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    磷灰石的研究进展及其在矿床学领域的应用

    Reviews on apatite and its application in the field of ore deposit geology

    • 摘要:
      研究目的 磷灰石是广泛存在于各种火山岩、变质岩和沉积岩中的一种副矿物,其晶格内可以容纳Sr、Mn、REEs、U、Th、F、Cl等多种元素,而且磷灰石的化学组成对于岩浆和热液过程十分敏感并因此引起了学者的广泛关注。
      研究方法 本文系统分析了目前关于磷灰石在矿相学、同位素年代学、矿床地球化学、人工智能以及勘查指示中的一些常用研究方法和最新成果。
      研究结果 岩浆磷灰石的Sr、Y、REEs等元素和Sr−Nd同位素可以用来判别岩浆源区,Ce、Eu、Ga、Mn等对氧逸度的敏感的元素可以用来指示岩浆氧化态,F、Cl等元素可以用来估算熔体初始状态下挥发分含量,其U−Pb年龄能代表其寄主岩的结晶年龄,而低温热年代学也常用于研究矿床形成后的剥蚀程度。热液磷灰石的结构和成分记录了流体的相关信息,可以用来指示流体来源、流体性质等与岩浆−热液成矿过程相关的信息。机器学习等人工智能技术可以处理海量磷灰石数据,实现基于磷灰石成分的岩石类型和矿床类型的判别。
      结论 磷灰石在矿床学研究和矿床勘查中具有重要作用,今后对热液磷灰石与成矿过程关系的研究工作,以及将人工智能与磷灰石结合来示踪成岩成矿过程应该是值得考虑的研究方向。

       

      Abstract:
      This paper is the result of mineral exploration engineering.
      Objective Apatite is a mineral commonly present in volcanic, metamorphic, and sedimentary rocks. Its crystal structure can host various elements such as Sr, Mn, REEs, U, Th, F, Cl, and others. Apatite's chemical composition is dictated by magma and hydrothermal processes, which makes it a subject of interest for many researchers.
      Methods This paper reviews common methods and the latest research achievements of apatite in mineralogy, isotope chronology, deposit geochemistry, artificial intelligence, and exploration indication.
      Results Elemental (e.g., Sr, Y, and REEs) and Sr−Nd isotopic compositions of magmatic apatite can help identify the source of its parental magma. Elements such as Ce, Eu, Ga, and Mn can indicate the oxidation state of the magma, while F and Cl can be used to estimate the volatile content of the melt. The U−Pb isotope system of apatite can record the crystallization age of its host rock. Low−temperature thermochronology is often used to study the degree of denudation after ore deposit formation. Hydrothermal apatite's structure and composition bear information about the fluid, which can indicate the fluid source, properties, and other information related to magmatic−hydrothermal mineralization processes. Artificial intelligence techniques such as machine learning can process massive amounts of apatite data to discriminate rock types and deposit types.
      Conclusions Apatite is a mineral that is crucial for studying mineral deposits and exploring ore deposits. Future researches should focus on the relationship between hydrothermal apatite and the metallogenic process. Additionally, combining artificial intelligence with apatite analyses to trace the diagenetic and metallogenic process is a promising avenue for further study.

       

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