Phase-Separated Polyzwitterionic Hydrogels with Tunable Sponge-Like Structures for Stable Solar Steam Generation

Solar steam generation (SSG) through hydrogel-based evaporators has shown great promise for freshwater production. However, developing hydrogel-based evaporators with stable SSG performance in high-salinity brines remains challenging. Herein, phase-separated polyzwitterionic hydrogel-based evaporators are presented with sponge-like structures comprising interconnected pores for stable SSG performance, which are fabricated by photopolymerization of sulfobetaine methacrylate (SBMA) in water-dimethyl sulfoxide (DMSO) mixed solvents. It is shown that driven by competitive adsorption, the structures of the resulting poly(sulfobetaine methacrylate) (PSBMA) hydrogels can be readily tuned by the volume ratio of DMSO to achieve phase separation. The optimized phase-separated PSBMA hydrogels, combining the unique anti-polyelectrolyte effects of polyzwitterionic hydrogels, demonstrate a rapid water transport capability in brines. After introducing photothermal polypyrrole particles on the surface of the phase-separated PSBMA hydrogel evaporators, a stable water evaporation rate of ≈2.024 kg m⁻² h⁻¹ and high solar-to-vapor efficiency of ≈97.5% in a 3.5 wt.% brine are obtained under simulated solar light irradiation (1.0 kW m⁻²). Surprisingly, the evaporation rates remain stable even under high-intensity solar irradiation (2.0 kW m⁻²). It is anticipated that the polyzwitterionic hydrogel evaporators with sponge-like porous structures will contribute to developing SSG technology for high-salinity seawater applications.     

Ultra-Stable and Sensitive Ultraviolet Photodetectors Based on Monocrystalline Perovskite Thin Films

The detection of ultraviolet (UV) radiation with effective performance and robust stability is essential to practical applications. Metal halide single-crystal perovskites (ABX₃) are promising next-generation materials for UV detection. The device performance of all-inorganic CsPbCl₃ photodetectors (PDs) is still limited by inner imperfection of crystals grown in solution. Here wafer-scale single-crystal CsPbCl₃ thin films are successfully grown by vapor-phase epitaxy method, and the as-constructed PDs under UV light illumination exhibit an ultralow dark current of 7.18 pA, ultrahigh ON/OFF ratio of ≈5.22 × 10⁵, competitive responsivity of 32.8 A W⁻¹, external quantum efficiency of 10867% and specific detectivity of 4.22 × 10¹² Jones. More importantly, they feature superb long-term stability toward moisture and oxygen within twenty-one months, good temperature tolerances at low and high temperatures. The ability of the photodetector arrays for excellent UV light imaging is further demonstrated.     

Tetrabutylammonium Bromide Functionalized Ti3C2Tx MXene as Versatile Cathode Buffer Layer for Efficient and Stable Inverted Perovskite Solar Cells

2D Ti₃C₂T_x MXene, possessing facile preparation, high electrical conductivity, flexibility, and solution processability, shows good application potential for enhancing device performance of perovskite solar cells (PVSCs). In this study, tetrabutylammonium bromide functionalized Ti₃C₂T_x (TBAB-Ti₃C₂T_x) is developed as cathode buffer layer (CBL) to regulate the PCBM/Ag cathode interfacial property for the first time. By virtue of the charge transfer from TBAB to Ti₃C₂T_x demonstrated by electron paramagnetic resonance and density functional theory, the TBAB-Ti₃C₂T_x CBL with high electrical conductivity exhibits significantly reduced work function of 3.9 eV, which enables optimization of energy level alignment and enhancement of charge extraction. Moreover, the TBAB-Ti₃C₂T_x CBL can effectively inhibit the migration of iodine ions from perovskite layer to Ag cathode, which synergistically suppresses defect states and reduce charge recombination. Consequently, utilizing MAPbI₃ perovskite without post-treatment, the TBAB-Ti₃C₂T_x based device exhibits a dramatically improved power conversion efficiency of 21.65% with significantly improved operational stability, which is one of the best efficiencies reported for the devices based on MAPbI₃/PCBM with different CBLs. These results indicate that TBAB-Ti₃C₂T_x shall be a promising CBL for high-performance inverted PVSCs and inspire the further applications of quaternary ammonium functionalized MXenes in PVSCs.     

