微波焙烧含锗氧化锌烟尘回收锗的研究
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摘要
云南省某湿法炼锌厂生产过程中产生大量的含锗氧化锌烟尘,现有工艺是用硫酸浸出、单宁沉锗工艺回收其中的锗,但由于氧化锌烟尘中锗主要以锗铁复合氧化物形式存在,造成锗的浸出率通常低于60%,难以高效回收。因此,锗铁复合氧化物晶体结构的破坏分离是提高锗浸出率、实现高效利用的关键技术。采用微波处理含锗氧化锌烟尘可以破碎矿物、提高比表面积、转变矿物晶型等。为此本论文提出两种微波处理新工艺,系统深入研究了各个工艺过程参数以及相关原理,提高了锗的浸出率。
首先,提出了微波煅烧-硫酸浸出含锗氧化锌烟尘工艺。单因素实验研究发现,微波煅烧温度在210℃～290℃的范围内,随着温度升高,物料粒度降低,比表面积增加,锗浸出率也提高；当温度高于290℃时,物料会发生烧结,不利于锗的浸出；在290℃下微波煅烧10min后,含锗氧化锌烟尘的平均粒度由原来的5.39μm降为1.70μm。根据微观形貌SEM和XRD物相分析发现,在适当的温度范围里,微波煅烧可以使含锗氧化锌烟尘中大颗粒产生碎裂,难溶的Fe4Ge3O12物相消失。采用响应曲面优化法,研究了液固比、硫酸初始浓度、微波煅烧温度、浸出温度、浸出时间等影响因素对锗的浸出率的影响规律。结果发现：前三个因素是显著影响因素；优化的工艺参数为：微波煅烧温度287℃、液固比6.5mL·g-1、浸出时间4h、硫酸初始浓度9.0mol/L.浸出温度60℃,预测在此条件下锗浸出率为85.25%。再采用该参数进行了验证实验,发现锗浸出率可达到84.37%。预测结果与实验值相对误差仅为1.04%,说明优化结果准确可靠。与现有工艺相比,锗浸出率提高了约22个百分点。接着,进行了硫酸浸出过程动力学的研究,考察了硫酸初始浓度、浸出温度和时间等因素对锗浸出率的影响。结果发现,该浸出过程遵循固体膜层的收缩核模型。
其次,为了进一步提高锗的回收率,提出了微波碱性焙烧-水溶含锗氧化锌烟尘的工艺,研究了配碱量比、微波焙烧温度、液固比、浸出温度、浸出时间、熟化时间等对锗浸出率的影响规律。结果表明：配碱量比、微波焙烧温度、配碱量比与微波加热温度交互影响是本工艺的显著影响因素；优化的工艺参数为配碱量比1g·g-1、熟化时间1d、焙烧温度408℃、保温10min、液固比6.4m L·g-1、水溶温度66℃、水溶时间67min；在此条件下,响应曲面优化预测值为97.16%,验证实验锗的浸出率为97.38%,两者相对误差仅为0.23%,说明优化结果较好。与现有的常规碱性焙烧工艺相比,碱性焙烧温度由1080℃降低到408℃,保温时间由60min降低到10min。水溶动力学研究表明,锗酸钠水溶过程符合扩散控制模型,表观活化能为15.46kJ/mol。
最后,分别建立了微波煅烧-硫酸浸出工艺和微波碱性焙烧-水溶工艺的神经网络反预测模型,预测结果表明神经网络预测模型的预测值与实验值有较好的拟合效果,且不同实验条件下的预测结果变化趋势与实测值变化趋势相符合,模型收敛精度都达到10-5。对实际预测锗浸出率及工艺参数有较好的指导意义。
Zinc hydrometallurgy plant produce large amounts of germanium-containing zinc oxide fume during a production process in Yunnan Province.The present art of dust treatment is sulfuric acid leaching and tannic germanium precipitation for recovering Ge. For insoluble of Fe4Ge3O12, the leaching rate of germanium is generally lower than60%. Thus, separation and destruction of Fe4Ge3O12becomes a key technical subject for improving germanium extraction and the efficient utilization of germanium resource. Microwave treatment has the capability of reducing the particle size of minerals, increasing their specific surface area, and even transforming their crystal structures. Two novel processes of microwave roasting are proposed for improving Ge extraction in this dissertation, and their key technology and related theories are studied. Results reveal that Ge leaching rates are markedly increased
At first, microwave calcination-sulfuric acid leaching was used to recover Ge. The size of material reduces the specific surface area and the Ge extraction increase with increasing temperature, when the microwave sintering temperature is in the range of210℃～290℃. It is unfit for leaching of germanium when the temperature is higher than290℃. The average particle sizes of zinc oxide dust bearing germanium reduce from5.39μm to1.70μm after microwave calcination at290℃for10min. The Ge extraction increased after microwave calcination because the particle size became small. The SEM and XRD of material show microwave calcination can change the morphology and particle size of zinc oxide dust bearing germanium. Large particle was fragmentated, the size of zinc oxide dust bearing germanium was reduced, the uniformity of size was improved, and the characteristic peak of Fe4Ge3O12was disappeared after microwave calcinations. The relational mode of the germanium extraction and the influencing factors was obtained by Design-Expert software. Microwave calcination temperature, liquid-solid ratio and initial concentration of sulfuric acid are the significant factors for the process. Microwave calcination-sulfuric acid leaching experiments was designed using response surface methodology. By analyzing each factors significance and the correlation, the optimized conditions were obtained as follows:microwave calcination at287℃, liquid-solid ratio of6.5mL·g-1, leaching time of4h, sulfuric acid initial concentration of9.0mol/L, leaching temperature at60℃with germanium extraction about84.37%. The predictive value was85.25%. The relative error is1.04%between the forecast value and the actual value. The germanium extraction was increased22%compared with existing process. The kinetics of Ge leaching by microwave calcination-sulfuric acid was studied. The effects of leaching temperature and initial concentration of sulfuric acid on the leaching rate of germanium were examined. The experiment results indicate that germanium leaching rate increases with increasing temperature and initial concentration of sulfuric acid. It was found that the reaction kinetic model follows the shrinking core model of the diffusion process of the solid film.
