Ni/Al_2O_3覆膜方法

阐述了Ni/Al2 O3 复合颗粒在生产中的应用 ,讨论了在Al2 O3 陶瓷颗粒上形成Ni膜的三种方法 ,分析了这些方法的优缺点。     

甲苯稀释对AlCl3-EMIC型离子液体电镀铝工艺氢脆性的影响

采用甲苯作为AlCl3-EMIC(1-乙基-3-甲基咪唑)型离子液体的稀释剂,其中纯态离子液体由物质的量比为2∶1的无水AlCl3和EMIC组成。对比了纯态和按稀释剂与离子液体体积比为1∶1稀释后电镀铝的外观、微观形貌和氢脆性。结果表明,采用甲苯稀释离子液体虽然可以降低镀液的黏度,改善镀层外观和微观形貌,但对离子液体电镀铝工艺的氢脆性有负面影响。     

酯交换法合成碳酸二苯酯研究进展

对碳酸二苯酯合成用催化剂、合成工艺、反应装置等进行了综述。认为国内应加强酯交换法合成碳酸二苯酯的基础研究 ,尽快实现其产业化     

模糊控制器在窑炉温度控制系统中的应用及计算机仿真

对陶瓷工业窑炉中的温度模糊控制问题进行了探讨,提出了模糊控制器在窑炉温控上的具体应用方法,并进行了计算机仿真,仿真结果表明模糊控制效果良好,具有较好的应用前景。     

复合肥料造粒装置的生产与操作

叙述了造粒装置生产运行应考虑的问题，总结了造粒装置的生产操作经验，对造粒机理和影响造粒工况的因素进行了详细探讨，并提出了造粒装置的优化运行方案。     

次氯酸钠氧化法测定聚丙烯酰胺浓度的研究

阐述了次氯酸钠氧化法（浊度法）测定部分水解聚丙烯酰胺浓度的反应机理，研究了聚丙烯酰胺的相对分子质量、次氯酸钠溶液浓度、反应时间对吸光度值的影响，针对大庆油田杏二中三元复合驱采出水中含有碱和表面活性剂、pH值高、黏度大、富集硫化物和亚硫酸根等特点，提出采用过硫酸铵一浊度法检测三元复合驱采出水中聚丙烯酰胺浓度。     

High temperature polymerization of propylene catalyzed by MgCl2‐supported Ziegler–Natta catalyst with various cocatalysts

Four cocatalysts, referred to as ethylaluminoxanes, were synthesized by the reaction between triethylaluminium (AIEt₃) and water under various molar ratios of H₂O/Al at ?78°C. Aluminoxanes were used as cocatalysts for a MgCl₂‐supported Ziegler–Natta catalyst for propylene polymerization at temperatures ranging from 70 to 100°C. When the polymerization was activated by AlEt₃, the activity as well as the molecular weight and isotacticity of the resulting polymer gradually dropped as the temperature varied from 70 to 100°C. When ethylaluminoxane was employed as the cocatalyst, good activity and high molecular weight and isotacticity were obtained at 100°C. Furthermore, when the cocatalyst varied from AlEt₃ to ethylaluminoxane, the atactic fraction and polymer fraction with moderate isotacticity decreased and the high isotactic fraction slightly increased, which indicated that the variation of the cocatalyst significantly affects the isospecificity of active sites. It was suggested that the reactivity of the Al‐Et group and the size of the cocatalyst were correlated to the performance of the Ziegler–Natta catalyst at different temperatures. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 100: 1978–1982, 2006     

聚天冬氨酸的合成与表征

以L-天冬氨酸为原料,热缩合成聚天冬氨酸酐,水解得到聚天冬氨酸。采用凝胶色谱法(GPC)测定了聚天冬氨酸的分子量,并用核磁共振(NMR)对其进行了表征。     

长江经济带水-能源-粮食系统耦合时空动态特征研究

水、能源和粮食为可持续发展的基础性资源,如何从时空角度全面评价长江经济带水-能源-粮食系统的耦合协调发展是促进区域资源可持续发展的重要前提。以水、能源、粮食以及共生单元水能、水粮和能粮系统为单元,构建水-能源-粮食系统耦合协调评价指标体系,采用熵值法对各系统指标赋权,运用耦合协调度模型和空间自相关分析对2010—2019年长江经济带的水-能源-粮食系统协调发展和时空动态特征进行定量研究。结果表明：2010—2019年长江经济带水-能源-粮食系统综合评价指数整体呈缓慢增长趋势,其中水系统对水-能源-粮食系统综合评价指数贡献最大,年均贡献占比为21.57%;能源系统贡献最小,占比为11.95%; 2010—2019年长江经济带水-能源-粮食系统耦合协调水平呈先升后降趋势,其中四川省上升幅度为5.05%,重庆市下降幅度为2.83%,且存在显著的空间异质性,上游地区明显高于中下游地区。其中能源资源是水-能源-粮食系统耦合协调发展的短板;长江经济带水-能源-粮食系统耦合协调度表现出显著空间关联性,高-高集聚区集中在长江上游地区,下游地区主要以低-低集聚区为主。长江经济带内各省市应因地制宜地完善资源管理机制,推动长江经济带资源可持续发展。     

Multimodal Pre-training Method for Vision-language Understanding and Generation

Most existing vision-language pre-training methods focus on understanding tasks and use BERT-like loss functions (masked language modeling and image-text matching) during pre-training. Despite their good performance in the understanding of downstream tasks, such as visual question answering, image-text retrieval, and visual entailment, these methods cannot generate information. To tackle this problem, this study proposes Unified multimodal pre-training for Vision-Language understanding and generation (UniVL). The proposed UniVL is capable of handling both understanding tasks and generation tasks. It expands existing pre-training paradigms and uses random masks and causal masks simultaneously, where causal masks are triangular masks that mask future tokens, and such pre-trained models can have autoregressive generation abilities. Moreover, several vision-language understanding tasks are turned into text generation tasks according to specifications, and the prompt-based method is employed for fine-tuning of different downstream tasks. The experiments show that there is a trade-off between understanding tasks and generation tasks when the same model is used, and a feasible way to improve both tasks is to use more data. The proposed UniVL framework attains comparable performance to recent vision-language pre-training methods in both understanding tasks and generation tasks. Moreover, the prompt-based generation method is more effective and even outperforms discriminative methods in few-shot scenarios.