Enhanced thermal shrinkage behavior of phenolic-derived carbon aerogel-reinforced by HNTs with superior compressive strength performance

A novel carbon/m-HNTs composite aerogel was synthesized by introducing the modified halloysite nanotubes (m-HNTs) into phenolic (PR) aerogels through chemical grafting, followed with carbonization treatment. In order to explore the best proportion of HNTs to phenolic, the micromorphology of PR/m-HNTs were investigated by SEM before carbonization, confirming 10 wt% of m-HNTs is most beneficial to the porous network of aerogels. The interaction between PR and HNTs was studied by FTIR spectra, and microstructure evolution of the target product-carbon/m-HNTs composite aerogel were illustrated by SEM and TEM techniques. SEM patterns indicated that the carbon/m-HNTs aerogels maintain a stable porous structure at 1000 °C (carbonization temperature), while a ~20 nm carbon layer was formed around m-HNTs generating an integral unit through TEM analysis. Specific surface area and pore size distribution of composite aerogels were analyzed based on mercury intrusion porosimetry and N₂ adsorption–desorption method, the obtained results stayed around 500 m²g^?1 and 1.00 cm³g^?1 (pore volume) without significant discrepancy, compared with pure aerogel, showing the uniformity of pore size. The weight loss rate (26.76%) decreased greatly compared with pure aerogel, at the same time, the best volumetric shrinkage rate was only 30.83%, contributed by the existence of HNTs supporting the neighbor structure to avoid over-shrinking. The highest compressive strength reached to 4.43 MPa, while the data of pure aerogel was only 1.52 MPa, demonstrating the excellent mechanical property of carbon/m-HNTs aerogels.     

Study on Runoff Control Effect of Different Drainage Schemes in Sponge Airport

Water Resources Management - The low impact development (LID) concept aims to control storm runoff and pollution through decentralized, small-scale source control to bring the development area as...     

Revealing Electrical-Poling-Induced Polarization Potential in Hybrid Perovskite Photodetectors

Despite recent rapid advances in metal halide perovskites for use in optoelectronics, the fundamental understanding of the electrical-poling-induced ion migration, accounting for many unusual attributes and thus performance in perovskite-based devices, remain comparatively elusive. Herein, the electrical-poling-promoted polarization potential is reported for rendering hybrid organic–inorganic perovskite photodetectors with high photocurrent and fast response time, displaying a tenfold enhancement in the photocurrent and a twofold decrease in the response time after an external electric field poling. First, a robust meniscus-assisted solution-printing strategy is employed to facilitate the oriented perovskite crystals over a large area. Subsequently, the electrical poling invokes the ion migration within perovskite crystals, thus inducing a polarization potential, as substantiated by the surface potential change assessed by Kelvin probe force microscopy. Such electrical-poling-induced polarization potential is responsible for the markedly enhanced photocurrent and largely shortened response time. This work presents new insights into the electrical-poling-triggered ion migration and, in turn, polarization potential as well as into the implication of the latter for optoelectronic devices with greater performance. As such, the utilization of ion-migration-produced polarization potential may represent an important endeavor toward a wide range of high-performance perovskite-based photodetectors, solar cells, transistors, scintillators, etc.     

河南省灵宝市董家埝银矿原生晕特征及地质意义

董家埝银矿是豫西小秦岭矿集区南成矿带目前发现的唯一大型矿床。为了矿床深部勘查工作的顺利进行,了解有用元素在垂向上的变化规律,选用原生晕地球化学方法,通过典型矿床剖面的原生晕特征研究,实现对深部矿体变化趋势的判断。经计算,确定As、Sb、Ag、Au、Cu、Pb、Zn、Co和Mo等9种元素可作为指示元素,其中As和Sb为前缘晕指示元素,Ag、Au、Cu、Pb和Zn为近矿晕指示元素,Co和Mo为尾晕指示元素。分带指数和浓集指数2种方法计算得出的元素在分带序列上的位置总体趋势一致。用分带指数法确定的主矿体自上而下的原生晕轴向分带序列为Co-Mo-Cu-Au-Sb-Zn-Pb-Ag-As,出现"反分带"现象。结合原生晕地球化学参数变化特征、矿体剥蚀程度研究和理想模型,预测M1-I主矿体向深部仍有较大的延伸。研究成果可以为区域同类型矿化地质体深部的趋势判断和决策提供参考。     

Achieving Rich and Active Alkaline Hydrogen Evolution Heterostructures via Interface Engineering on 2D 1T‐MoS2 Quantum Sheets

