Graft copolymerization of styrene and acrylonitrile onto EPDM

Acrylonitrile–EPDM–styrene (AES) graft copolymers were synthesized by solution graft polymerization of styrene (St) and acrylonitrile (AN) onto EPDM in an n‐hexane/benzene solvent with benzoyl peroxide (BPO) as an initiator. The structure changes were studied by an FTIR spectrophotometer. The grafting parameters were calculated gravimetrically. The influence of the polymerization conditions, such as the reaction time, concentration of the initiator, EPDM content, and weight ratio of St/AN, on the structure of the products was investigated. It was found that a proper initiator concentration and EPDM content will give a high grafting ratio of the AES resin. The thermal property of the copolymer was studied using programmed thermogravimetric analysis (TGA). The results showed that the copolymer has a better heat‐resistant property than that of ABS, especially for the initial decomposition temperature (T_in) and the maximum weight loss rate temperature (T_max). Also, the mechanism of the graft reaction was discussed. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 86: 428–432, 2002     

脱乙烷系统参数优化

吉化300kt/a乙烯装置脱乙烷系统采用德国Linde公司双塔双压前脱乙烷技术，自1996年开始以来，运行良好，通过工程技术人员近两年的探索实践，对其工艺参数做了较大的优化调整，取得了较好的经济效益。     

Artificial neural network approaches on composition-property relationships of jet fuels based on GC-MS

The relationships of composition-properties of 80 jet fuels concerning chemical compositions and several specification properties including density, flashpoint, freezing point, aniline point and net heat of combustion were studied. The chemical compositions of the jet fuels were determined by GC-MS, and grouped into eight classes of hydrocarbon compounds, including n-paraffins, isoparaffins, monocyclopraffins, dicyclopraffins, alkylbenzens, naphthalenes, tetralins, hydroaromatics. Several quantitative composition-property relationships were developed with three artificial neural network (ANN) approaches, including single-layer feedforward neural network (SLFNN), multiple layer feedforward neural network (MLFNN) and general regressed neural network (GRNN). It was found that SLFNNs are adequate to predict density, freezing point and net heat of combustion, while MLFNNs produce better results as far as the flash point and aniline point prediction are concerned. Comparisons with the multiple linear regression (MLR) correlations reported and the standard ASTM methods showed that ANN approaches of composition-property relationships are significant improvement on MLR correlations, and are comparable to the standard ASTM methods.     

强化单螺杆挤出机内层流混合的方法

综述了单螺杆挤出机内聚合物熔体层流混合机理的研究进展，对提高混合的措施进行了分析总结，指出了进一步强化混合效果的方法。     

磺化聚芳醚酮酮催化合成顺丁烯二酸二丁酯

以交联的聚芳醚酮酮和20％发烟硫酸合成了磺化聚芳醚酮酮树脂，并用于顺丁烯二酸酐和正丁醇的催化酯化，最佳条件：醇：酐为2．5：1（物质的量比）；催化剂用量为2．5g，反应温度140－150℃，反应时间7h ，酯化率96．4％。气相色谱分析结果：顺丁烯二酸二丁酯的含量达99．96％，催化剂易回收且可重复使用。     

单螺杆混沌挤出过程周期性行为数值模拟

建立了混沌单螺杆挤出机计量段物理和数学模型。定义了更合理的边界条件,采用Carreau本构方程,采用有限体积方法对聚合物熔体在螺槽内流动的周期性效应进行了数值模拟分析。得到了不同位置的速度分布细节以及流体示踪粒子的行为轨迹。发现螺槽内速度分布表现出周期性和对称性的变化,揭示了同宿点及椭圆点存在及位置不变性,为进一步分析流体质点在相空间的动力学行为奠定了基础。     

高冰镍硫酸浸出液萃取净化工艺流程的经济分析和最优化

本文以我国水法冶金的实际应用课题为对象,用系统分析的手法对高冰镍硫酸浸出液以5709和P507为萃取剂的两种萃取净化流程作了技术经济分析和比较.本文基于工艺实验建立的萃取与反萃模型,作为过程模拟和设计的基础.最后确定出该流程的最优操作参数和各单元操作的费用估算.     

PROFIBUS自动化控制系统的维护

滇西水泥厂3号窑FCS自动化系统自投产以来运行一直正常,这与操作者做好对PROFIBUS-DP和 PROFIBUS-PA总线及Freelance 2000系统软件的维护工作分不开。阐述了现场总线的环境要求和安装经验。     

国内外无机颜料工业的现状及发展趋势

阐述了国内外无机颜料的生产及需求现状,预测了无机颜料工业的发展趋势、产品发展方向,提出了发展我国无机颜料工业的策略。     

提高产品合格粒级产率的试验研究

扼要介绍了某选厂碎磨试验研究的情况．并根据研究结论，提出了该厂技术改造应当采用的流程与设备方案，以提高产品合格粒级产率。