Abstract
Laser-Induced Breakdown Spectroscopy (LIBS) has proven to be a versatile analytical technique for the detection of trace elements in various sample matrices, including hydrocarbon materials. This study focuses on optimizing LIBS parameters to enhance the accuracy and sensitivity of vanadium (V) detection in coal and hydrocarbon-based samples. A probabilistic-deterministic design of experiments (PDDoE) was employed to fine-tune key factors such as lamp energy, delay, and the number of laser impulses. Optimal settings (lamp energy: 20 J, Q-SW1: 111 µs, ΔQ-SW: 3 µs, delay: 1 µs, and 100 impulses) significantly improved the intensity of vanadium spectral lines, particularly in samples with low concentrations, achieving a limit of detection (LoD) of 0.03 % for vanadium. Calibration models were developed using Partial Least Squares Regression (PLS-R) and Multiple Linear Regression (MLR) methods. These models achieved an accuracy of 95–98 % for vanadium quantification in coal ash and hydrocarbon samples. Validation of the developed method was performed using Atomic Absorption Spectroscopy (AAS), demonstrating good correlation between predicted and experimental values. Although the method requires sample preparation and shows lower accuracy than traditional AAS, it offers a practical solution for cases where sample dissolution is difficult, such as the analysis of glasses, enamels, and geological materials. Furthermore, the method demonstrated satisfactory results in field applications, where rapid on-site analysis with portable LIBS devices was required.
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