Intercalative Motifs-Induced Space Confinement and Bonding Covalency Enhancement Enable Ultrafast and Large Sodium Storage

Alloying-type metal sulfides with high theoretical capacities are promising anodes for sodium-ion batteries, but suffer from sluggish sodiation kinetics and huge volume expansion. Introducing intercalative motifs into alloying-type metal sulfides is an efficient strategy to solve the above issues. Herein, robust intercalative In S motifs are grafted to high-capacity layered Bi₂S₃ to form a cation-disordered (BiIn)₂S₃, synergistically realizing high-rate and large-capacity sodium storage. The In S motif with strong bonding serves as a space-confinement unit to buffer the volume expansion, maintaining superior structural stability. Moreover, the grafted high-metallicity Indium increases the bonding covalency of Bi S, realizing controllable reconstruction of Bi S bond during cycling to effectively prevent the migration and aggregation of atomic Bi. The novel (BiIn)₂S₃ anode delivers a high capacity of 537 mAh g⁻¹ at 0.4 C and a superior high-rate stability of 247 mAh g⁻¹ at 40 C over 10000 cycles. Further in situ and ex situ characterizations reveal the in-depth reaction mechanism and the breakage and formation of reversible Bi S bonds. The proposed space confinement and bonding covalency enhancement strategy via grafting intercalative motifs can be conducive to developing novel high-rate and large-capacity anodes.     

Freely Tailorable Yolk-Shell Encapsulation: Versatile Applications in Ultralow-k Dielectric,Drug Delivery Systems,and Catalysts

Herein, a facile, controllable, and versatile method is reported to prepare monodisperse yolk-shell and yolk-multishell silica nanoparticles (NPs) with mesoporous shells by a novel selective etching strategy. The mechanism of selective etching based on fluoride-silica chemistry is investigated in detail and thus provides a fundamentally novel principle for the fabrication of yolk-shell NPs. Specifically, this unprecedented and versatile synthesis strategy can be used to encapsulate essentially any silica-based, carbon-based, metal, metal oxide, or other possible NPs. Noteworthy is that most of the yolk-shell mesoporous silica (mSiO₂) NPs are prepared for the first time. To demonstrate the major structural and compositional advantages of the designed yolk-shell NPs, their applications in the fields of ultralow-dielectric constant (k) materials, drug delivery systems, and catalysts were explored. In detail, the lowest k value of the prepared yolk-shellordered mesoporous silica@mSiO₂/fluorinated polybenzoxazole composite films is 2.02; The obtained yolk-shell mSiO₂/C@mSiO₂/C NPs possess high hydrophilicity and pH-responsive sensitivity; The conversion of the catalytic reaction of the designed magnetic yolk-shell hollow Fe₃O₄@SiO₂/Au@mSiO₂ NPs at 20 min is 97% with a high conversion rate (92%) and recyclability even after 10 reuses. This innovative work lays a solid foundation for freely tailorable yolk-shell encapsulation and will greatly stimulate more efforts devoted to relevant research and development.     

软件缺陷预测模型间的比较实验: 问题、进展与挑战

近年来,研究者提出了大量的软件缺陷预测模型,新模型往往通过与过往模型进行比较实验来表明其有效性.然而,研究者在设计新旧模型间的比较实验时并没有达成共识,不同的工作往往采用不完全一致的比较实验设置,这可能致使在对比模型时得到误导性结论,最终错失提升缺陷预测能力的机会.对近年来国内外学者所做的缺陷预测模型间的比较实验进行系统性的总结:首先,阐述缺陷预测模型间的比较实验的研究问题;然后,分别从缺陷数据集、数据集划分、基线模型、性能指标、分类阈值这5个方面对现有的比较实验进行总结;最后,指出目前在进行缺陷预测模型间比较实验时面临的挑战,并给出建议的研究方向.     

