Noble-free potassium-bimetallic catalysts supported on beta-zeolite for the simultaneous removal of NOx and soot from simulated diesel exhaust

This paper deals with the activity of the KCu and KCo catalysts supported on beta-zeolite for the simultaneous NO_x/soot removal from a simulated diesel exhaust, containing C₃H₆ as model hydrocarbon. In order to reveal the effect of potassium, the corresponding monometallic catalysts (Co/beta and Cu/beta) were analyzed and different potassium loadings were used. In addition, for comparative purpose, the performance of a platinum based catalyst (Pt/beta) was studied. All noble-free catalysts show, at 450 °C, a high activity for the simultaneous NO_x/soot removal. Among them, K1Cu/beta presents the best global performance at 350 and 450 °C achieving a high soot consumption rate (comparable to platinum catalysts) and the highest NO_x reduction. In contrast to platinum catalysts, K1Cu/beta has the advantage that the main reaction products are N₂ and CO_2.     

1-(2-氯苯基)-5(4H)-四唑啉酮的合成研究

1 (2 氯苯基 ) 5 (4H) 四唑啉酮 (Ⅰ)可由 2 氯硝基苯经三步合成反应制得。首先 ,2 氯硝基苯经铁粉还原得 2 氯苯胺 (Ⅱ) ,Ⅱ与碳酸二 (三氯甲基 )酯反应得 2 氯苯基异氰酸酯 (Ⅲ ) ,Ⅲ在DMF溶剂中 ,无水三氯化铝催化下与叠氮钠缩合得Ⅰ。三步收率分别为 90 %、80 %、90 % ,总收率为 6 5 %(以邻氯硝基苯计 ) ,产品质量分数达 95 %。     

基于1H NMR测定和基团贡献法预测石油馏分的热化学性质

测定了两种原油 2 0个石油馏分的¹H NMR谱和氢、碳元素含量等结构参数 ,以及馏分的燃烧焓、蒸发焓等热化学性质 .假设每个石油馏分仅由CH₃ 、CH₂ 、CH、ACH和C这 5种简单基团构成 ,基于¹H NMR测定和元素分析结果解出石油馏分平均分子结构中的基团数目 ,再用纯有机物的基团贡献法预测石油馏分的燃烧焓、蒸发焓 ,预测值与实验数据吻合良好     

氧氯化锆的生产及其在现代新能源中的应用

介绍了氧氯化锆（氧化锆）的生产原理和生产工艺，一酸一碱法是国内外普遍采用的方法，沸腾氯化法是国际上较为先进的锆英石分解方法，阐述了氧氯化锆（氧化锆）产品在镍氢动力电池负极材料（贮氢材料AB2）、燃料电池（特别是高温固体氧化物燃料电池），电池隔膜纸中的应用前景。     

D102的Ti(OC_2H_5)_4杂化材料的制备与性能研究

采用Sol-Gel法制备了D102的Ti(OC2H5)4杂化材料,探讨了材料的制备工艺条件,对材料进行了表面形态,热性能,光学性能等测试和分析。结果显示透光性和热稳定性较纯有机功能分子D102都有所提高,薄膜表面平整,无相分离。     

新型绝缘树脂及应用

本文介绍了FUCHEM系列无溶剂绝缘树脂的性能及应用，着重探讨了产品的阻燃、低收缩、高耐腐蚀、高耐热等级等特性。     

新型绝缘树脂的应用

本文介绍了FUCHEM系列无溶剂绝缘树脂的性能及应用，着重探讨了产品的阻燃，低收缩，高耐腐蚀，高耐热等级等特性。     

LoVis: Local Pattern Visualization for Model Refinement

Linear models are commonly used to identify trends in data. While it is an easy task to build linear models using pre‐selected variables, it is challenging to select the best variables from a large number of alternatives. Most metrics for selecting variables are global in nature, and thus not useful for identifying local patterns. In this work, we present an integrated framework with visual representations that allows the user to incrementally build and verify models in three model spaces that support local pattern discovery and summarization: model complementarity, model diversity, and model representivity. Visual representations are designed and implemented for each of the model spaces. Our visualizations enable the discovery of complementary variables, i.e., those that perform well in modeling different subsets of data points. They also support the isolation of local models based on a diversity measure. Furthermore, the system integrates a hierarchical representation to identify the outlier local trends and the local trends that share similar directions in the model space. A case study on financial risk analysis is discussed, followed by a user study.     

Evaluating the Impact of User Characteristics and Different Layouts on an Interactive Visualization for Decision Making

There is increasing evidence that user characteristics can have a significant impact on visualization effectiveness, suggesting that visualizations could be designed to better fit each user's specific needs. Most studies to date, however, have looked at static visualizations. Studies considering interactive visualizations have only looked at a limited number of user characteristics, and consider either low‐level tasks (e.g., value retrieval), or high‐level tasks (in particular: discovery), but not both. This paper contributes to this line of work by looking at the impact of a large set of user characteristics on user performance with interactive visualizations, for both low and high‐level tasks. We focus on interactive visualizations that support decision making, exemplified by a visualization known as Value Charts. We include in the study two versions of ValueCharts that differ in terms of layout, to ascertain whether layout mediates the impact of individual differences and could be considered as a form of personalization. Our key findings are that (i) performance with low and high‐level tasks is affected by different user characteristics, and (ii) users with low visual working memory perform better with a horizontal layout. We discuss how these findings can inform the provision of personalized support to visualization processing.     

Group‐in‐a‐Box Meta‐Layouts for Topological Clusters and Attribute‐Based Groups: Space‐Efficient Visualizations of Network Communities and Their Ties

An important part of network analysis is understanding community structures like topological clusters and attribute‐based groups. Standard approaches for showing communities using colour, shape, rectangular bounding boxes, convex hulls or force‐directed layout algorithms remain valuable, however our Group‐in‐a‐Box meta‐layouts add a fresh strategy for presenting community membership, internal structure and inter‐cluster relationships. This paper extends the basic Group‐in‐a‐Box meta‐layout, which uses a Treemap substrate of rectangular regions whose size is proportional to community size. When there are numerous inter‐community relationships, the proposed extensions help users view them more clearly: (1) the Croissant–Doughnut meta‐layout applies empirically determined rules for box arrangement to improve space utilization while still showing inter‐community relationships, and (2) the Force‐Directed layout arranges community boxes based on their aggregate ties at the cost of additional space. Our free and open source reference implementation in NodeXL includes heuristics to choose what we have found to be the preferable Group‐in‐a‐Box meta‐layout to show networks with varying numbers or sizes of communities. Case study examples, a pilot comparative user preference study (nine participants), and a readability measure‐based evaluation of 309 Twitter networks demonstrate the utility of the proposed meta‐layouts.