in improving photovoltaic performances with simultaneously increasing open-circuit voltage (Voc) and fill factor (FF). In this work, we prepared a series of asymmetric non-fullerene acceptors (NFAs) by introducing alkoxy side chains and phenoxy groups on the state-of-the-art Y6-derivative BTP-BO-4F. For the comparison, 2O-BO-4F with a symmetric alkoxy side chain on the outer thiophene units and BTP-PBO-4F with an asymmetric N-attached phenoxy alkyl chain on the pyrrole ring are synthesized from BTP-BO-4F. Thereafter, we construct four asymmetric NFAs by introducing different lengths of linear/branched alkoxy chains on the ß-position of the thienothiophene units of BTP-PBO-4F. The resulting NFAs, named L10-PBO, L12-PBO, B12-PBO, and B16-PBO (L = linear and B = branched alkoxy side chains), are collectively called OR-PBO-series. Unexpectedly, all OR-PBO NFAs exhibit strong edge-on molecular packing and weaker π-π interactions in the film state, which diminish the charge transfer in organic solar cell (OSC) devices. As a consequence, the optimal devices of OR-PBO-based binary blends show poor photovoltaic performances [power conversion efficiency (PCE) = 6.52-9.62%] in comparison with 2O-BO-4F (PCE = 12.42%) and BTP-PBO-4F (PCE = 15.30%) reference blends. Nevertheless, the OR-PBO-based binary devices show a higher Voc and smaller Vloss. Especially, B12-PBO- and B16-PBO-based devices achieve Voc over 1.00 V, which is the highest value of Y-series OSC devices to the best of our knowledge. Therefore, by utilizing higher Voc of OR-PBO binary blends, B12-PBO and B16-PBO are incorporated into the PM6:BTP-PBO-4F-based binary blend and fabricated ternary devices. As a result, the PM6:BTP-PBO-4F:B12-PBO ternary device delivers the best PCE of 15.60% with an increasing Voc and FF concurrently.
Graph-based semisupervised learning can explore the graph topology information behind the samples, becoming one of the most attractive research areas in machine learning in recent years. Nevertheless, existing graph-based methods also suffer from two shortcomings. On the one hand, the existing methods generate graphs in the original high-dimensional space, which are easily disturbed by noisy and redundancy features, resulting in low-quality constructed graphs that cannot accurately portray the relationships between data. On the other hand, most of the existing models are based on the Gaussian assumption, which cannot capture the local submanifold structure information of the data, thus reducing the discriminativeness of the learned low-dimensional representations. This article proposes a semisupervised subspace learning with adaptive pairwise graph embedding (APGE), which first builds a k1 -nearest neighbor graph on the labeled data to learn local discriminant embeddings for exploring the intrinsic structure of the non-Gaussian labeled data, i.e., the submanifold structure. Then, a k2 -nearest neighbor graph is constructed on all samples and mapped to GE learning to adaptively explore the global structure of all samples. Clustering unlabeled data and its corresponding labeled neighbors into the same submanifold, sharing the same label information, improves embedded data's discriminative ability. And the adaptive neighborhood learning method is used to learn the graph structure in the continuously optimized subspace to ensure that the optimal graph matrix and projection matrix are finally learned, which has strong robustness. Meanwhile, the rank constraint is added to the Laplacian matrix of the similarity matrix of all samples so that the connected components in the obtained similarity matrix are precisely equal to the number of classes in the sample, which makes the structure of the graph clearer and the relationship between the near-neighbor sample points more explicit. Finally, multiple experiments on several synthetic and real-world datasets show that the method performs well in exploring local structure and classification tasks.
