Mn对含炭耐火材料抗渣侵蚀性的影响

以烧结板状刚玉、锆莫来石、天然鳞片状石墨为主原料 ,酚醛树脂为结合剂 ,Al、Si、B4C、Mn粉为添加剂 ,经 1 4 50℃埋炭烧成后 ,制成铝炭和铝锆炭系列试样 ,并对各试样的抗渣侵蚀性能进行了对比研究。结果表明 :在铝锆炭材料中 ,当Mn与Al、Si复合加入且Mn与C的质量比为 1∶4时 ,试样的抗侵蚀性和渗透性均较好 ;在铝炭材料中 ,当Mn与Al、Si、B4C复合加入且Mn与C的质量比为 1∶4时 ,试样的抗渗透性较好     

Modeling of iron ore pelletization using 3 ** factorial design of experiments and polynomial surface regression methodology

The process of size enlargement or agglomeration finds a variety of applications in material processing and utilization. Pelletization is one such process which uses water as medium and revolving units (Disc/Drums) to form spherical pellets from fine particulates. Green or wet pelletization is the first step in pelletization process and is of critical importance since the effectiveness of the subsequent stages of drying and in duration depends on the quality and quantity of green pellets.This research presents the work carried out to develop model equations to predict the size distribution of pellets at any given level of intervals. Modeling of pelletization was oriented towards predicting the size distribution of pellets at any given level of variables .The prediction of pellet size distribution involves quantification of the self preserving curve and correlation between D₅₀ and the variables. A new model has been developed to predict the size distribution of the pellets using advanced statistical software “STATISTICA”. The equation Y = − 0.3757X² + 1.6256X-0.74 where “Y” is the cumulative wt.% passing and “X” is D/D₅₀ was used to predict the pellet size distribution.Correlation between D₅₀ and variables was given by “D 50” = 4.226 + (3.106*M) − (0.544*M²) + (2.044*I) − (0.644*I²) + (0.2444*T) − (0.028*T²) − (0.058*M*I) + (0.0917*I*T) using quadratic response surface methodology. The mean pellet diameter “D₅₀” observed versus predicted was compared. A polynomial regression equation was used to quantify the characteristic curve of iron ore slimes agglomeration process. This can be utilized to predict the complete agglomerate size distribution irrespective of the operating conditions and the size of the pelletizer if a relationship such as agglomerate median product size D₅₀, as a function of the operating conditions is made available.     

Al2O3-Al-C材料加热过程的变化

按w(板状刚玉)=84%,w(铝粉)=8%,w(α-Al2O3微粉)=6%,w(鳞片石墨)=2%的配比配料,外加3%热固性酚醛树脂作结合剂,成型后于200℃烘烤24h。在埋炭条件下于600～1400℃保温3h加热处理,冷却后测量试样的线变化率、显气孔率和常温耐压强度,并分析部分试样的孔径分布、相组成和显微结构,同时测定烘烤后试样在600℃、800℃、1000℃、1200℃和1400℃下的热态抗折强度,以分析该材料在加热过程的变化。结果表明,试样在600～1400℃埋炭加热过程中的变化可大致分为3个阶段:1)600～800℃,金属Al于660℃熔化,促进试样致密化,在800℃时已有少量Al4C3和AlN生成,使加热后试样的致密度和强度增大;2)800～1200℃,大量生成Al4C3和AlN,Al4C3和AlN填充在刚玉骨架结构中,试样的显气孔率进一步减小,常温耐压强度和热态抗折强度进一步增大;3)1200～1400℃,金属Al消失,Al4C3含量减少,部分与N2反应转化为AlN,试样的显气孔率略有降低,常温耐压强度和热态抗折强度略有增大。由此可见,随着加热温度的提高,材料的结合方式从碳结合转变为碳和金属铝复合结合,最后逐渐转变为碳和非氧化物复合结合。     

含钒渣对铝碳材料的侵蚀

为了探讨含矾渣对铝碳材料的侵蚀机制,用动态感应抗渣法研究了w(V2O5)=10%、碱度2.8,w(V2O5)=6%、碱度2.8,w(V2O5)=6%、碱度1.44的3种含钒渣对铝碳材料的侵蚀。结果表明:随着V2O5含量(w)由6%增加到10%,铝碳材料的熔损指数增加;随着碱度的增加,铝碳材料的熔损指数也增加;添加电熔镁砂有助于提高铝碳材料的抗侵蚀性能。显微分析表明:V、Ti元素渗透能力强,渗透深,而尖晶石可固溶少量V2O5、MnO及FeO。     

