选矿
抑制剂
尾矿
泡沫浮选
试剂
选矿
研磨
制浆造纸工业
石墨
Box-Behnken设计
响应面法
冶金
废物管理
环境科学
工艺工程
化学
材料科学
工程类
色谱法
物理化学
药理学
医学
作者
Vasumathi Nallusamy,K. Chennakesavulu,Cassandra Austen Immanuel,Ajita Kumari,K. Jayasankar,Sreejakumari Sukumaran Suseelamma,Vijayakumar Tadiparthi Venkata,Gopalkrishna Sirigeri Jois
标识
DOI:10.1080/15567036.2023.2168318
摘要
Mineral processing plants operate in capacity of hundreds/thousands of tons per day. Accordingly, chemical reagents’ usage also increases proportionally. Stringent norms toward environment sustainability question the usage of chemical reagents, especially in large quantities and tailings disposal in open areas. Hence, bioreagents have gained great interest. Froth flotation is by far the most practiced processing route for fines beneficiation and low-grade ore upgradation especially for naturally hydrophobic minerals. Flotation being a physico-chemical separation technique, flotation reagents selection plays a pivotal role in the process performance. A novel environmental-friendly biocollector, an extract from the leaves of Vitex negundo, was used as flotation collector in the present investigation for beneficiating a low-grade graphite ore with 8.67% fixed carbon. A three-factor and three-level Box-Behnken Design (BBD) under Response Surface Methodology (RSM) was employed to study the effects of important process variables such as grinding time, depressant dosage, and collector dosage on the responses, namely, ash percent of final concentrate and its recovery. A final graphite concentrate with 4.24% ash and 14.42% yield was obtained using the developed biocollector by flotation of low-grade graphite ore with 89.47% ash content. The degree of significance of input variables was determined using ANOVA. Regression models for ash content, % of final concentrate, and its %recovery was obtained from BBD analysis. It showed that the grinding time has a significant influence on the process followed by depressant dosage on the grade of final concentrate and collector dosage on its recovery.
科研通智能强力驱动
Strongly Powered by AbleSci AI