结合跨层特征融合与级联检测器的防震锤缺陷检测

目的 防震锤可以减少输电线路的周期性震动以降低线路的疲劳损害,定期对防震锤进行巡检非常必要。针对目前无人机巡检输电线路所得航拍图像背景复杂,而种类较多、形状各异以及特性不一的防震锤在航拍图像中占据像素面积很小,导致防震锤检测过程中出现的检测精度低、无法确定缺陷类型等问题,提出了一种结合跨层特征融合和级联检测器的防震锤缺陷检测方法。方法 本文使用无人机对防震锤部件巡检的航拍图像进行数据扩充建立防震锤缺陷检测数据集,并划分了4种缺陷类型,为研究提供了数据基础。首先,以VGG16（Visual GeometryGroup 16-layer network）为基础对1、3、5层特征进行特征融合得到特征图,平衡了语义信息和空间特征;其次,使用3个级联检测器对目标进行分类定位,减小了交并比（intersection over union,IoU）阈值对网络性能的影响;最后,将非极大值抑制法替换为Soft-NMS（soft non-maximum suppression）算法,去除边界框保留了最佳结果。结果 在自建数据集上验证网络模型对4种防震锤缺陷类型的检测效果,与现有基于深度学习的其他6种先进算法相比,本文算法的平均准确率比Fast R-CNN（fast region-based convolutional network）、Faster R-CNN、YOLOv4（you only look onceversion 4）分别提高了13.5%、3.4%、5.8%,比SSD300（single shot MultiBox detector 300）、YOLOv3、RetinaNet分别提高了9.5%、8.5%、8%。与Faster R-CNN相比,本文方法的误检率降低了5.61%,漏检率降低了3.01%。结论 本文提出的防震锤缺陷检测方法对不同背景、不同光照、不同角度、不同尺度、不同种类和不同缺陷种类的防震锤均有较好的检测结果,不但可以更好地提取防震锤的特征,而且还能提高分类和位置预测网络的定位精度,从而有效提高了防震锤缺陷检测算法的准确率,在满足防震锤巡检工作实际检测要求的同时还具有较好的鲁棒性和有效性。     

基于机器学习的超声造影分析综述

超声造影（Contrast-enhanced ultrasound, CEUS）通过外周静脉注入超声造影剂,显著增强来自肿瘤微血管的血流信号,便于临床医生以实时、动态的方式评估肿瘤血管生成、周边浸润等,广泛应用于多器官病变诊断、预后评估和治疗方案规划等方面。近年来,以深度学习为代表的机器学习方法快速发展,为动态超声造影智能分析带来新的机遇。深度学习方法很大程度上拓宽了超声造影临床应用范围,提高了其诊疗效能。但与常规超声影像类似,超声造影仍然存在斑点噪声、呼吸运动干扰和标准化程度低等问题,使得动态灌注时间、空间信息挖掘面临挑战。本文系统性回顾了近年来超声造影智能分析相关工作,涵盖良恶性鉴别、恶性分级、疗效预测和诊疗方案选择等方面应用,总结了当前影像组学及深度学习方法在超声造影分析领域的最新进展,并指出当前研究的局限性和未来发展方向。     

Extended state observer-based finite-region control for 2-D Markov jump systems

In this article, an extended state observer-based finite-region control scheme is presented for two-dimensional Markov jump systems with unknown mismatched disturbances. The mathematical model of the two-dimensional Markov jump systems is built on the well-known Roesser model. By establishing special recursive formulas and utilizing the 2-D Lyapunov function theory, sufficient conditions are obtained, which prove that the resultant system is finite-region bounded, if some linear matrix inequalities are achieved. Then, we provide an algorithm to solve the extended state observer-based controller gains. With the proposed control scheme, the external disturbances can be actively rejected from the system outputs. To conclude, a numerical example based on the Darboux equation is provided to demonstrate the validity and effectiveness of the devised control scheme.     

基于改进YOLOX-s的安全帽检测

在施工现场中, 发生过许多高空坠落事故, 因此在施工现场佩戴安全帽是十分有必要的. 针对安全帽佩戴状况检测中遇到的小目标样本缺检、漏检的情况, 提出一种基于YOLOX-s的改进算法. 首先, 在Neck层引入主干特征提取网络中的160×160特征层进行特征融合, 并且增加了一个针对小目标的检测头; 其次, 采用SIoU损失函数计算损失值, 使得网络在训练过程中考虑的损失项更加全面; 并且采用varifocal loss函数来计算置信度损失值, 进一步改善训练过程中存在的正样本与困难样本不均衡的问题, 最后, 采用CA (coordinate attention)注意力机制来增强模型的特征表达能力. 实验结果表明, 通过对Neck层与检测层、损失函数的优化以及引入CA注意力机制, 使得网络在训练过程中收敛与回归性能更佳. 改进后的算法的mAP值为95.57%, 相较于YOLOv3及原YOLOX-s算法在mAP值上分别提高了17.11%、3.59%. 改进后的算法检测速度为54.73帧/s, 符合实时检测速度要求.