薄板坯连铸用浸入式水口的性能与使用

针对薄板坯连铸用浸入式水口的使用条件,选择了水口不同部位的材质。以板状刚玉、氧化铝粉、锆莫来石、电熔稳定氧化锆、电熔镁砂、天然鳞片状石墨等为原料制备了浸入式水口,重点研究水口本体铝碳材料的抗氧化性能和渣线锆碳材料的抗侵蚀性能,并模拟现场使用条件进行了烘烤试验。结果表明:所研制的水口材料性能完全满足使用要求,烘烤时无氧化和剥落;在薄板坯实际连铸生产条件下,所研制的浸入式水口稳定地实现了24炉连浇,为相关的浸入式水口研究提供了良好的基础。     

喷雾造粒粉体对BaTiO3系PTCR半导体陶瓷性能的研究

研究了通过喷雾造粒制得的BaTiO3系PTCR热敏陶瓷粉体性能对生坯成型及瓷体物理、PTC效应、电学等性能的影响,与手工造粒粉体比较,由于喷雾造粒的粉体流动性好,表面活性大,粒度均匀,其成型性及烧结后瓷体PTCR效应、电学性能均有明显提高。     

原位生成O'-SiAlON晶须增强铝碳耐火材料

以板状刚玉、石墨为主要原料,基质部分分别添加3%、5%和7%的O’-SiAlON前驱体混合粉(即β-Si3N4微粉、SiO2微粉和α-Al2O3微粉的混合球磨粉),以酚醛树脂为结合剂制成试样,于200℃烘烤后,在空气中埋(SiO2 C)混合粉,分别于1000℃、1300℃、1500℃保温3h原位合成了含O’-SiAlON晶须的铝碳耐火材料。对烧后试样的物理性能、物相及显微结构进行了分析,并对烧结有重要影响的反应进行了热力学分析。结果表明:埋(SiO2 C)混合粉能有效抑制反应体系中SiO2在高温烧结过程中的分解,从而促进O’-SiAlON晶须的原位生成。1500℃时,含有O’-SiAlON前驱体混合粉的试样原位生成了针状和絮状的O’-SiAlON晶须,这些晶须交织于试样的骨料与基质之间,能显著增强试样的强度;且随着O’-SiAlON前驱体含量的增加,试样的强度逐渐增加。     

Fast and controlled release of triamcinolone acetonide from extrusion-spheronization pellets based on mixtures of native starch with dextrin or waxy maize starch

Pellets composed chiefly of inexpensive starches allow modulation of the rate of release of the poorly soluble drug triamcinolone acetonide in media of pH 1.2-6.8. Wheat- or maize-starch-based pellets with 20% of white dextrin release the drug in vitro almost completely within 20 min, while maize-starch-based pellets with 5-35% of waxy maize starch sustain gradual release over periods of 9-12 hr or longer when prepared using appropriate amounts of granulation fluid.     

Fast and Controlled Release of Triamcinolone Acetonide from Extrusion-Spheronization Pellets Based on Mixtures of Native Starch with Dextrin or Waxy Maize Starch

Pellets composed chiefly of inexpensive starches allow modulation of the rate of release of the poorly soluble drug triamcinolone acetonide in media of pH 1.2–6.8. Wheat- or maize-starch-based pellets with 20% of white dextrin release the drug in vitro almost completely within 20 min, while maize-starch-based pellets with 5–35% of waxy maize starch sustain gradual release over periods of 9–12 hr or longer when prepared using appropriate amounts of granulation fluid.     

铁矿石粒度对生球团性能的影响(英文)

高炉和COREX工艺对铁矿球团的质量提出了要求。铁矿球团的质量由生球质量和焙烧参数决定。生球特性由矿石的成球行为和矿石特性决定,矿石特性包括矿石的化学成分、矿石本质(硬度)、比表面积和粒度分布。金达尔钢公司的铁矿石来自Bellary-Hospet地区的不同矿点。用于实验室研究的3种铁矿粉(矿1、矿2和矿3)来自3个不同的矿点。用矿1、矿2、矿3和矿4(混矿)制成不同的生球。矿石的邦德功指数的变化范围为6～11kWh/t。从矿石的本质来说,矿1较软,而矿3较硬,其硬度范围为:1～3。矿石的粒度范围为:-45μm占56%～68%。为理解矿石粒度对生球特性的影响,研究了生球的落下次数、压溃强度,干燥后压溃强度,孔隙度和堆密度。随着矿石粒度的降低,平均落下次数增加。平均落下次数的变化范围为6.5～14.7,不同矿石的生球落下次数的排序为矿1>矿2>矿4>矿3。矿1、矿2和矿4的生球GCS和DCS随着-45μm部分比例的增加而提高,在64%时达到最大值,而后随着-45μm部分比例的继续提高而降低。生球的GCS和DCS变化范围分别为1.35～2.77kg/p和2.3～5.4kg/p。生球的孔隙度随着矿石粒度的降低而下降,矿3的孔隙度较高,矿1的孔隙度较低,这和矿石的硬度相关。生球的堆密度随矿石粒度的降低而增大。生球的堆密度范围为2.0～2.3kg/m3,生球堆密度顺序为矿1>矿4>矿2>矿3。     

