量子化学在方铅矿浮选中的应用研究进展  

Research Progress on the Application of Quantum Chemistry in the Flotation of Galena

作　　者：姚钰昀 付博 张晨阳 陈建华 孙伟[1] YAO Yuyun;FU Bo;ZHANG Chenyang;CHEN Jianhua;SUN Wei(School of Minerals Processing and Bioengineering&Engineering,Research Center of Ministry of Education for Carbon Emission Reduction in Metal Resource Exploitation and Utilization,Central South University,Changsha 410083,China;School of Mining Engineering and Geology&Key Laboratory of Green Mining of Coal Resources in Xinjiang(XJIE),Ministry of Education,Xinjiang Institute of Engineering,Urumqi 830023,China;Xinjiang Uygur Autonomous Region Geological Exploration Quality Evaluation Center,Urumqi 830002,China;School of Resources,Environment and Materials,Guangxi University,Nanning 530004,China)

机构地区：[1]中南大学、资源加工与生物工程学院、金属资源开发利用碳减排教育部工程研究中心,长沙410083 [2]新疆工程学院、矿业工程与地质学院、新疆煤炭资源绿色开采教育部重点实验室,乌鲁木齐830023 [3]新疆维吾尔自治区地质勘查质量评价中心,乌鲁木齐830002 [4]广西大学资源环境与材料学院,南宁530004

出　　处：《有色金属（选矿部分）》2024年第9期121-133,共13页Nonferrous Metals（Mineral Processing Section）

基　　金：国家自然科学基金联合基金资助项目(U20A20269);国家重点研发计划项目(2022YFC2904503);煤炭资源与安全开采国家重点实验室-新疆工程学院联合开放研究基金资助项目(SKLCRSM-XJIE23KF005);湖南省科技创新计划项目(2022RC1183);长沙市科技计划项目(长沙市杰出创新青年培养计划)。

摘　　要：铅作为国家战略资源,其赋存矿物方铅矿分离回收至关重要,浮选法是分离方铅矿最重要的方法。量子化学以其独特的微观视角,为方铅矿浮选分离研究提供了新思路。随着高性能计算和AI技术的飞速发展,量子化学已成为矿物浮选研究不可或缺的工具。本文深入探讨了量子化学在方铅矿浮选中的应用研究进展,通过矿物晶体化学、固体物理及配位化学等多维度分析,探讨了新型捕收剂与抑制剂在浮选分离中的应用效果,并展示了量子化学在浮选药剂设计、矿物表面特性研究及药剂-矿物界面作用机制方面的最新进展;指出了准确构建初始模型与科学设置计算参数在量子化学计算中的重要性。展望未来,随着AI技术的赋能,量子化学将在方铅矿浮选体系研究中发挥更加广泛而重要的作用。基于AI机器学习的低标度和线性标度量子化学方法的发展及应用,能够对更大的矿物-药剂体系进行准确的计算模拟;此外,结合机器学习能够进一步发展基于量子化学的高精度深度势分子动力学力场,能够对复杂溶液体系进行高精度的分子动力学模拟,从而更加准确描述药剂与方铅矿作用的动态过程,为铅矿资源的高效、清洁、精细化利用提供理论和方法支撑。Lead,as a national strategic resource,the separation and recovery of its occurring mineral galena is of utmost significance.Flotation is the most critical method for the separation of galena.Quantum chemistry,with its distinctive microscopic perspective,offers novel ideas for the research on the flotation separation of galena.With the rapid advancement of high-performance computing and AI technology,quantum chemistry has emerged as an indispensable tool in the research of mineral flotation.This paper conducts an in-depth exploration of the application research progress of quantum chemistry in the flotation of galena.Through multi-dimensional analyses encompassing mineral crystal chemistry,solid physics,and coordination chemistry,it discusses the application effects of new collectors and inhibitors in flotation separation,and showcases the latest developments in the design of flotation reagents,the study of mineral surface characteristics,and the interaction mechanisms at the reagent-mineral interface.It also indicates the significance of accurately constructing initial models and scientifically setting calculation parameters in quantum chemistry computations.Looking ahead,with the empowerment of AI technology,quantum chemistry will play an even more extensive and profound role in the research of galena flotation systems.The development and application of low-scale and linear-scale quantum chemistry methods based on AI machine learning can enable accurate calculation and simulation of larger mineral-reagent systems.Additionally,the combination of machine learning can further develop high-precision deep potential molecular dynamics force fields based on quantum chemistry,allowing for high-precision molecular dynamics simulations of complex solution systems and thereby more accurately describing the dynamic process of the interaction between reagents and galena,providing theoretical and methodological support for the efficient,clean,and refined utilization of lead ore resources.

关 键 词：量子化学 浮选 机理 方铅矿 

分 类 号：TD923[矿业工程—选矿] TD952