三乙烯四胺循环浸出废铅膏中硫酸铅的性能研究
Study on the cyclic leaching performance of lead sulfate from waste lead paste by triethylene tetramine
陈彪 1黄明 1曹靖 2张俊丰1
作者信息
- 1. 湘潭大学 环境与资源学院,湖南 湘潭 411105
- 2. 湘潭大学 化学学院,湖南 湘潭 411105
- 折叠
摘要
废铅膏资源化是再生铅产业的重点,传统的火法熔炼存在能耗高和污染重的问题.湿法转化是一种绿色低碳的废铅膏资源化技术,但硫酸铅(PbSO4)的浸出效率和浸出剂的循环利用仍需要进一步改善.以三乙烯四胺(TETA)作为浸出剂,开展了TETA对废铅膏中PbSO4 的循环浸出研究.通过响应曲面法建立了有效浸出模型,优化了浸出反应参数,当n(TETA/PbSO4)为1.3,反应时间为11 min,液固质量比为2,反应温度为30℃时,PbSO4浸出率预测值为99.99％,实际值为 99.93％.该过程反应速率受界面化学反应步骤控制,PbSO4 浸出反应的表观活化能为47.5 kJ/mol.另外,利用Na2CO3 从 TETA-Pb 溶液中可制取杂质含量仅为 0.020 4％的高纯度PbCO3,并同时实现TETA的再生循环,对PbSO4 的10 次循环浸出率可保持在90％以上.研究结果可为废铅膏的高值化利用提供参考.
Abstract
The recycling of waste lead paste is the focus of the lead recycling industry.Traditional fire smelting has issues with high energy consumption and heavy pollution.Wet conversion is a green and low-carbon recycling technology for waste lead paste,but its leaching efficiency and recycling of leac-hing agent need further improvement.In this study,triethylenetetramine(TETA)was used as a leac-hing agent to investigate the cyclic leaching of PbSO4 from waste lead paste.An effective leaching model was established using the response surface method,and the leaching reaction parameters were optimized.With a n(TETA/PbSO4)ratio of 1.3,a reaction time of 11 minutes,a liquid-solid ratio of 2,and a reaction temperature of 30℃,the predicted leaching rate of PbSO4 was 99.99％,achieving an actual leaching rate of 99.93％.The apparent activation energy of PbSO4 leaching reaction was found to be 47.5 kJ/mol.Furthermore,high-purity PbCO3 with an impurity content of 0.020 4％could be ob-tained from TETA-Pb solution by using Na2CO3.This process allows for the regeneration cycle of TETA while maintaining a leaching rate of PbSO4 above 90％in 10 cycles.The results provide a reference for the high-value utilization of waste lead paste.
关键词
废铅膏/湿法转化/硫酸铅/三乙烯四胺/浸出Key words
Waste lead paste/Wet conversion/Lead sulfate/Triethylenetetramine/Leaching引用本文复制引用
基金项目
国家自然科学基金面上资助项目(52070159)
郴州国家可持续发展议程创新示范区建设专项(2022sfq25)
出版年
2024
国家科技期刊平台
NSTL
万方数据