添加物对铝碳耐火材料防氧化涂料抗氧化性能的影响

以SiO2-A l2O3-B2O3-Na2O-K2O-CaO系釉料为基料,分别添加质量分数为10%、30%、50%、70%的氧化物(粒度均<0.076 mm的石英和刚玉粉)和非氧化物(粒度均<0.076 mm的碳化硅和硅粉),以水玻璃为结合剂配制涂料,首先研究了涂料半球温度的变化,然后将涂料涂覆在铝碳材料样块的表面,考察其抗氧化性能(以铝碳样块在200~1 300℃氧化后的质量损失率表征),并采用SEM观察了涂层结构。结果表明:加入氧化物SiO2、A l2O3以及非氧化物SiC、Si,均使涂料的半球温度升高;A l2O3和SiC的加入能增强涂料的防氧化作用,而SiO2、Si的加入使涂料的防氧化作用降低。     

二氧化硅喷雾造粒粉体的热处理工艺研究

研制了一种以SiO2为基体的高温可磨耗封严涂层,为了改善二氧化硅喷雾造粒粉体的性能,研究了热处理工艺对粉体松装密度、流动速度及粒度分布的影响。结果表明,热处理过程中伴随着SiO2颗粒的烧结,热处理温度对粉体性能的影响较热处理时间更为显著,随着温度的升高,喷雾造粒SiO2球逐渐烧结,粉体粒度减小,松装密度增加,流动性提高,采用1000～1050℃、30～60min的工艺对粉体进行热处理能够获得最优的粉体性能。     

Sustained-release alginate-chitosan pellets prepared by melt pelletization technique

Context: Alginate-chitosan pellets prepared by extrusion-spheronization technique exhibited fast drug dissolution.

Objective: This study aimed to design sustained-release alginate pellets through rapid in situ matrix coacervation by chitosan during dissolution.

Methods: Pellets made of alginate with chitosan and/or calcium acetate were prepared using solvent-free melt pelletization technique which prevented reaction between processing materials during agglomeration and allowed such reaction to occur only in dissolution phase.

Results: Drug release was retarded in pH 2.2 medium when pellets were formulated with calcium acetate or chitosan till a change in medium pH to 6.8. The sustained-release characteristics of calcium alginate pellets were attributed to pellet dispersion and rapid cross-linking by soluble Ca²⁺ during dissolution. The slow drug release characteristics of alginate-chitosan pellets were attributed to polyelectrolyte complexation and pellet aggregation into swollen structures with reduced erosion. The drug release was, however, not retarded when both calcium acetate and chitosan coexisted in the same matrix as a result of chitosan shielding of Ca²⁺ to initiate alginate cross-linkages and rapid in situ solvation of calcium acetate induced fast pellet dispersion and chitosan losses from matrix.

Conclusion: Similar to calcium alginate pellets, alginate-chitosan pellets demonstrated sustained drug release property though via different mechanisms. Combination of alginate, chitosan and calcium acetate in the same matrix nevertheless failed to retard drug release via complementary drug release pattern.     

回转窑结圈的原因分析及改进措施

对豫河公司投产初期回转窑结圈现象频发的问题进行了分析,提出了改进措施。通过对原燃料条件、工艺参数、设备等方面进行改进后,提高了生球质量并优化热工制度,有效地解决了结圈问题。     

Iron Ore Pellet Dustiness Part II: Effects of Firing Route and Abrasion Resistance on Fines and Dust Generation

Iron ore pellets abrade during their production and handling, which lowers product quality and leads to dustiness issues. Pellets were collected from a variety of plants (operating either Straight-Grate (SG) or Grate-Kiln (GK) furnaces) to understand whether furnace type affects fines and dust formation. Results showed that pellets fired in SG furnaces were less abrasion-resistant (3.5 × lower) than pellets fired in GK furnaces. Concurrently, laboratory pellets were prepared using various ores, binders, and firing temperatures. These were tested to understand the relationship between abrasion index and dustiness. AI was observed to range from 1 to 14%. Dustiness, determined via AI and size distributions of abrasion progeny, ranged from 0.2 to 1.6%. For AI greater than 5%, AI can be used to indicate potentially high levels of dust. For AI less than 5%, there was a poor correlation between AI and dustiness. This was explained by the observation that as AI decreased, the abrasion product fineness increased. The results from parts I and II of this investigation suggest that material loss and levels of pellet dustiness may be significantly affected by pellet quality up to a certain point. Poorly fired pellets will be dusty during handling and transportation, while well-fired pellets will generate less – but finer – material as their quality improves. This could lead to little observed changes in dust generation over a wide range of pellet quality. Dust generation at each site would then depend on the quantity of material produced and their extent of handling.