Microwave alkaline roasting-water dissolving process was proposed to further improve the germanium extraction. The germanium extraction is consistent with the linear polynomial model type. Alkali-material ratio, microwave heating temperature and leaching temperature are the significant factors for the process. By analyzing each factors significance and the correlation, the optimized conditions were obtained as follows, alkali-material ratio of1g·g-1, aging time of1day, microwave heating at408℃, microwave alkaline roasting holding time of10min, liquid-solid ratio of6.4mL·g-1, leaching temperature at66℃, leaching time of67min with the germanium extraction about97.38%. The predictive value was97.16%. The relative error is0.23%between the forecast value and the actual value. Compared with the existing methods, the alkaline roasting temperature was reduced from1080℃to408℃and the alkaline roasting holding time was greatly reduced from60min to10min.The kinetics of germanium leaching by microwave alkaline roasting-water dissolving was studied. It was found that the dissolution reaction kinetic model follows diffusion control. The apparent activation energy is15.46kJ/mol.
Basing on the study of Artificial Neural Network, the neural models were established for the prediction of microwave calcination-sulfuric acid leaching and microwave alkaline roasting-water dissolving. The results indicated that the neural network prediction model of microwave calcination-sulfuric acid leaching and microwave alkaline roasting-water dissolving were reliable, the forecast and actual values fitted well. The model could be used to predict the regeneration experiments with high credibility and practical significance. The accuracy of convergence of two models has reached10-5.
首先,提出了微波煅烧-硫酸浸出含锗氧化锌烟尘工艺。单因素实验研究发现,微波煅烧温度在210℃～290℃的范围内,随着温度升高,物料粒度降低,比表面积增加,锗浸出率也提高；当温度高于290℃时,物料会发生烧结,不利于锗的浸出；在290℃下微波煅烧10min后,含锗氧化锌烟尘的平均粒度由原来的5.39μm降为1.70μm。根据微观形貌SEM和XRD物相分析发现,在适当的温度范围里,微波煅烧可以使含锗氧化锌烟尘中大颗粒产生碎裂,难溶的Fe4Ge3O12物相消失。采用响应曲面优化法,研究了液固比、硫酸初始浓度、微波煅烧温度、浸出温度、浸出时间等影响因素对锗的浸出率的影响规律。结果发现：前三个因素是显著影响因素；优化的工艺参数为：微波煅烧温度287℃、液固比6.5mL·g-1、浸出时间4h、硫酸初始浓度9.0mol/L.浸出温度60℃,预测在此条件下锗浸出率为85.25%。再采用该参数进行了验证实验,发现锗浸出率可达到84.37%。预测结果与实验值相对误差仅为1.04%,说明优化结果准确可靠。与现有工艺相比,锗浸出率提高了约22个百分点。接着,进行了硫酸浸出过程动力学的研究,考察了硫酸初始浓度、浸出温度和时间等因素对锗浸出率的影响。结果发现,该浸出过程遵循固体膜层的收缩核模型。
其次,为了进一步提高锗的回收率,提出了微波碱性焙烧-水溶含锗氧化锌烟尘的工艺,研究了配碱量比、微波焙烧温度、液固比、浸出温度、浸出时间、熟化时间等对锗浸出率的影响规律。结果表明：配碱量比、微波焙烧温度、配碱量比与微波加热温度交互影响是本工艺的显著影响因素；优化的工艺参数为配碱量比1g·g-1、熟化时间1d、焙烧温度408℃、保温10min、液固比6.4m L·g-1、水溶温度66℃、水溶时间67min；在此条件下,响应曲面优化预测值为97.16%,验证实验锗的浸出率为97.38%,两者相对误差仅为0.23%,说明优化结果较好。与现有的常规碱性焙烧工艺相比,碱性焙烧温度由1080℃降低到408℃,保温时间由60min降低到10min。水溶动力学研究表明,锗酸钠水溶过程符合扩散控制模型,表观活化能为15.46kJ/mol。
最后,分别建立了微波煅烧-硫酸浸出工艺和微波碱性焙烧-水溶工艺的神经网络反预测模型,预测结果表明神经网络预测模型的预测值与实验值有较好的拟合效果,且不同实验条件下的预测结果变化趋势与实测值变化趋势相符合,模型收敛精度都达到10-5。对实际预测锗浸出率及工艺参数有较好的指导意义。
Zinc hydrometallurgy plant produce large amounts of germanium-containing zinc oxide fume during a production process in Yunnan Province.The present art of dust treatment is sulfuric acid leaching and tannic germanium precipitation for recovering Ge. For insoluble of Fe4Ge3O12, the leaching rate of germanium is generally lower than60%. Thus, separation and destruction of Fe4Ge3O12becomes a key technical subject for improving germanium extraction and the efficient utilization of germanium resource. Microwave treatment has the capability of reducing the particle size of minerals, increasing their specific surface area, and even transforming their crystal structures. Two novel processes of microwave roasting are proposed for improving Ge extraction in this dissertation, and their key technology and related theories are studied. Results reveal that Ge leaching rates are markedly increased
