用改性膨润土去除水中四氯化碳的试验研究

为完善地下水中氯代烃污染物的处理技术,进行了用改性膨润土吸附模拟水样中四氯化碳的试验研究。试验结果表明：天然钙基膨润土经十六烷基三甲基溴化铵改性后,颗粒间间距明显增大,颗粒表面由亲水性变为疏水性,可有效吸附去除水中的四氯化碳,其适宜的吸附条件为膨润土投加量5 g/L、吸附时间2 h、吸附温度30 ℃。按此条件用改性膨润土处理某CCl₄含量为1.60 mg/L的实际四氯化碳污染地下水,CCl₄的去除率可达70%～80%。     

Small Molecules Functionalized Zinc Oxide Interlayers for High Performance Low-Temperature Carbon-Based CsPbI2Br Perovskite Solar Cells

The charge recombination resulting from bulk defects and interfacial energy level mismatch hinders the improvement of the power conversion efficiency (PCE) and stability of carbon-based inorganic perovskite solar cells (C-IPSCs). Herein, a series of small molecules including ethylenediaminetetraacetic acid (EDTA) and its derivatives (EDTA-Na and EDTA-K) are studied to functionalize the zinc oxide (ZnO) interlayers at the SnO₂/CsPbI₂Br buried interface to boost the photovoltaic performance of low-temperature C-IPSCs. This strategy can simultaneously passivate defects in ZnO and perovskite films, adjust interfacial energy level alignment, and release interfacial tensile stress, thereby improving interfacial contact, inhibiting ion migration, alleviating charge recombination, and promoting electron transport. As a result, a maximum PCE of 13.94% with a negligible hysteresis effect is obtained, which is one of the best results reported for low-temperature CsPbI₂Br C-IPSCs so far. Moreover, the optimized devices without encapsulation demonstrate greatly improved operational stability.     

High Quantum Efficiency Zn2+ Doped Lead Manganese Halide @PET Film Used for Wide Color Gamut Backlit Display

Organic–inorganic manganese halide with environmentally friendly properties has become a new candidate material for backlight display applications. In this article, tetraethylammonium bromide (C₈H₂₀N)₂MnBr₄ is synthesized by a simple room temperature evaporation method. The tetrahedral coordinated Mn²⁺ demonstrates a green emission peak at 523 nm and a commendable photoluminescence quantum yield (PLQY) of 81.7%. To improve its stability, different proportions of Zn²⁺ are incorporated, leading to the discovery of (C₈H₂₀N)₂Mn_0.95Zn_0.05Br₄ as the most stable variant with a high PLQY of 84.3%. Additionally, by utilizing a sandwich method and double-layer polyethylene terephthalate (PET) film encapsulation, the powder-to-binder ratio and thickness gradient are optimized, resulting in the ideal (C₈H₂₀N)₂Mn_0.95Zn_0.05Br₄@PET film with a powder-to-binder ratio of 1:2 and a thickness of 0.5 mm. Remarkably, the film exhibits superior stability against water, heat, and photo degradation. Finally, the light conversion film prepared from (C₈H₂₀N)₂Mn_0.95Zn_0.05Br₄@K₂SiF₆: Mn⁴⁺@PET composite material is applied to backlight display, and the color gamut covers 112% of NTSC 1953 and 83% of Rec. 2020. This study provides a feasible route for developing environmentally friendly, low-cost, and high-performance liquid crystal displays.     

Undoped Hole Transport Layer Toward Efficient and Stable Inorganic Perovskite Solar Cells

Numerous strategies have been practiced to improve the power conversion efficiency of CsPbI₂Br-based perovskite solar cells (PSCs), which definitely makes efficiency gradually approach the theoretical efficiency limit. However, sufficient device stability is still in urgent demand for commercialization, pushing to overcome some instability sources induced by hygroscopicity of spiro-OMeTAD and residual strain of perovskite layer. To address these issues, p-type semiconductor of PCPDTBT is used to replace spiro-OMeTAD, enabling dual functions of hole transport and strain regulation. On the one hand, undoped PCPDTBT performs excellent hole extraction and transport, while avoiding the perovskite degradation caused by the hygroscopicity of common additives. On the other hand, PCPDTBT assisted by a thermally spin-coating method compensates for the thermally-induced residual strain in perovskite layer owing to its high thermal expansion coefficient. Consequently, CsPbI₂Br-based PSCs with PCPDTBT layer achieve improved efficiency of 16.5% as well as enhanced stability. This study provides a simple and facile strategy to achieve efficient and stable CsPbI₂Br-based PSCs.     

An Improved Deep Structure for Accurately Brain Tumor Recognition

Brain neoplasms are recognized with a biopsy, which is not commonly done before decisive brain surgery. By using Convolutional Neural Networks (CNNs) and textural features, the process of diagnosing brain tumors by radiologists would be a noninvasive procedure. This paper proposes a features fusion model that can distinguish between no tumor and brain tumor types via a novel deep learning structure. The proposed model extracts Gray Level Co-occurrence Matrix (GLCM) textural features from MRI brain tumor images. Moreover, a deep neural network (DNN) model has been proposed to select the most salient features from the GLCM. Moreover, it manipulates the extraction of the additional high levels of salient features from a proposed CNN model. Finally, a fusion process has been utilized between these two types of features to form the input layer of additional proposed DNN model which is responsible for the recognition process. Two common datasets have been applied and tested, Br35H and FigShare datasets. The first dataset contains binary labels, while the second one splits the brain tumor into four classes; glioma, meningioma, pituitary, and no cancer. Moreover, several performance metrics have been evaluated from both datasets, including, accuracy, sensitivity, specificity, F-score, and training time. Experimental results show that the proposed methodology has achieved superior performance compared with the current state of art studies. The proposed system has achieved about 98.22% accuracy value in the case of the Br35H dataset however, an accuracy of 98.01% has been achieved in the case of the FigShare dataset.