Applications of laser induced breakdown spectroscopy in geotechnical engineering: a critical review of recent developments, perspectives and challenges

Atomic spectrometry update – a review of advances in environmental analysis

“…A review (163 references) of applications of LIBS in geotechnical engineering covered 147 recent developments, perspectives and challenges. Various applications in mineralogy, soil studies, rock investigations and fluid analysis were discussed, as well as calibration-free LIBS methods such as chemometrics, ANNs and support vector machines for quantification.…”

“…A review (162 references) provided 147 a useful overview of recent progress and challenges in the application of LIBS to geotechnical samples. It included: information on the fundamental principles of LIBS; physical and chemical matrix effects; spectral pre-processing methods; quantitative analysis (both with calibration and calibration-free); and chemometric approaches for information extraction.…”

A Review of Development in the Research of Self-Absorption on Laser-Induced Breakdown Spectroscopy

“…Compared to other spectroscopy approaches, [2][3][4] LIBS offers several distinct advantages, including (i) a simple and quick procedure that does not require sample preparation; (ii) simultaneous multi-elemental analysis; 5 (iii) competence for remote detection; 6 (iv) in-situ analysis; [7][8][9] (v) validity for a broad range of analytes, [9][10][11][12][13][14][15] among others. Currently, it is widely used in atmospheric particle detection, 19 corrosion detection, 20 environmental and agricultural, 21 food crop detection, 22 and medical diagnosis. 23,24 However, the LIBS technique faces several critical challenges due to the complex of the spatial-temporal evolution of plasma.…”

Investigating the Soil Unconfined Compressive Strength Based on Laser-Induced Breakdown Spectroscopy Emission Intensities and Machine Learning Techniques

“…Additionally, machine learning has been employed to solve problems in engineering, sciences, energy, construction, business, and medicine, to mention a few. ,− A couple of works exist where machine learning techniques were used to conduct a calibration-free LIBS study. , This was supported by the ability of the laser-induced spectroscopy device to produce sufficient input datasets and the capacity of machine learning algorithms to process them. − Studying the physical properties of soils under LIBS is utterly cumbersome. However, considering the built-in capability of machine learning techniques to map complex patterns, it can be trained using the acquired chemical properties to predict the physical properties, such as soil UCS, as conducted in the current work.…”

“… 25 , 26 This was supported by the ability of the laser-induced spectroscopy device to produce sufficient input datasets and the capacity of machine learning algorithms to process them. 27 − 31 Studying the physical properties of soils under LIBS is utterly cumbersome. However, considering the built-in capability of machine learning techniques to map complex patterns, it can be trained using the acquired chemical properties to predict the physical properties, such as soil UCS, as conducted in the current work.…”