Application of ultrasonic waves in activation of microcrystalline cellulose

In this work, microcrystalline cellulose (MCC) was activated with ultrasonic waves. The influences of ultrasonic treatment on the changes of supramolecular structures and morphology structure were studied by WAXS and SEM. The accessibility of the MCC was characterized by water retention value (WRV) and specific surficial area. The influence of ultrasonic treatment on the reactivity of MCC was investigated through the reaction of MCC being oxidized into 2,3‐diadehyde cellulose (DAC) by periodate sodium. The mechanism of the reactivity change of ultrasonically treated MCC was examined. The results showed that the degree of crystallinity of MCC decreased and the degree of polymerization showed little change after treatment with ultrasonic waves. The morphologial variation of the treated MCC was significant when compared with the untreated MCC, which contribute to the improvement of accessibility. The aldehyde content of DAC prepared from ultrasonically treated MCC was improved from 64.19 to 85.00%, indicating that the regioselective oxidation reactivity of MCC was significantly improved. The aldehyde content was found to first increase with time of ultrasonic treatment to a point, and then decrease as time progressed. In addition, the aldehyde content was found to increase with an increase in ultrasonic power. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

Facile synthesis of nitrogen and oxygen co-doped hierarchical porous carbon materials for high performance super capacitors

Journal of Porous Materials - Nitrogen and oxygen co-doped hierarchical porous carbons (NOPCs) is prepared by the pyrolysis of polyethylene glycol-200 (PEG) and triazine carbon forming agent (CFA)...     

弱酸性条件起始合成MUF树脂工艺研究

为了开发一种新的在"弱酸—弱碱—弱酸—弱碱"条件下合成三聚氰胺-尿素-甲醛树脂(MUF)的工艺,对弱酸性条件下起始合成MUF工艺进行研究.探讨了在不同酸性阶段加入的三聚氰胺对脲醛树脂性能的影响,找出最佳的三聚氰胺改性脲醛树脂的合成工艺.在最佳工艺基础上,评价三聚氰胺用量对MUF树脂性能的影响以及对胶合板性能的影响,并对MUF树脂和普通脲醛树脂进行红外分析.结果证明:三聚氰胺在甲醛与尿素一次缩聚之后加入,对脲醛树脂改性效果最好,其胶合板湿剪切强度与甲醛释放量之间达到较好平衡,胶合板甲醛释放量为0.63mg/L,湿剪切强度为1.03MPa.红外谱图分析表明:三聚氰胺分子以亚甲基与脲醛树脂分子链相连并有可能嵌入脲醛树脂分子链中,形成一定数量的醚键,使三聚氰胺在脲醛树脂中真正起到骨架作用.     

厌氧活性污泥PCR-DGGE图谱的优化

针对特种污泥PCR-DGGE图谱的优化一直是微生物分子生态学研究的重点.在反硝化抑制硫酸盐还原菌的研究中,研究厌氧硫酸盐还原污泥和反硝化污泥DNA的提取方法,应用通用引物958F/1401R扩增16S rDNA序列,探讨不同的退火温度对DGGE指纹图谱多样性影响,同时采用时间进程法对DGGE图谱进行优化.结果表明,采用PBS洗涤污泥和超声震荡有利于硫酸盐还原污泥DNA提取;采用958F/1401R为引物时,扩增片段大约500 bp,不同的退火温度对DGGE指纹图谱的多样性影响不显著;采用时间进程法可以很好地再现不同电泳阶段对样品的分离效果,最佳变性剂梯度为40%～60%,在130 V电压下,最佳电泳时间为5 h.     

