Department of Chemistry Ugo Schiff, University of Florence, 50019 Sesto Fiorentino, Italy.
Department of Earth Sciences, University of Florence, 50121 Florence, Italy.
Analyst. 2023 Jun 12;148(12):2861-2870. doi: 10.1039/d3an00441d.
Here, we demonstrate, for the first time, the possibility of distinguishing between geogenic and anthropogenic calcite in a non-destructive and effective way. Geogenic calcite derives from natural sedimentary and metamorphic rocks whereas anthropogenic calcite is formed artificially due to the carbonation process in mortars and plaster lime binders. Currently, their distinction is a major unaddressed issue although it is crucial across several fields such as C dating of historical mortars to avoid contamination with carbonate aggregates, investigating the origins of pigments, and studying the origins of sediments, to name a few. In this paper, we address this unmet need combining high-resolution micro-Raman spectroscopy with data mining and machine learning methods. This approach provides an effective means of obtaining robust and representative Raman datasets from which samples' origins can be effectively deduced; moreover, a distinction between sedimentary and metamorphic calcite has been also highlighted. The samples, chemically identical, exhibit systematic and reliable differences in Raman band positions, band shape and intensity, which are likely related to the degree of structural order and polarization effects.
在这里，我们首次展示了一种非破坏性且有效的方法来区分地质成因和人为成因的方解石。地质成因的方解石来自于天然的沉积岩和变质岩，而人为成因的方解石则是由于砂浆和石膏石灰粘合剂中的碳化过程而人工形成的。目前，尽管在几个领域（如历史砂浆的 C 年代测定以避免与碳酸盐骨料的污染、研究颜料的起源以及研究沉积物的起源等）都需要区分它们，但这仍然是一个未解决的主要问题。在本文中，我们结合高分辨率微拉曼光谱和数据挖掘以及机器学习方法来解决这个问题。这种方法为从样品中获取稳健且具有代表性的拉曼数据集提供了有效的手段，从而可以有效地推断出样品的来源；此外，还突出了沉积岩和变质岩成因的方解石之间的区别。这些化学性质相同的样品在拉曼谱带位置、谱带形状和强度上表现出系统且可靠的差异，这可能与结构有序度和极化效应有关。
