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A novel 2D benzodifuran (BDF)-based copolymer (PBDF-T1) is synthesized. Polymer solar cells fabricated with PBDF-T1 show high power conversion efficiency of 9.43% and fill factor of 77.4%, which is higher than the performance of its benzothiophene (BDT) counterpart (PBDT-T1). These results provide important progress for BDF-based copolymers and demonstrate that BDF-based copolymers can be competitive with the well-studied BDT counterparts via molecular structure design and device optimization.

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Terpolymers comprising three different components in the backbone have emerged as a new design strategy for conjugated polymers. However, compared with the backbone modification, less effort has been devoted to the alkyl side chain engineering, especially the subtle side chain modifications of random polymers. In this contribution, we designed and synthesized a series of random terpolymers, in which the subtle side chain regioregularity is used to finely tune the optical, electronic, and morphological properties. PB55 was found to outperform the other copolymers with better mixing with fullerene and higher photovoltaic performance. Moreover, the utilization of these random terpolymers in nonfullerene solar cells was investigated. A well-known nonfullerene acceptor, ITCPTC, was used as the acceptor. Among the terpolymers, PB55 yielded the best photovoltaic performance with an impressive PCE of ∼12.1%, representing the highest value reported in the literature so far for nonfullerene OSCs based on random terpolymers. This work demonstrates the importance of subtle side chain engineering of random terpolymers for high-performance organic solar cells.

Emerging evidence from lesion-symptom mapping (LSM) studies suggested that regional white matter lesions (WML) on strategic white matter (WM) fiber tracts are significantly associated with specific cognitive domains, independent of global WML burden. However, previous LSM investigations were mostly carried out in disease cohorts, with little evidence from community-based older individuals, making findings difficult to generalize. Moreover, most LSM studies applied a threshold to the probabilistic atlas, leading to the loss of information and threshold-dependent findings. Furthermore, it is still unclear whether associations between regional WML and cognition are independent of global grey matter (GM) and WM volumes, which have also been linked to cognition. In the current study, we undertook a region of interest (ROI) LSM study to examine the relationship between regional WML on strategic WM tracts and cognitive performance in a large community-based cohort of older individuals (N = 461; 70–90 years). WML were extracted using a publicly available pipeline, UBO Detector (https://cheba.unsw.edu.au/group/neuroimaging-pipeline). Mapping of WML to the WM atlas was undertaken using an automated TOolbox for Probabilistic MApping of Lesions (TOPMAL), which we introduce here, and is implemented in UBO Detector. The results show that different patterns of brain structural volumes in the ageing brain were associated with different cognitive domains. Regional WML were associated with processing speed, executive function, and global cognition, independent of total GM, WM and WML volumes. Moreover, regional WML explained more variance in executive function, compared to total GM, WM and WML volumes. The current study highlights the importance of studying regional WML in age-related cognitive decline.