延迟焦化装置弹丸焦形成机理探讨

关于弹丸焦形成机理的研究,国内外起步都比较晚,目前关于其深层的机理研究并不多。就国内而言,大多来源于炼油企业的生产报道,实验室研究较少,未形成成熟的理论体系。根据弹丸焦的形态及物性,提出了弹丸焦气相成核的动态过程,认为形成弹丸焦的本质原因是塔内气速过大,造成气相中焦粒(或前驱物)浓度过大,且停留时间过长。气相中的焦粒经融合、摩擦等过程后,最终形成弹丸焦。根据此机理,可以很好地统一解释各种影响弹丸焦形成的因素。该理论认为,塔内气速为原料性质、操作条件等因素的综合函数,是弹丸焦形成的关键因素之一。通过该机理,可以很好地解释弹丸焦生成过程中各种现象及其影响因素。塔内气速是弹丸焦生成的一个综合判据,它是原料性质、操作条件的函数。如果能够结合装置工况、原料性质等因素,通过流体动力学计算,拟合出弹丸焦生成的临界气速,可以对装置操作起到实质性的指导作用。     

生物质颗粒燃料成型影响因素研究进展

综述了国内外生物质颗粒燃料成型研究资料,分析了颗粒燃料的黏结机理及质量参数,总结了原料含水率、贮藏时间、成型温度、压力等影响因子对颗粒燃料质量的影响,为成型工艺的合理选择及提高生物质颗粒燃料的物理品质提供理论依据和文献参考。     

Can Modified Starch be Used As A Binder For Iron Ore Pellets?

Organic binders are often desired when making low-silica iron ore pellets. Corn and wheat are grown in large quantities near certain iron ore pelletizing facilities and their starches are easily modified to form cold-water-soluble powders that can be used as binders. We investigated how starch cold-water solubility, starch dose, starch hydration time, green ball moisture content, and firing temperature affected pellet quality. With a fluxed, hematite concentrate, the high-soluble starch led to good wet and dry balls, but weak and friable indurated pellets compared to the standard binder, bentonite clay. As expected, the low-soluble starch did not make as good green balls as the high-soluble starch. Thermogravimetric analyses of unfired pellets and their abrasion products showed that modified starch was inhomogeneously distributed in pellets, with a high concentration near the ball surfaces. The surface concentration increased, and the core concentration decreased, as pellets grew during the pelletizing process. This suggests that starch enrichment near surfaces is a consequence of the agglomeration–compaction process, and may occur with other pelletizing binders. Abrasion mass losses were 81% greater with modified starch than with bentonite at 1100°C, and 31% greater at 1250°C. However, starch contents near the surfaces did not qualitatively correlate to roughness, as the highest starch dose tested gave the smoothest and least dusty pellets.     

Estimation of pellet size and strength of limestone and manganese concentrate using soft computing techniques

This paper presents a soft computing approach to estimate wet or green pellet size and strength and signifies the importance of individual process parameter. A huge portion of available minerals and materials is in the form of fine powder that makes their management and utilization a tedious job. Pelletization, a size enlargement technique, is used to tackle aforementioned problems and provides benefits such as ease of handling and storage, convenient transportation and improved process efficiency. Besides other characteristics, pellet size and strength are of prime significance and their accurate estimation can enhance the product quality. Real-life constraints (e.g., time in conducting experiments, repetition of experiments considering measurement errors, availability of resources, etc.) pose difficulties in generating sufficient experimental data at the laboratory. Hence, the concept of random population generation of genetic algorithm is exploited to fulfill data requirement where fitness functions are formulated using multiple regression. Better visualisation of pellets attributes and operating conditions is done through self-organizing map which also helped in deducing some important facts. Sensitivity analysis and construction of learning curves is also performed in present study. Finally, multilayer perceptron, a popular supervised neural network model, is applied on synthetic data to approximate pellet properties. Agreement between estimated and corresponding experimental values ascertained that neural network based system can be employed as an effective and credible tool to anticipate characteristics of wet pellets.