At first, microwave calcination-sulfuric acid leaching was used to recover Ge. The size of material reduces the specific surface area and the Ge extraction increase with increasing temperature, when the microwave sintering temperature is in the range of210℃～290℃. It is unfit for leaching of germanium when the temperature is higher than290℃. The average particle sizes of zinc oxide dust bearing germanium reduce from5.39μm to1.70μm after microwave calcination at290℃for10min. The Ge extraction increased after microwave calcination because the particle size became small. The SEM and XRD of material show microwave calcination can change the morphology and particle size of zinc oxide dust bearing germanium. Large particle was fragmentated, the size of zinc oxide dust bearing germanium was reduced, the uniformity of size was improved, and the characteristic peak of Fe4Ge3O12was disappeared after microwave calcinations. The relational mode of the germanium extraction and the influencing factors was obtained by Design-Expert software. Microwave calcination temperature, liquid-solid ratio and initial concentration of sulfuric acid are the significant factors for the process. Microwave calcination-sulfuric acid leaching experiments was designed using response surface methodology. By analyzing each factors significance and the correlation, the optimized conditions were obtained as follows:microwave calcination at287℃, liquid-solid ratio of6.5mL·g-1, leaching time of4h, sulfuric acid initial concentration of9.0mol/L, leaching temperature at60℃with germanium extraction about84.37%. The predictive value was85.25%. The relative error is1.04%between the forecast value and the actual value. The germanium extraction was increased22%compared with existing process. The kinetics of Ge leaching by microwave calcination-sulfuric acid was studied. The effects of leaching temperature and initial concentration of sulfuric acid on the leaching rate of germanium were examined. The experiment results indicate that germanium leaching rate increases with increasing temperature and initial concentration of sulfuric acid. It was found that the reaction kinetic model follows the shrinking core model of the diffusion process of the solid film.
Microwave alkaline roasting-water dissolving process was proposed to further improve the germanium extraction. The germanium extraction is consistent with the linear polynomial model type. Alkali-material ratio, microwave heating temperature and leaching temperature are the significant factors for the process. By analyzing each factors significance and the correlation, the optimized conditions were obtained as follows, alkali-material ratio of1g·g-1, aging time of1day, microwave heating at408℃, microwave alkaline roasting holding time of10min, liquid-solid ratio of6.4mL·g-1, leaching temperature at66℃, leaching time of67min with the germanium extraction about97.38%. The predictive value was97.16%. The relative error is0.23%between the forecast value and the actual value. Compared with the existing methods, the alkaline roasting temperature was reduced from1080℃to408℃and the alkaline roasting holding time was greatly reduced from60min to10min.The kinetics of germanium leaching by microwave alkaline roasting-water dissolving was studied. It was found that the dissolution reaction kinetic model follows diffusion control. The apparent activation energy is15.46kJ/mol.
Basing on the study of Artificial Neural Network, the neural models were established for the prediction of microwave calcination-sulfuric acid leaching and microwave alkaline roasting-water dissolving. The results indicated that the neural network prediction model of microwave calcination-sulfuric acid leaching and microwave alkaline roasting-water dissolving were reliable, the forecast and actual values fitted well. The model could be used to predict the regeneration experiments with high credibility and practical significance. The accuracy of convergence of two models has reached10-5.
引文
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