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二氧化钛纳米管可作为载体,经过磁性金属修饰,制备陶瓷基金属纳米复合材料.本文利用二氧化钛纳米管为载体,经过硅烷化改性,钯催化沉积金属镍,制备一种陶瓷基/镍纳米复合材料,并利用TEM,XRD,FTIR和XPS等方法表征该复合材料的结构特征.结果表明二氧化钛纳米管表面镍沉积均匀,镍晶粒度尺寸为9.7nm,具有衍射宽化特征.沉积镍后,纳米管端部呈开口特征,仍具有空腔结构.在外加电磁场作用下(8~12GHz),复合材料具有较高的磁导率和磁损耗,但具有很低的介电损耗.该复合材料具有长径比高、比重小、重量轻、镍含量少等特点.人们还可在二氧化钛纳米管外部沉积其他金属或合金(如铁、钴),调控复合材料的电磁性能,用于开发薄而轻的电磁活性复合材料. 相似文献
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锂-硫电池具有高的理论质量/体积能量密度,因而成为最具发展潜力的高比能二次电池体系. 然而,由于硫载体通常采用轻质的碳纳米材料,导致硫基复合材料的振实密度和体积比容量均偏低,制约了电池体积能量密度的提升. 本文尝试采用具有高密度特征的钴酸锂(LiCoO2)作为硫的载体材料,以构筑高振实密度的硫基复合材料,进而提高硫正极的体积比容量. 研究显示,LiCoO2对可溶性多硫化物具有较强的吸附作用,能够促进硫的电化学转化,因而提高了硫的活性物质利用率和循环稳定性. 同时,由于具有高的振实密度(1.90 g·cm-3),S/LiCoO2复合材料的首周体积比容量高达1750.5 mAh·cm-3,是常规硫/碳复合材料的2.2倍. 因此,本文利用具有高密度特征的LiCoO2作为硫载体来提升硫复合材料的体积比容量,有助于实现锂-硫电池的高体积能量密度. 相似文献
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纳米材料具有较高的比表面积和较强的表面效应,在水处理领域展现出优异的净污性能,具有广阔的应用前景。将纳米颗粒负载于毫米级载体中制备毫纳结构复合材料,可有机结合纳米颗粒的高反应活性与载体的良好操作性,是突破纳米材料易聚团失活、难分离、稳定性差、潜在环境风险等工程应用瓶颈并实现规模化应用的重要技术手段。本文综述了毫纳结构复合材料的制备方法、结构特性及其在吸附和催化氧化除污性能及机制方面的研究进展,并从纳米颗粒的限域生长、限域吸附特性和限域催化氧化特性等方面阐述限域效应及载体-纳米颗粒的协同净污效应。最后,针对目前毫纳结构复合材料方向亟待解决的科学问题和实际应用挑战提出了展望,以期为推动纳米材料的实际应用提供一定的理论指导和技术参考。 相似文献
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超疏水材料因具有超高的拒水性以及自清洁能力而备受关注,但是在制备过程中也因所选用溶剂和低表面能物质不同给环境带来不同程度的压力。生物质材料可再生、价格低并且绿色无污染,常用于超疏水材料的制备。本文介绍了生物质基超疏水材料的制备方法,并按照制备技术中所用溶剂不同分类,将生物质基超疏水材料分为有机溶剂型、水基/半水基型、无溶剂型三类,同时分析了三种不同类型超疏水材料的优势以及劣势。最后,总结了制备环保型超疏水材料的方法,并且展望了生物质基超疏水材料未来的发展方向。 相似文献
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The last decade has witnessed multiple thermally responsive materials emerge as a significant class of stimuli‐responsive materials. These materials are elaborately designed and exert interesting properties. Herein, an overview of thermally responsive materials with respect to design strategies, fabrication procedures, and their applications is presented. Recently reported thermally responsive materials are highlighted. Then, applications of thermally responsive materials in bioimaging are summarized. 相似文献
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中空结构材料作为一类新兴功能材料,具有可调空腔、高比例活性表面及强化的物质传递等特性;当多组分及功能被整合与分区时,可实现中空结构材料的非对称结构(Janus)的拓扑演化.本文重点介绍若干典型中空结构材料,包括Janus中空材料的模板合成方法进展及中空结构材料在催化、储能、油/水分离与药物递送等领域的潜在应用,并展望了中空结构材料的未来发展趋势. 相似文献
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有机光伏材料与器件研究的新进展 总被引:4,自引:0,他引:4
近几年有机光伏电池应用研究发展迅猛。本文综述了有机光伏薄膜电池在材料(包括有机小分子材料与聚合物材料)、器件构造方面的最新进展,分析了有机聚合物光伏电池目前效率低的主要原因,并探讨了该领域进一步研究的方向和前景。 相似文献
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长余辉发光材料研究进展 总被引:48,自引:0,他引:48
90年代发现和发展起来的铝酸盐体系长余辉发光材料是一类重要的新 型能源材料和节能材料。本文主要综述了最近几年来铝酸盐体系中长人科辉发光研究进展。指出了氧化物体系长余辉发光材料的特点和优势,总结了新型长余辉发光材料的基质和激活剂种类、性质及其对稀土 离子 长余辉发光性能的影响和作用,概括了长余辉发光模型,并提出了今后研究和应用的发展方向。 相似文献
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《Chemical record (New York, N.Y.)》2018,18(2):118-136
The frequent occurrence of water pollution accidents and the leakage of organic pollutants have caused severe environmental and ecological crisis. It is thus highly imperative to find efficient materials to solve the problem. Inspired by the lotus leaf, superwetting materials are receiving increasing attention in the field of removal of organic pollutants from water. Various superwetting materials have been successfully generated and integrated into devices for removal of organic pollutants from water. On the basis of our previous work in the field, we summarized in this account the progress of removal of (1) floating and underwater insoluble, (2) emulsified insoluble, and (3) both insoluble and soluble organic pollutants from water using superwetting materials including superhydrophobic & superoleophilic materials, superhydrophilic & underwater superoleophobic materials, and materials with controllable wettability. The superwetting materials are in the forms of 2D porous materials, 3D porous materials and particles, etc. Finally, the current state and future challenges in this field are discussed. We hope this account could shed light on the design of novel superwetting materials for efficient removal of organic pollutants from water. 相似文献
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Dr. Ali Malek Dr. Mohammad Javad Eslamibidgoli Mehrdad Mokhtari Dr. Qianpu Wang Prof. Dr. Michael H. Eikerling Dr. Kourosh Malek 《Chemphyschem》2019,20(22):2946-2955
Similar to advancements gained from big data in genomics, security, internet of things, and e-commerce, the materials workflow could be made more efficient and prolific through advances in streamlining data sources, autonomous materials synthesis, rapid characterization, big data analytics, and self-learning algorithms. In electrochemical materials science, data sets are large, unstructured/heterogeneous, and difficult to process and analyze from a single data channel or platform. Computer-aided materials design together with advances in data mining, machine learning, and predictive analytics are expected to provide inexpensive and accelerated pathways towards tailor-made functionally optimized energy materials. Fundamental research in the field of electrochemical energy materials focuses primarily on complex interfacial phenomena and kinetic electrocatalytic processes. This perspective article critically assesses AI-driven modeling and computational approaches that are currently applied to those objects. An application-driven materials intelligence platform is introduced, and its functionalities are scrutinized considering the development of electrocatalyst materials for CO2 conversion as a use case. 相似文献