利用微生物开发矿物底土的研究进展

Q4 Biochemistry, Genetics and Molecular Biology
G. Jandieri, D. Sakhvadze, B. Schukin
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引用次数: 0

摘要

这篇小型综述专门分析了相对较少使用的天然矿物地下生物采矿的现状。在此分析的基础上,证实了细菌浸出技术对于环境安全且经济收支平衡的含矿岩石和含金属岩层的开采来说是不可替代的,这些岩层难以接近,或者传统方法无利可图。强调生物技术的效率取决于金属生物提取过程工作参数的建模和操作控制的准确性,为此有必要开发一种新的联合水力技术系统,该系统可能对浸出过程产生相反的技术影响。这一过程的控制模式是强制曝气的强度、细菌溶液的pH值、营养培养基的量和浸出时间。为了提高地下微生物发展预测和控制的准确性,建议采用基于自适应网络的模糊推理系统(ANFIS)控制方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Underground Development of Mineral Subsoil Using Microorganisms: A Mini-Review
This mini-review is devoted to the analysis of the current state of the relatively rarely used underground bio-mining of natural minerals. On the basis of this analysis, it is substantiated that bacterial leaching technology has no alternative for environmentally safe and economically break-even mining of ore-bearing rocks and off -balance metal-bearing formations that are difficult to access, or unprofitable for traditional methods. It is emphasized that the efficiency of biotechnology depends on the accuracy of modeling and operational control of the working parameters of the process of biological extraction of metals, for which it is necessary to develop a new combined hydro-technical system with the possibility of the reverse technological influence on the regimes of leaching. Such controlled modes of the process are the intensity of forced aeration, pH level of the bacterial solution, amount of nutrient medium, and duration of leaching. To improve the accuracy of prediction and control of underground microbiological development, the use of a control method based on an adaptive-network-based fuzzy inference system (ANFIS) is recommended.
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来源期刊
Mikrobiolohichnyi zhurnal
Mikrobiolohichnyi zhurnal Medicine-Microbiology (medical)
CiteScore
0.70
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