Large‐scale production of hydrogen from water‐alkali electrolyzers is impeded by the sluggish kinetics of hydrogen evolution reaction (HER) electrocatalysts. The hybridization of an acid‐active HER catalyst with a cocatalyst at the nanoscale helps boost HER kinetics in alkaline media. Here, it is demonstrated that 1T–MoS₂ nanosheet edges (instead of basal planes) decorated by metal hydroxides form highly active ${\text{edge}}_{{\text{1T‐MoS}}_{\text{2}}}$/ ${\text{edge}}_{\text{Ni}{(\text{OH})}_{\text{2}}}$ heterostructures, which significantly enhance HER performance in alkaline media. Featured with rich ${\text{edge}}_{{\text{1T‐MoS}}_{\text{2}}}$/ ${\text{edge}}_{\text{Ni}{(\text{OH})}_{\text{2}}}$ sites, the fabricated 1T–MoS₂ QS/Ni(OH)₂ hybrid (quantum sized 1T–MoS₂ sheets decorated with Ni(OH)₂ via interface engineering) only requires overpotentials of 57 and 112 mV to drive HER current densities of 10 and 100 mA cm^?2, respectively, and has a low Tafel slope of 30 mV dec^?1 in 1 m KOH. So far, this is the best performance for MoS₂‐based electrocatalysts and the 1T–MoS₂ QS/Ni(OH)₂ hybrid is among the best‐performing non‐Pt alkaline HER electrocatalysts known. The HER process is durable for 100 h at current densities up to 500 mA cm^?2. This work not only provides an active, cost‐effective, and robust alkaline HER electrocatalyst, but also demonstrates a design strategy for preparing high‐performance catalysts based on edge‐rich 2D quantum sheets for other catalytic reactions.     

How Cells Communicate with Each Other in the Tumor Microenvironment: Suggestions to Design Novel Therapeutic Strategies in Cancer Disease

Connexin- and pannexin (Panx)-formed hemichannels (HCs) and gap junctions (GJs) operate an interaction with the extracellular matrix and GJ intercellular communication (GJIC), and on account of this they are involved in cancer onset and progression towards invasiveness and metastatization. When we deal with cancer, it is not correct to omit the immune system, as well as neglecting its role in resisting or succumbing to formation and progression of incipient neoplasia until the formation of micrometastasis, nevertheless what really occurs in the tumor microenvironment (TME), which are the main players and which are the tumor or body allies, is still unclear. The goal of this article is to discuss how the pivotal players act, which can enhance or contrast cancer progression during two important process: “Activating Invasion and Metastasis” and the “Avoiding Immune Destruction”, with a particular emphasis on the interplay among GJIC, Panx-HCs, and the purinergic system in the TME without disregarding the inflammasome and cytokines thereof derived. In particular, the complex and contrasting roles of Panx1/P2X7R signalosome in tumor facilitation and/or inhibition is discussed in regard to the early/late phases of the carcinogenesis. Finally, considering this complex interplay in the TME between cancer cells, stromal cells, immune cells, and focusing on their means of communication, we should be capable of revealing harmful messages that help the cancer growth and transform them in body allies, thus designing novel therapeutic strategies to fight cancer in a personalized manner.     

A Student's t-based density peaks clustering with superpixel segmentation (tDPCSS) method for image color clustering

Image color clustering is a basic technique in image processing and computer vision, which is often applied in image segmentation, color transfer, contrast enhancement, object detection, skin color capture, and so forth. Various clustering algorithms have been employed for image color clustering in recent years. However, most of the algorithms require a large amount of memory or a predetermined number of clusters. In addition, some of the existing algorithms are sensitive to the parameter configurations. In order to tackle the above problems, we propose an image color clustering method named Student's t-based density peaks clustering with superpixel segmentation (tDPCSS), which can automatically obtain clustering results, without requiring a large amount of memory, and is not dependent on the parameters of the algorithm or the number of clusters. In tDPCSS, superpixels are obtained based on automatic and constrained simple non-iterative clustering, to automatically decrease the image data volume. A Student's t kernel function and a cluster center selection method are adopted to eliminate the dependence of the density peak clustering on parameters and the number of clusters, respectively. The experiments undertaken in this study confirmed that the proposed approach outperforms k-means, fuzzy c-means, mean-shift clustering, and density peak clustering with superpixel segmentation in the accuracy of the cluster centers and the validity of the clustering results.     

面部运动单元检测研究综述

面部运动单元检测旨在让计算机从给定的人脸图像或视频中自动检测需要关注的运动单元目标。经过二十多年的研究，尤其是近年来越来越多的面部运动单元数据库的建立和深度学习的兴起，面部运动单元检测技术发展迅速。首先，阐述了面部运动单元的基本概念，介绍了已有的常用面部运动单元检测数据库，概括了包括预处理、特征提取、分类器学习等步骤在内的传统检测方法；然后针对区域学习、面部运动单元关联学习、弱监督学习等几个关键研究方向进行了系统性的回顾梳理与分析；最后讨论了目前面部运动单元检测研究存在的不足以及未来潜在的发展方向。