Suppr超能文献

从印刷电路板废料中回收金属的优化研究

Optimization Studies on Recovery of Metals from Printed Circuit Board Waste.

作者信息

Sivakumar P, Prabhakaran D, Thirumarimurugan M

机构信息

Department of Chemical Engineering, Coimbatore Institute of Technology, Coimbatore 641 014, Tamil Nadu, India.

出版信息

Bioinorg Chem Appl. 2018 Nov 1;2018:1067512. doi: 10.1155/2018/1067512. eCollection 2018.

Abstract

The aim of the study was to recover copper and lead metal from waste printed circuit boards (PCBs). The electrowinning method is found to be an effective recycling process to recover copper and lead metal from printed circuit board wastes. In order to simplify the process with affordable equipment, a simple ammonical leaching operation method was adopted. The selected PCBs were incinerated into fine ash powder at 500°C for 1 hour in the pyrolysis reactor. Then, the fine ash powder was subjected to acid-leaching process to recover the metals with varying conditions like acid-base concentration, electrode combination, and leaching time. The relative electrolysis solution of 0.1 M lead nitrate for lead and 0.1 M copper sulphate for copper was used to extract metals from PCBs at room temperature. The amount of lead and copper extracted from the process was determined by an atomic absorption spectrophotometer, and results found were 73.29% and 82.17%, respectively. Further, the optimum conditions for the recovery of metals were determined by using RSM software. The results showed that the percentage of lead and copper recovery were 78.25% and 89.1% should be 4 hrs 10 A/dm.

摘要

本研究的目的是从废弃印刷电路板(PCBs)中回收铜和铅金属。电解沉积法被发现是一种从印刷电路板废料中回收铜和铅金属的有效回收工艺。为了用经济实惠的设备简化工艺,采用了一种简单的氨浸操作方法。将选定的印刷电路板在热解反应器中于500°C下焚烧1小时,制成细灰粉。然后,将细灰粉进行酸浸工艺,在不同条件下(如酸碱浓度、电极组合和浸出时间)回收金属。使用0.1 M硝酸铅的相对电解液回收铅,0.1 M硫酸铜的相对电解液回收铜,在室温下从印刷电路板中提取金属。通过原子吸收分光光度计测定该工艺中提取的铅和铜的量,结果分别为73.29%和82.17%。此外,使用响应曲面法(RSM)软件确定了金属回收的最佳条件。结果表明,铅和铜的回收率分别为78.25%和89.1%时,条件应为4小时、10 A/dm²。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1fd0/6236970/733f613de52d/BCA2018-1067512.001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验