This chapter offers a brief overview of the current literature regarding the combination of chemometric algorithms and data fusion techniques involving LIBS and Raman spectroscopies. The two techniques allow complementary information on both the molecular structure and elemental composition of a sample under study. Furthermore, when measured simultaneously, they consent to improve characterization of complex matrixes. After a brief introduction where the concept of "data fusion" is explained, including the main data treatments used, some examples are reported illustrating how LIBS + Raman data fusion strategies allow to improve the classification of samples of different origin.
Data Fusion LIBS+RAMAN
2022
Abstract
This chapter offers a brief overview of the current literature regarding the combination of chemometric algorithms and data fusion techniques involving LIBS and Raman spectroscopies. The two techniques allow complementary information on both the molecular structure and elemental composition of a sample under study. Furthermore, when measured simultaneously, they consent to improve characterization of complex matrixes. After a brief introduction where the concept of "data fusion" is explained, including the main data treatments used, some examples are reported illustrating how LIBS + Raman data fusion strategies allow to improve the classification of samples of different origin.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
