Investigations into elemental analysis using laser induced breakdown spectroscopy - Ilangovan, Rishivarathan (Nanyang Technological University, 2024)
This dissertation focuses on enhancing the analytical capabilities of Laser-Induced Breakdown Spectroscopy (LIBS) for liquid samples. LIBS, as a rapid chemical analysis tool, faces specific challenges when applied to liquids due to the low signal levels and the complexity of data processing. This dissertation addresses these challenges, aiming to refine the accuracy and reliability of elemental analysis in liquid samples. The research sets two main goals: first, to compile an extensive reference database for key elements like B, C, Ca, Cu, Fe, H, K, Mg, Mn, N, Na, O, P, and S, aiming to underpin precise spectral analysis. Second, it aims to develop an algorithm specifically designed for analyzing liquid LIBS data. This algorithm is designed to simplify the identification and quantification of elements in liquid samples, a task traditionally fraught with difficulty due to the inherent limitations of liquid LIBS. The research methodology adopted consisted of several essential steps. Initially, a detailed collection of spectral data for the targeted elements (with a focus on agricultural applications) was carried out. This process was thorough, gathering data from trusted and verified sources to build a strong reference library. Next, the focus turned to the development of the algorithm for elemental identification and quantification. This algorithm was designed to be efficient and equipped to address the specific challenges of liquid LIBS data. The design of the algorithm was a continuous process, involving regular revisions and updates. Extensive testing was conducted using diverse liquid LIBS datasets. These tests were designed to assess the algorithm's accuracy in elemental identification and quantification. The performance of the algorithm was then compared with traditional analysis methods. The results indicated a significant improvement in the ease of accomplishing elemental analysis using the new algorithm. The algorithm demonstrated enhanced capability in dealing with the variability and complexity of liquid samples. The research contributes notably to the field of LIBS technology, particularly in the context of liquid sample analysis. The development of the reference data library and the specialized algorithm has the potential to transform the way liquid samples are analyzed using LIBS. The implications of this research extend beyond the immediate field, offering potential