**5. The chemometric approach to the interpretation of XAS data**

Due to the increasing performance of many synchrotron beamlines specialized in *in situ* XAS studies, extremely large dataset containing many tens or hundreds of spectra associates to a single experiment are currently collected. This huge amount of data is calling for a suitable strategy for their treatment in reasonable time. For instance, the study of the charge or the discharge process of a battery produces something like 100–300 spectra, depending on the experimental conditions (data acquisition protocol and battery discharge rate). In similar cases, the use of chemometrics may be applied [87]. Specifically, the application of multivariate curve resolution (MCR) to large datasets of *in situ* XAS experiments (where the samples undergo continuous evolution during the reaction path) allows one to interpret their modification in terms of sums of pure spectra with variable concentration profiles, without needing any preexisting model or *a priori* information about the system. To our knowledge, the first application of MRC to a XAS study of battery materials concerns the investigation of the evolution during charge of a positive electrode based on a Cu0.1V<sup>2</sup> O5 xerogel [40]. This study, which is performed using the alternate least square (ALS) algorithm, allowed obtaining relevant information on the cell charging dynamics. In particular, the data treatment evidenced for the first time the occurrence of three species during the battery charging, which were further identified with a common EXAFS analysis. This successful chemometric approach to XAS has further been used for other *operando* studies, mostly by the catalysis community [88]. MCR was also applied to analyze XAS data from Fischer-Tropsch reaction [89] and to infer about the speciation and the evolution of ruthenium in Co − Ru/SiO2 systems by looking at quick-XAS data [90].
