Thiocarbonyl-Based Hole Transport Materials with Enhanced Defect Passivation Ability for Efficient and Stable Perovskite Solar Cells.

Organic hole transporting materials (HTMs) are extensively studied in perovskite solar cells (PSCs). The HTMs directly contact the underlying perovskite material, and they play additional roles apart from hole transporting. Developing organic HTMs with defect passivation function has been proved to be an efficient strategy to construct efficient and stable PSCs. In this work, new organic molecules with thiocarbonyl (C═S) and carbonyl (C═O) functional groups are synthesized and applied as HTMs (named FN-S and FN-O). FN-S with C═S can be facilely obtained from FN-O containing C═O. Notably, the C═S in FN-S results in superior defect passivation ability compared to FN-O. Moreover, FN-S exhibits excellent hole extraction/transport capability. Conventional PSCs using FN-S as HTM show an impressive power conversion efficiency (PCE) of 23.25%, with excellent long-term stability and operational stability. This work indicates that simply converting C═O to C═S is an efficient way to improve the device performance by strengthening the defect passivation functionality.

Deep learning shows good reliability for automatic segmentation and volume measurement of brain hemorrhage, intraventricular extension, and peripheral edema.

OBJECTIVES: To evaluate for the first time the performance of a deep learning method based on no-new-Net for fully automated segmentation and volumetric measurements of intracerebral hemorrhage (ICH), intraventricular extension of intracerebral hemorrhage (IVH), and perihematomal edema (PHE) in primary ICH on CT. METHODS: Three hundred and eighty primary ICH patients who underwent CT at hospital arrival were divided into a training cohort (n = 300) and a validation cohort (n = 80). An independent cohort with 80 patients was used for testing. Ground truth (segmentation masks) was manually generated by radiologists. Model performance on lesion segmentation and volumetric measurement of ICH, IVH, and PHE were evaluated by comparing the model results with the segmentations performed by radiologists. RESULTS: In the test cohort, the Dice scores of lesion segmentation were 0.92, 0.79, and 0.71 for ICH, IVH, and PHE, respectively. The sensitivities were 0.93 for ICH, 0.88 for IVH, and 0.81 for PHE. The positive predictive values were 0.92, 0.76, and 0.69 for ICH, IVH, and PHE, respectively. Excellent concordance (concordance correlation coefficients [CCCs] ≥ 0.98) of ICH and IVH and good concordance of PHE (CCCs ≥ 0.92) were demonstrated between manually and automatically measured volumes. The model took approximately 15 s to provide automatic segmentation and volume analysis for each patient. CONCLUSION: Our model demonstrates good reliability for automatic segmentation and volume measurement of ICH, IVH, and PHE in primary ICH, which can be useful to reduce the effort and time of doctors to calculate volumes of ICH, IVH, and PHE. KEY POINTS: • Deep learning algorithms can provide automatic and reliable assessment of intracerebral hemorrhage, intraventricular hemorrhage, and perihematomal edema on CT. • Non-contrast CT-based deep learning method can be helpful to provide efficient and accurate measurements of ICH, IVH, and PHE in primary ICH patients, thereby reducing the effort and time of doctors to segment and calculate volumes of ICH, IVH, and PHE in primary ICH patients.

Organic Semiconductor Based on N, S-Containing Crown Ether Enabling Efficient and Stable Perovskite Solar Cells.

The uncoordinated lead cations are ubiquitous in perovskite films and severely affect the efficiency and stability of perovskite solar cells (PSCs). In this work, 15-crown-5 with various heteroatoms are connected to the organic semiconductor carbazole diphenylamine, and two new compounds, CDT-S and CDT-N, are developed to modify the Pb2+ defects in perovskite films through the anti-solvent method. Apart from the oxygen atoms, there are also N atoms on crown ether ring in CDT-N, and both S and N heteroatoms in CDT-S. The heteroatoms enhance the interaction between the crown ether-based semiconductors and the undercoordinated Pb2+ defect in perovskite. Particularly, the stronger interaction between S atoms and Pb2+ further enhances the defect passivation effect of CDT-S than CDT-N, thereby more effectively suppressing the non-radiative recombination of charge carriers. Finally, the efficiency of the device treated with CDT-S is up to 23.05 %. Moreover, the unencapsulated device based on CDT-S maintained 90.5 % of the initial efficiency after being stored under dark conditions for 1000 hours, demonstrating good long-term stability. Our work demonstrates that crown ethers are promising in perovskite solar cells, and the crown ether containing multiple heteroatoms could effectively improve both efficiency and stability of devices.

Lesion synthesis to improve intracranial hemorrhage detection and classification for CT images.

Computer-aided diagnosis (CAD) for intracranial hemorrhage (ICH) is needed due to its high mortality rate and time sensitivity. Training a stable and robust deep learning-based model usually requires enough training examples, which may be impractical in many real-world scenarios. Lesion synthesis offers a possible solution to solve this problem, especially for the issue of the lack of micro bleedings. In this paper, we propose a novel strategy to generate artificial lesions on non-lesion CT images so as to produce additional labeled training examples. Artificial masks in any location, size, or shape can be generated through Artificial Mask Generator (AMG) and then be converted into hemorrhage lesions through Lesion Synthesis Network (LSN). Images with and without artificial lesions are combined for training an ICH detection with a novel Residual Score. We evaluate our method by the auxiliary diagnosis task of ICH. Our experiments demonstrate that the proposed approach can improve the AUC value from 84% to 91% in the ICH detection task and from 89% to 96% in the classification task. Moreover, by adding artificial lesions of small size, the sensitivity of micro bleeding is remarkably improved from 49% to 70%. Besides, the proposed method overcomes the other three synthetic approaches by a large margin.