Progress in the principle and application of zircon trace element

Abstract

锆石是地质学研究中最重要的副矿物，其分布广泛、物理、化学性质稳定，记录了结晶时的年龄、温度、氧逸度以及O-Hf-Si-Zr-Li等多元同位素和微量元素信息，被广泛运用于地球科学的研究中。近年来，随着分析技术的发展，研究者在获取锆石年龄的同时也获取了大量锆石微量元素数据，这些数据的积累推动着研究者对锆石微量元素理论研究的不断深入，并取得了一系列重要进展，如发现锆石微量元素组成受锆石本身的晶格特点主导，符合晶格应变模型和类质同象替代机制；发现锆石微量元素组成受到熔体成分演化影响，锆石结晶时的熔体微量元素组成往往不等同于全岩；发现锆石内部的微量元素不均一特征（矿物包裹体、热点、蜕晶化作用等）可能会严重影响锆石的微量元素组成，继而建立了干净锆石的判别指标和筛选机制。此外，锆石微量元素的应用研究也取得了长足进展，研究者们不断尝试通过各类锆石微量元素指标、图解、分配系数，识别母岩浆物理化学性质、反演母岩浆组成，大大推动了锆石微量元素在示踪岩浆源区和岩浆过程中的应用。然而，由于锆石微量元素组成受控于多种因素，使得锆石微量元素在实际应用当中常常面临着多解性问题、重叠问题和分配系数的选择问题，在一定程度上影响了锆石微量元素应用研究的可靠性。未来的锆石微量元素研究将不满足于使用传统的低维指标和图解以及分配系数，而将在充分吸收传统方法精华的基础上，从海量数据与更高的维度中寻找元素之间相关性，基于热力学定律揭示新原理，基于更高空间分辨率揭示动力学因素的影响，从数据驱动和理论驱动的全新视角下深入揭示隐藏在锆石微量元素中的信息。;Zircon is widely used in geological studies due to its chemical and physical robustness, widespread in a series of rock types and multiple geochemical usages kept in isotopes, trace elements and inclusions. The relatively recent development of analysis allows simultaneous determination of age and trace element, which builds a big trace elements dataset and helps make progress in the principle of zircon trace elements, such as revealing the concentration and the distribution of trace elements in zircon are dominated by zircon's lattice, which is ruled by lattice strain model and substitution mechanism, affected by the trace element composition of melt that zircon crystallized from rather than that of the whole rock, and even not robust if inclusions, alteration, hot spots or metamictization in zircon were not properly screened. In addition, researchers also make progress in the application of zircon trace element such as using zircon trace element indexes, diagrams and partitioning coefficients to trace the composition, type and tectonics backgrounds of parental magma source, largely extended the usage in igneous rocks studies. However, we should notice that, the multiple explanations of zircon trace element indexes, the overlapping of zircon trace element diagrams and the dispute of partition coefficients may weaken the robustness in using zircon trace elements to tracing magma sources and processes. The future zircon trace element studies will not be limited by the traditional low-dimensional indexes, diagrams and partitioning coefficients, instead, will use new tools, such as machine learning methods and analysis with higher spatial resolution, to find more correlation between zircon trace element and to reveal the thermal or dynamic factors that affect the zircon trace elements. In a data-driven and theoretical driven perspective, we will reveal more geological and geochemical information hidden behind zircon trace elements.

Topics & Concepts