Properties and crystallization kinetics of poly(ether ether ketone)‐co‐poly(ether ether ketone ketone) block copolymers

A series of block copolymers composed of poly(ether ether ketone) (PEEK) and poly(ether ether ketone ketone) (PEEKK) components were prepared from their corresponding oligomers via a nucleophlilic aromatic substitution reaction. Various properties of the copolymers were investigated with differential scanning calorimetry (DSC) and a tensile testing machine. The results show that the copolymers exhibited no phase separation and that the relationship between the glass‐transition temperature (T_g) and the compositions of the copolymers approximately followed the formula T_g = T_g1X₁ + T_g2X₂, where T_g1 and T_g2 are the glass‐transition‐temperature values of PEEK and PEEKK, respectively, and X₁ and X₂ are the corresponding molar fractions of the PEEK and PEEKK segments in the copolymers, respectively. These copolymers showed good tensile properties. The crystallization kinetics of the copolymers were studied. The Avrami equation was used to describe the isothermal crystallization process. The nonisothermal crystallization was described by modified Avrami analysis by Jeziorny and by a combination of the Avrami and Ozawa equations. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 97: 1652–1658, 2005     

面向聚类的平面反射数据扰动方法

面向聚类的数据隐藏通常使用数据扰动技术防止敏感信息泄露。针对现有的面向聚类的数据扰动方法隐私保护度低的问题,提出一种基于平面反射的数据扰动方法,将发布对象的全部属性两两配对构成平面上的点,再随机选择一条直线,作每对属性关于直线的对称点,转换后的数据即为发布的数据。实验结果表明,这种方法具有较好的隐私保护度和聚类可用性,且对高维数据有良好的适应性。     

MC尼龙/纳米Al2O3复合材料力学性能的研究

采用原位聚合技术制备了纳米Al2O3增强单体浇铸(MC)尼龙复合材料,用扫描电子显微镜观察其断口形貌纳米粒子分布状况,并测试、分析了纳米Al2O3含量对对材料力学性能的影响。结果表明，采用原位聚合技术可获得的纳米粒子分布均匀、综合性能优良的纳米复合材料，当纳米Al2O3质量分数的4%时，MC尼龙/纳米Al2O3复合材料的拉伸强度、冲击强度和弯曲强度均达到最大值，分别比纯MC尼龙提高了19%、33%和11%。     

对乙酰氨基酚的合成与生产

综述了国内外近年来对药物扑热息痛（对乙酰氨基酚）合成与生产方法的研究，主要介绍了二步法、一步法和生化法。提出了无论从经济上还是从环保上考虑，一步催化合成法是当今扑热息痛合成的出路     

挤出机各段温度对开孔型橡塑共混材料性能的影响

研究开孔型橡塑共混材料在不同挤出加工工艺中结构形态及力学性能的变化规律。结果表明，挤出机的机头温度应稍高于发泡剂的分解温度，均化段温度要设在发泡剂分解温度区的低温段，在挤出加工工艺中，要特别注意挤出机均化段温度及机头温度的设定，温度设定不好会使发泡剂无法发挥作用。     

不同结合系统刚玉-方镁石-尖晶石浇注料的性能

对比研究了水泥结合和水合氧化铝结合的刚玉 -方镁石 -尖晶石浇注料的性能。结果表明 :二者相比 ,水合氧化铝结合浇注料的需水量较大 ,流动性较差 ,烧结致密化温度高 ,在 1 5 5 0℃下烧结后的强度和致密度低 ,但其抗热震性能及抗渣性能较好。     

Phase evolution and thermophysical properties of high-entropy RE2(Y0.2Yb0.2Nb0.2Ta0.2Ce0.2)2O7 oxides

Pursuing novel thermal barrier–coating materials with lower thermal conductivity and high-temperature stability can simultaneously improve the working efficiency and service temperature of a gas turbine. In this study, a series of high-entropy RE₂(Y_0.2Yb_0.2Nb_0.2Ta_0.2Ce_0.2)₂O₇ (RE = La, Nd, Sm, Gd, Dy, and Er) oxides were prepared though solid-state reaction. Through tuning the rare-earth cations, an order–disorder transition occurs from certain partially ordered weberite structure (C222₁) to disordered defective fluorite structure (Fm$\overline{3}$m). All the high-entropy RE₂(Y_0.2Yb_0.2Nb_0.2Ta_0.2Ce_0.2)₂O₇ oxides possess low thermal conductivity in the range of 0.91–1.34 W m⁻¹ K⁻¹ at room temperature, which can be attributed to increased lattice anharmonicity and disorder, resulting in additional phonon scattering. Herein, we proved that the incorporation of heterovalent cations at B-sites in high-entropy A₂B₂O₇ crystals is an effective strategy to reduce the thermal conductivity without compromising the decrease of oxygen vacancy. Moreover, the high-entropy RE₂(Y_0.2Yb_0.2Nb_0.2Ta_0.2Ce_0.2)₂O₇ oxides show the relatively higher thermal expansion coefficients of 10.3–10.7 × 10⁻⁶°C⁻¹ and excellent phase stability at elevated temperatures.     

塑料抗菌剂国内外开发现状及市场分析

阐述了抗菌剂的种类及其作用机理,详细介绍了塑料抗菌剂的国内外市场、开发现状及发展趋势,对今后国内市场进行了预测,并提出了我国塑料抗菌剂的发展建议。     

A hybrid recommendation algorithm adapted in e-learning environments

With the rapid development of online learning technology, a huge amount of e-learning materials have been generated which are highly heterogeneous and in various media formats. Besides, e-learning environments are highly dynamic with the ever increasing number of learning resources that are naturally distributed over the network. On the other hand, in the online learning scenario, it is very difficult for users without sufficient background knowledge to choose suitable resources for their learning. In this paper, a hybrid recommender system is proposed to recommend learning items in users’ learning processes. The proposed method consists of two steps: (1) discovering content-related item sets using item-based collaborative filtering (CF), and (2) applying the item sets to sequential pattern mining (SPM) algorithm to filter items according to common learning sequences. The two approaches are combined to recommend potentially useful learning items to guide users in their current learning processes. We also apply the proposed approach to a peer-to-peer learning environment for resource pre-fetching where a central directory of learning items is not available. Experiments are conducted in a centralized and a P2P online learning systems for the evaluation of the proposed method and the results show good performance of it.