Speaker
Description
Multivariate Curve Resolution with Alternating Least Squares (MCR-ALS) is today extensively used to solve the mixture analysis problem from Quick-EXAFS datasets recorded during the monitoring of chemical reactions, phase transitions and others [1-2]. Its objective is to decompose the XAS dataset, D, according to the bilinear relationship characteristic of Beer-Lambert spectroscopies:
D = C . ST + E (1)
where the columns of matrix C contain the relative proportions of the n pure species in the mixture, the rows of the matrix ST are the spectra of those n pure species (ST meaning the transpose of matrix S) and E is the matrix expressing the error or variance not explained by the C.ST product. The use of chemically relevant constraints (non-negativity of concentrations and/or spectra, closure relation for the concentrations …) during minimization reduces the ambiguities inherent in MCR solutions, making it possible to obtain spectra that can be satisfactorily identified by comparison with known references, by fitting or by ab initio spectra simulations.
This lecture will illustrate the power of the MCR-ALS method for isolating information of interest for the users from time-resolved datasets. The limitations of its “universal” application, particularly in the presence of co-evolving species or when spectra are too similar, will be discussed, along with strategies for overcoming them. These include data augmentation methods, such as the use of additional XAS datasets obtained by modifying experimental conditions or multimodal datasets [2-4].
The MCR-ALS use to spatially and temporally resolved datasets acquired by recently implemented full-field hyperspectral XAS imaging on the ROCK beamline [5] will conclude the presentation, highlighting the power of the chemometric method to extract high quality noise-filtered pure spectra from noisy hyperspectral imaging datasets expressed at the pixel level.
References
[1] Cassinelli, W. H., Martins, L., Passos, A. R., Pulcinelli, S. H., Santilli, C. V., Rochet, A. & Briois V. (2014). Multivariate Curve Resolution Analysis Applied to Time-Resolved Synchrotron X-ray Absorption Spectroscopy Monitoring of the Activation of Copper Alumina Catalyst. Catalysis Today 229, 114.
[2] Passos, A.R., La Fontaine, C., Rochet, A. & Briois, V. (2023). Case Studies: Time-Resolved X-Ray Absorption Spectroscopy (XAS), Springer Handbook of Advanced Catalyst Characterization (Springer), pp. 625.
[3] Rabeah, J., Briois, V., Adomeit, S., La Fontaine, C., Bentrup, U. & Brückner, A. (2020). Multivariate analysis of coupled operando EPR/XANES/ EXAFS/UV–vis/ATR–IR spectroscopy: A new dimension for mechanistic studies of catalytic gas‐liquid phase reactions. Chem. – A Eur. J. chem.202000436
[4] Plais, L., Lancelot, C., Lamonier, C., Payen, E. & Briois, V. (2021). First in-situ Temperature Quantification of CoMoS species upon Gas Sulfidation enabled by New Insight on Cobalt Sulfide Formation, Catalysis Today 377, 114.
[5] Briois, V., Itié, J.P., Polian, A., King, A., Traore, A.S., Marceau, E., Ersen, O., La Fontaine, C., Barthe, L., Beauvois, A., Roudenko, O., Belin, S. (2024). Hyperspectral Full Field Quick-EXAFS Imaging at the ROCK beamline for monitoring micrometer sized heterogeneity of functional materials under process conditions. J Synchrotron Radiation 31, 1084.
