Quantitative structural determination of active sites from in situ and operando XANES spectra: From standard ab initio simulations to chemometric and machine learning approaches

Abstract

• Different theoretical methods in the simulation of the XANES spectra are discussed. • An extended list of available codes for XANES spectra simulation is provided. • The potential of operando XANES in catalysis is described with relevant examples. • Chemometric methods in the treatment of operando XANES spectra is discussed. • Machine learning approaches are used to provide structural determination from XANES. In the last decade the appearance of progressively more sophisticated codes, together with the increased computational capabilities, has made XANES a spectroscopic technique able to quantitatively confirm (or discard) a structural model, thus becoming a new fundamental diagnostic tool in catalysis, where the active species are often diluted metal centers supported on a matrix. After providing a brief historical introduction and the basic insights on the technique, in this review article, we provide a selection of four examples where operando XANES technique has been able to provide capital information on the structure of the active site in catalysts of industrial relevance: (i) Phillips catalyst for ethylene polymerization reaction; (ii) TS-1 catalyst for selective hydrogenation reactions; (iii) carbon supported Pd nanoparticles for hydrogenation reactions; (iv) Cu-CHA zeolite for NH 3 -assisted selective reduction of NO x and for partial oxidation of methane to methanol. The last example testifies how the multivariate curve resolution supported by the alternating least-squares algorithm applied to a high number of XANES spectra collected under operando conditions allows to quantitatively determine different species in mutual transformation. This approach is particularly powerful in the analysis of experiments where a large number of spectra has been collected, typical of time- or space-resolved experiments. Finally, machine learning approaches (both indirect and direct) have been applied to determine, from the XANES spectra, the structure of CO, CO 2 and NO adsorbed on Ni 2+ sites of activated CPO-27-Ni metal-organic framework.