Swarming Microdroplets to a Dexterous Micromanipulator

Many astonishing biological collective behaviors exist in nature, and artificial microrobotic swarms have been developed by emulating these scenarios. However, these microswarms typically have single structures and lack the adaptability that many biological swarms exhibit to thrive in complex environments. Inspired by viscoelastic fire ant aggregations and using a combination of experiment and simulation, a strategy to trigger ferrofluid droplets into forming microswarms exhibiting both liquid-like and solid-like behaviors is reported. By spatiotemporally programming an applied magnetic field, microswarms can be liquefied to implement reversible elongation with a high aspect ratio and solidified into entireties to perform overturning and bending behaviors. It is demonstrated that reconfigurability enables the microswarm to be a mobile dexterous micromanipulator, acting not only as a soft “octopus arm” to explore a confined environment and grasp a targeted object but also adaptively navigate multiple terrains, such as uneven surfaces, curved grooves, complex mazes, high steps, narrow channels, and even wide gaps. This microrobotic swarm can reconfigure both shapes and tasks based on the demands of the environment, presenting novel solutions for a variety of applications.     

Ultralight and robustly compressible silica aerogel enhanced by AC/C sponge with high oil/water separation

Journal of Porous Materials - In recent years, oil spills and industrial organic pollutants have caused irreparable damage to the environment and biological ecosystems. Therefore, the treatment of...     

竹材液化墙体泡沫材料的阻燃改性

为提高竹材液化产物所制备的高轻发泡墙体材料的防火性能，分别采用材料内部添加和表面浸泡的方法进行阻燃改性，并评价不同阻燃剂及其添加量对发泡材料阻燃性能的影响。实验结果表明：在材料内部或表面添加选择的阻燃剂不会对材料自身形貌或组分产生明显影响，对材料的力学性能亦不会造成破坏，在材料内部添加3 g膨胀型凝胶-二氧化硅/聚磷酸铵核壳阻燃剂（MCAPP）后压缩强度达到了0.37 MPa，在材料表面浸泡聚硅氧烷后压缩强度达到了0.58 MPa，同时能提高材料的阻燃性能，在材料内部添加聚磷酸铵（M-APP）后极限氧指数提高到33.2%，比改性前提高3%。在材料表面浸泡膨胀型壳聚糖-蒙脱土-聚磷酸铵（CMAp）后点燃时间明显延长，极限氧指数最高达到了31.5%。     

四川省植被覆盖时空演变及未来变化趋势分析

四川省地处长江上游,是长江流域重要的生态屏障;解析该区域植被覆盖的时空演变特征,对长江上游的生态环境修护与治理具有重要意义。基于长时间序列的MODIS NDVI数据,解析2000~2016年间四川省植被的空间分布格局与时间变化特征;采用趋势分析法和Hurst指数,预测未来植被的变化趋势及持续性。结果表明:(1)四川省NDVI多年平均值为0.50,植被覆盖整体上呈现川东高于川西的空间分布特征;(2)2000~2016年间,四川省的NDVI值在0.48至0.53之间波动,整体呈上升趋势,增长率为0.002 5/a;(3)植被覆盖度在未来变化将呈现改善大于退化的趋势;植被持续性改善的面积大于持续性退化的面积。     

Tuning Parameter Selection Based on Blocked $$3\times 2$$3×2 Cross-Validation for High-Dimensional Linear Regression Model

Neural Processing Letters - In high-dimensional linear regression, selecting an appropriate tuning parameter is essential for the penalized linear models. From the perspective of the expected...     

In-line characterization of dispersion uniformity evolution during a twin-screw blending extrusion based on near-infrared spectroscopy

Properties of an immiscible polymer blend have been proved to be closely related to dispersion uniformity of the minor phase. At present, dispersion uniformity is difficult to evaluate during the blending process, resulting in hysteretic feedback. Aiming at this problem, this work utilized near-infrared (NIR) spectroscopy to in-line characterize dispersion uniformity evolution during a twin-screw extrusion. A multichannel NIR measurement system was set up and applied to evaluate the blending process of polypropylene and polyolefin elastomer (POE). Based on the NIR spectra collected at different positions of the extruder, five prediction models of POE content were established using the light gradient boosting machine algorithm. Dispersion uniformity was characterized through the fluctuation of the predicted content. The evolution of dispersion under such processing parameters was consistent with scanning electron microscopy.     

基于机器视觉的手机电池表面缺陷检测

针对手机电池表面质量人工检测情况,开发了电池表面缺陷无损检测系统软件。首先电池表面经过倾斜矫正、感兴趣区域提取和字符灰度值修改等预处理操作,通过基于灰度密度分布和灰度差的自适应阈值亮度法对感兴趣区域进行子图像遍历,融合有重合区域的缺陷子图像并滤除没有明显缺陷的区域;然后采用支持向量机多种类分类法,提取二值图像像素分布规律作为训练特征,识别电池表面缺陷种类;最后设计了人机交互界面,确定最佳的可变参数,实验测试缺陷识别率达95%以上。     

Ni@N-doped graphene nanosheets and CNTs hybrids modified separator as efficient polysulfide barrier for high-performance lithium sulfur batteries

Lithium-sulfur batteries (LSBs) have been regarded as one of the most promising energy storage systems to break through the upper limit of lithium-ion batteries. However, the rampant diffusions of soluble lithium polysulfides (LiPSs) in the electrolyte induced the shuttle effect between anode and cathode, resulting in low sulfur utilization, low energy efficiency and short cycling life. Herein, we prove the rational design and construction of Ni nanoparticles filled in vertically grown N-doped bamboo-like carbon nanotubes (CNTs) on graphene nanosheets (Ni@NG-CNTs) as efficient polysulfide barrier for high-performance LSBs. The unique design integrates graphene nanosheets and CNTs into hierarchical architectures with one-dimensional (1D) CNTs, two-dimensional (2D) ultrathin nanosheets and abundant carbon nanocages. This design provides large surface area for lithium polysulfides (LiPSs) adsorption, accelerates electron transport and enhances electrochemical redox of LiPSs. Benefiting from the unique structural features, the LSBs with the Ni@NG-CNTs as polysulfide barrier keep high reversible specific capacities of 309.1 and 265.0 mAh·g⁻¹ at 5 and 10 C rates after 500 cycles. This work provides a new strategy for constructing self-assembled hybrids of CNTs and graphene nanosheets with abundant carbon nanocages for high-performance LSBs.