Publication Date:
2022
abstract:
Laser-induced breakdown spectroscopy (LIBS) spectra are characterized by a redundancy of information that makes the use of multivariate methods for building calibration surfaces particularly suited. In the previous chapter, the case of linear calibration surfaces in all the coordinates considered was discussed. However, many effects in LIBS may produce a nonlinear dependence of the signal from the concentration of the elements in the sample. In the past decades, several multivariate nonlinear chemometric methods have been proposed and successfully tested for LIBS analytical applications. In this chapter, we will present a general overview and some examples on the application of these techniques.
Iris type:
02.01 Contributo in volume (Capitolo o Saggio)
Keywords:
LIBS; Quantitative analysis; Multivariate nonlinear algorithms; Artificial neural networks; Convolutional neural networks; Kalman filter; Calibration-free LIBS
List of contributors: