Istituto di Fisica Applicata "N. Carrara", Consiglio Nazionale delle Ricerche, 50019 Florence, Italy.
Dipartimento di Scienze Fisiche, della Terra e dell'Ambiente, Università di Siena, 53100 Siena, Italy.
Molecules. 2022 Mar 10;27(6):1813. doi: 10.3390/molecules27061813.
Here, the potential of laser-induced breakdown spectroscopy (LIBS) in grading calcareous rocks for the lime industry was investigated. In particular, we developed a system equipped with non-intensified detectors operating in scanning mode, defined a suitable data acquisition protocol, and implemented quantitative data processing using both partial least squares regression (PLS-R) and a multilayer perceptron (MLP) neural network. Tests were carried out on 32 samples collected in various limestone quarries, which were preliminarily analyzed using traditional laboratory X-ray fluorescence (XRF); then, they were divided into two groups for calibration and validation. Particular attention was dedicated to the development of LIBS methodology providing a reliable basis for precise material grading. The congruence of the results achieved demonstrates the capability of the present approach to precisely quantify major and minor geochemical components of calcareous rocks, thus disclosing a concrete application perspective within the lime industry production chain.
在这里，研究了激光诱导击穿光谱（LIBS）在石灰工业中对钙质岩石进行分级的潜力。特别是，我们开发了一个配备非增强探测器、以扫描模式运行的系统，定义了一个合适的数据采集协议，并使用偏最小二乘回归（PLS-R）和多层感知器（MLP）神经网络实现了定量数据分析。对从不同石灰石采石场采集的 32 个样本进行了测试，这些样本最初使用传统的实验室 X 射线荧光（XRF）进行了分析；然后，它们被分为两组进行校准和验证。特别关注提供可靠基础以进行精确材料分级的 LIBS 方法的开发。所获得的结果的一致性表明，该方法能够精确地定量钙质岩石的主要和次要地球化学成分，从而在石灰工业生产链中显示出具体的应用前景。