Developing new electron transport layers has been an effective way to fabricate high-performance bulk-heterojunction organic solar cells (OSCs). Resolving the longstanding problems associated with commonly used zinc oxide (ZnO), such as electron traps and light-induced device deterioration, however, is still a great challenge. In this study, glycerol diglycidyl ether (GDE) and 1,4-butanesultone (BS) are blended with polyethyleneimine (PEI) to produce cross-linkable PEI-based materials, PEI-GDE and PEI-GDE-BS, which can function as alternative electron transport layers to replace conventional ZnO cathode-modifying layers in inverted OSCs. PEI-GDE and PEI-GDE-BS are amendable to low-temperature annealing processes to produce cross-linked films. The inverted device structure of ITO/ETL/PM6:BTP-BO-4F:PC71BM/MoO3/Ag was used to evaluate the effects of incorporating PEI-GDE and PEI-GDE-BS as electron transport materials. Compared with ZnO-based devices, the PEI-GDE- and PEI-GDE-BS-based devices exhibit significant improvements in photovoltaic performances due to smoother surface roughness, higher charge collection and exciton dissociation efficiencies, higher electron mobilities, and stronger π-π interactions. In particular, a PEI-GDE-BS-based device shows an outstanding power conversion efficiency (PCE) of 17.55% with a VOC of 0.83 V, a JSC of 27.88 mA/cm2, and an FF of 75.96%, which offers great possibilities in the applications of flexible solar cells.
The molecular design of wide-bandgap conjugated polymer donors (WB-CPDs) is a promising strategy for tuning the bulk heterojunction blend film morphologies to achieve high-performance organic photovoltaic (OPV) devices. Herein, we synthesize two WB-CPDs, namely, PBQ-H and PBQ-M, with and without methyl groups on the fused-dithieno[3,2-f:2',3'-h]quinoxaline (DTQx) moiety. We systematically investigate their structure-property relationship and OPV performances. The AFM and 2D grazing-incidence wide-angle X-ray scattering (GIWAXS) studies reveal that the PBQ-H:BO-4Cl BHJ blend shows strengthened aggregation behavior and stronger π-π stacking on face-on orientation compared with the PBQ-M:BO-4Cl BHJ blend, enhancing the phase separation, charge transport, and fill factor (FF). Blend film absorption spectra, however, show that the PBQ-H:BO-4Cl BHJ blend exhibits a lower absorption coefficient than that of the PBQ-M:BO-4Cl BHJ blend, which decreases the short-circuit current density (JSC). As a consequence, the optimized PBQ-H:BO-4Cl BHJ blend delivers a higher power conversion efficiency (PCE) of 12.88% with a JSC of 23.97 mA/cm2, an open-circuit voltage (VOC) of 0.86 V, and an FF of 62.46%, compared with the PBQ-M:BO-4Cl BHJ blend (PCE of 11.81% with a JSC of 24.78 mA/cm2, a VOC of 0.85 V, and an FF of 56.11%). Overall, this work demonstrates that alkyl group substitution on the DTQx moiety on the basis of WB-CPDs is critical for controlling the film morphology and thus obtaining high OPV performances.
In this work, two asymmetric non-fullerene acceptors (NFAs), BTP-EHBO-4F and BTP-PHD-4F, are designed to be applied in green-solvent-processable organic photovoltaics (OPVs). BTP-EHBO-4F and BTP-PHD-4F show good solubilities in green solvent o-xylene. As a result, PM6:BTP-EHBO-4F-based devices exhibit outstanding photovoltaic performances using o-xylene as a solvent. By comparison, due to the poor solubility of Y6 in o-xylene, PM6:Y6-based devices show poor performances. Owing to the favorable phase separation, molecule packing, and orientation observed from atomic force microscopy (AFM) and grazing-incidence wide-angle X-ray scattering (GIWAXS) measurements, PM6:BTP-PHD-4F-based devices demonstrate a PCE of 15.91% with a VOC of 0.87 V, a JSC of 25.64 mA/cm2, and an FF of 71.34%. Moreover, PM6:BTP-EHBO-4F-based devices exhibit an impressive PCE of 16.82% with a VOC of 0.85 V, a JSC of 26.12 mA/cm2, and an FF of 75.78%, which is outstanding for OPVs using o-xylene as a solvent.
