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针对铜烟尘酸性浸出液中砷与有价金属分离的难题,采用加压合成臭葱石的方法,实现Cu和As的高效分离以及将砷以臭葱石的形式进行稳定固化的目的。在加压体系下研究了温度、总压和初始pH值对Cu和As的分离效果以及臭葱石合成的影响。结果表明:提高反应温度,有利于Cu和As的分离及合成晶型良好的臭葱石,温度较低时生成铁矾影响臭葱石合成进而影响Cu、As的分离;初始pH值增大,不利于Cu和As的分离,初始pH值越高,体系中的Fe3+越易水解,不利于臭葱石的合成,进而影响Cu和As的分离效率;总压增大,有利于Cu和As分离,不利于臭葱石的稳定固化,氧压过高氧化速率加快,易发生Fe3+水热水解反应,臭葱石形貌由双锥状变为团聚状使其稳定性降低。在初始Fe和As物质的量之比1.2、初始pH值0.4、时间2 h、初始铜离子浓度9 g·L-1、总压0.8 MPa、温度160℃的条件下,As和Cu的沉淀率分别为81.57%与12.27%,Cu、As分离系数为76.88,能够高效分离Cu和As,并获得晶态臭葱石。 相似文献
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通过水平振荡毒性浸出试验,研究了硫化砷渣在不同的pH值和n(Ca)/n(As)下As的浸出。结果表明:浸出液pH值和n(Ca)/n(As)的不同,会对As的浸出质量浓度产生较大影响,pH在1.0113.12范围内时,随着pH值的增大,浸出液As的质量浓度先减小后增加,在pH=11.91时,达到最小值4.27 g/L;而随着n(Ca)/n(As)的增加,As的浸出质量浓度先增大后减小,在n(Ca)/n(As)=1.405时出现最大值,As浸出质量浓度为31.674 g/L。但总体来说n(Ca)/n(As)在(0.18713.12范围内时,随着pH值的增大,浸出液As的质量浓度先减小后增加,在pH=11.91时,达到最小值4.27 g/L;而随着n(Ca)/n(As)的增加,As的浸出质量浓度先增大后减小,在n(Ca)/n(As)=1.405时出现最大值,As浸出质量浓度为31.674 g/L。但总体来说n(Ca)/n(As)在(0.1875.619)范围内,加入Ca O宏观表现为促进硫化砷渣中As的溶出。 相似文献
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采用生物浸出法处理铜砷滤饼废渣,考察了pH值、温度和菌种对浸出效果的影响,分析了铁氧化菌浸出机理和将生物浸出用于含砷废渣无害化处理的可行性. 结果表明,微生物对铜砷滤饼浸出起促进作用,热酸预处理后在50℃、pH值为1.5的条件下,以中度嗜热西伯利亚硫杆菌(Sulfobacillus sibiricu)浸出7 d,砷浸出率达91.33%,铜浸出率达94.22%. 相似文献
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对不锈钢电炉烟尘的基本特性和环境浸出行为进行了研究.结果表明,该烟尘中Fe,cr,Ni和Zn含量较高,主要物相是铁铬尖晶石和石英,具有潜在回收价值;烟尘略显酸性,具有较好的流动性,其中Cd含量超过了国家标准,是一种有毒固体废弃物;烟尘应尽量避免堆放或填埋在低pH场所,以防止其中的重金属离子浸出;不同的浸出液对烟尘中Cr(Ⅵ)浸出能力的影响不同,其中以1 mol/L硝酸为浸出液,Cr(Ⅵ)浸出量最大,0.1 mol/L冰醋酸溶液最小.随浸出时间的延长、浸出液温度升高和固液比增大,Cr(Ⅵ)浸出量增加. 相似文献
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锡烟尘的真空脱砷预处理 总被引:1,自引:0,他引:1
采用真空蒸发的方法对烟尘进行了脱砷预处理,并考察了蒸发温度、蒸发时间和体系压强对烟尘蒸发率的影响。结果表明:在蒸发温度为673 K,蒸发时间为30 min,体系压强为40 Pa的条件下,烟尘的蒸发率为16.2%,蒸余物中砷的含量降低到1.12%,砷的脱除率达92.7%。 相似文献
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含砷硫铁矿焙烧过程的热力学分析 总被引:2,自引:0,他引:2
对含砷硫铁矿焙烧过程的热力学分析,绘出焙烧曲线,找出脱硫脱焙烧的理想条件,并对BASF和Boliden两种脱砷方法进行了讨论。 相似文献
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Preparation of Arsenic Oxide and High Purity UltrafineAntimony Compounds from Flue Dust Containing Arsenic and Antimony 总被引:3,自引:0,他引:3
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1 INTRODUCTIONIt is estimated that there are about 6000 tons of arsenic loaded into smelters along with theirvarious concentrates each year in China(reference data from 1986).As result,a lot of flue dustcontaning arsenic and antimony is produced.Utilization and treatment of this flue dust are ofsignificance for the econony of recovery of arsenic and antimony and the environmental protection.But conventional treatment processes of Pyrometallurgical volatilization and hydrometallurgicalleaching are unsatisfactory because of the difficulty in seperating As and Sb as well as inpreventing secondary pollution.This research is intended to develop a new low temperaturechlorination-distillation process with high recovery of val uables and low pollution. 相似文献
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介绍了我国北方某电解铜厂,在很长一段时间内,采购的阳极含砷较低而含锑较高。针对这种阳极板,采取了合理控制电解液成分、合理选用添加剂种类和控制用量、提高电解液温度、改变电解液循环方式、由常规电解改为周期反向电解等技术措施和完善操作方法,使电铜的合格率达到了100%。 相似文献
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以大冶有色金属公司铜冶炼污泥为原料,研究了氨浸法回收铜的工艺路线,并用加热的方法驱氨,使铜以氢氧化铜的形式析出,氧化铜的最大回收率达89.1%. 相似文献
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Recovery of Copper from Leaching Solution of Copper Smelting Ash 总被引:2,自引:0,他引:2
An efficient and reliable approach based on solvent extraction to selectively recover copper from leaching solution of Jinchuan copper smelting ash has been developed in this work. And the extraction isotherm of 50%(j) N902 with initial aqueous acidity of 19.6 g/L was determined at 25℃. The results show that the extractant, N902, has good selectivity to copper, and its saturated capacity of copper under the given conditions is over 23 g/L. The recovery rate of copper in the extraction is over 99%. And copper extraction equilibrium is reached in 90 s using 50% N902 with kerosene as the diluenting agent at an organic and aqueous volume phase ratio (O/A) of 1. Furthermore, over 99.5% of the loaded copper in the organic phase could be stripped by applying 196 g/L H2SO4 as the stripping agent. 相似文献
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The copper flash smelting process neural network model (CFSPNNM) was developed, its input layer includes eightnodes: oxygen grade (OG), oxygen volume per ton of concentrate (OVPTC), flux rate (FR) and quantities of Cu, S, Fe, SiO2and MgO in copper concentrate; output layer includes three nodes: matte grade, matte temperature and Fe/SiO2 in slag, andnet structure was 8-13-10-3. Then, the internal relationship between the technological parameters and the objectiveparameters was built after the CFSPNNM was trained by using GA-BP algorithm. Moreover, the technological parameterswere optimized by using genetic algorithms (GA) to make energy consumption the lowest. Simulation results showed that theCFSPNNM had high prediction precision and good generalization performance. Compared with the practical average data, theenergy consumption can be reduced by 6.8% if the smelting process is controlled by adopting the optimized technologicalparameters. 相似文献
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