新型细胞固定化载体强化白腐菌降解活性染料

为提高白腐真菌的产酶能力和后续对染料的降解效果,采用摇瓶试验研究新型细胞固定化载体——聚氨酯泡沫固定化白腐真菌后的锰过氧化物酶(MnP)产生情况以及后续对活性染料——活性艳红K-2BP的降解效果.结果显示,新型载体固定化培养白腐真菌的5d脱色率为95%,比悬浮培养7d的脱色率高15%.固定化培养产生的MnP酶活为936.61U/L,而悬浮培养的MnP仅为269.52U/L,并且酶活高峰期提前4d.另外,固定化培养体系中碳、氮源的消耗比悬浮培养快很多,而且固定化培养使得白腐真菌具有较高的H2O2产量.因此,新型细胞固定化载体强化白腐真菌降解活性染料的原因应归于这种培养体系碳、氮源的快速消耗而带来的MnP酶活的提高和高H2O2产量.     

两级数据融合算法在木材干燥过程中的应用

本文提出了一种基于RBF神经网络和证据理论的两级数据融合方法。利用RBF神经网络实现特征层数据融合,建立基本信任分配函数,具有最佳一致逼近特性,同时解决了D-S证据理论确定基本信任分配函数困难的问题。基于D-S证据理论的传感器故障诊断方法的研究,可有效地判断工业现场传感器的工作状态。实验结果表明该方法可正确定位并准确分离出木材含水率检测系统中失效传感器。     

Comparison of Skidding Performance of Small Track-type Experimental Prototype Skidder and J-50 Skidding Tractor

In this paper, field experimental comparison is made between a small track-type experimental prototype skidder and a J-50 skidding tractor. Experimental data, including skidding productivity, soil compaction on skidding trails, and damage rate of the residual trees, are analyzed. The results indicate that with the condition of scattered skidding area and low skidding volume per cycle, small track-type experimental prototype skidder has advantage on working and a higher skidding productivity. It makes lower soil compaction to the skidding trails in the depth of 0-5 cm, 5-10 cm, and 10-15 cm. Under the same work conditions, the damage rate of the residual trees made by small track-type experimental prototype skidder is only 1/5 of those made by J-50 type skidding tractor. The damage rate is reduced by 80%.     

Chemical vapor deposition and homogeneous nucleation in fluidized bed reactors: silicon from silane

Two models are developed to treat the simultaneous chemical vapor deposition (CVD) on solid particles and gas-phase nucleation of solid fines in a fluidized bed reactor. The first assumes both gas and solids to be well mixed. The second distinguishes between the grid, bubble and emulsion region of the bed. The population balance is used to describe the size distribution of fines, and the growth of large particles is ascribed to CVD and capture of fines. The results of the two models are compared to the experimental data from the JPL six-inch fluidized bed reactor. Good agreement between predictions and experimental data is established for the production rate, gas conversion and quantity of fines formed. The suppression of fines is most efficient when a CSTR flow pattern is approached in the bed.     

Real-time display and development of an aerometric data base for a field experiment

An innovative data center responsible for collecting, displaying, and analyzing near real-time meteorological and air quality measurements from a variety of sources was operated in Camarillo, California, during September–October 1985. This data center was part of a multi-million dollar study conducted for the South Central Coast Cooperative Monitoring Program sponsored by the Western Oil and Gas Association, a consortium of petroleum and fuel-producing organizations, to gain a better understanding of air quality conditions in the southern California coastal areas, and to produce a comprehensive data base for which coastal air quality models could be developed and evaluated.Led by the Atmospheric Science Center of SRI International, the program included a large number of contractor organizations responsible for collecting air quality measurements from land, sea, and air instrumentation for future analysis and model development. The data center integrated near real-time air quality and meteorological data with weather services forecasts to develop day-to-day environmental predictions governing the data collection activities.     

采用遗传算法优化最小二乘支持向量机参数的方法

支持向量机是建立在统计学习理论上的一种学习算法,较好地解决了小样本学习问题.由不同的参数和核函数构造的支持向量机在性能上存在很大差异,而在参数和核函数的选择上目前还没有明确的理论依据.针对支持向量机的参数选择问题,提出了一种采用遗传算法优化最小二乘支持向量机参数的方法.结合LS-SVMlab工具箱,在MATLAB实验平台的仿真实验表明,该方法提高了支持向量机的参数选择效率,得到的参数对测试样本的分类结果是最优的,从而避免了人为设定参数的不足,同时缩短了优化时间.