Chemical selectivity in structure determination by the time dependent analysis of in situ XRPD data: a clear view of Xe thermal behavior inside a MFI zeolite

Abstract

X-ray diffraction methods in general provide a representation of the average structure, thus allowing only limited chemical selectivity. As recently shown [D. Chernyshov, et al., Acta Crystallogr., Sect. A: Found. Crystallogr., 2011, 67, 327], some structural information on a subset of atoms can be obtained using the modulation enhanced diffraction (MED), thus providing a new tool that is able to enhance selectivity in diffraction. MED uses a periodic stimulus supplied in situ on a crystal while diffraction data are collected continuously during one or more stimulation periods. Such large data sets can then be treated by different methods. Herein, we present and compare phase sensitive detection (PSD) and principal component analysis (PCA) for in situ X-ray powder diffraction (XRPD) data treatment. The application of PCA to MED data is described for the first time in the present paper. Simulated and experimental MED powder data were produced using an MFI zeolite as a static spectator in which Xe, acting as the active species, is adsorbed and desorbed in a periodic manner. By demodulating the simulated and experimental data, MED allowed the powder diffraction pattern of the responding scattering density to be obtained and enabled the selective extraction of crystallographic information on Xe by solving the crystal structure of the active species independently of the static zeolite framework. The "real world" experiments indicated that the PSD-MED approach has some limitations related to the degree of fulfilment of some theoretical assumptions. When applied to in situ XRPD data, PCA, despite being based on blind statistical analysis, gave results similar to those obtained by PSD (based on Fourier analysis) for simulated data. Moreover, PCA is complementary to PSD thanks to its capability of gathering information on the Xe substructure even in the presence of a non-periodic stimulus, i.e. using the most simple stimulus shape as a single temperature ramp. In particular, PC1 results are able to perfectly reproduce the corresponding 1Ω signal from a traditional PSD analysis. Moreover PCA can be applied directly to raw non periodic XRPD data, opening the possibility of using it during an "in situ" experiment. PCA can thus be envisaged as a very useful, fast and efficient tool to improve data collection and maximize data quality. To date, however, PSD remains superior for substructure solution from the analysis of 2Ω demodulated data.

New Hints on the Maya Blue Formation Process by PCA‐Assisted In Situ XRPD/PDF and Optical Spectroscopy

“…PCA scores promptly supply the reactionc oordinate, and thus the kinetic trends of solid-state reactions, without any prior structural knowledge. [21,[23][24][25] PCA loadings gave the contribution of each signal (i.e.,X RPD or FORS intensities) to each principal component.…”

“…PCA analysis : PCA and correlation analysis to unravel the kinetic trends were carried out by Rootprof, exploiting the methods developed in Ref. .…”

“…[44] PCA analysis:P CA and correlation analysis to unravel the kinetic trends were carried out by Rootprof, [22] exploiting the methods developed in Ref. [21]. Characterization techniques:T GA was collected using aS etaram SETSYS Evolution instrument under air flow,w ith ag as flow rate of 20 mL min À1 .…”

“…[19,20] Several Mayan-like pigments were investigated to understand the mutuale ffect of the organic and inorganic parts on their formation. To efficiently and coherently analyze this huge set of data (about 3000 FORS, XRPD and PDF patterns), principal component analysis (PCA) [21] was adopted, exploitingt he RootProf software. [22] This pool of techniques was appliedt oi nvestigatet he thermal treatment at different temperatures of fresh and pre-heated mixtureso fi ndigo-like dyes and palygorskite.D ye removal experiments were performed on the same samples to furtheri nvestigate the chemical stability provided by the different temperaturet reatments.…”

Frequency analysis for modulation-enhanced powder diffraction

“…If a response is nonlinear with respect to the stimulus, or a response does not obey the half-wave symmetry, then all the harmonics are linear mixtures of two diffraction components as exemplified by equation (10) approach is based on principal component analysis (PCA) applied directly to Bragg intensities (Palin et al, 2015), in particular its version adapted to MED called optimum constrained components rotation (OCCR) . The approach can potentially work with any response but, at variance with FA, assumes application of some optimization procedures minimizing certain figures of merit (see Caliandro et al, 2015, for details).…”