Abstract
The increasing efficiency of detectors and brightness of X-rays in both laboratory and large-scale facilities allow the collection of full single-crystal X-ray data sets within minutes. The analysis of these `crystallographic big data' requires new tools and approaches. To answer these needs, the use of principal component analysis (PCA) is proposed to improve the efficiency and speed of the analysis. Potentialities and limitations of PCA were investigated using single-crystal X-ray diffraction (XRD) data collected in situ on Y zeolite, in which CO2, acting as an active species, is thermally adsorbed while cooling from 300 to 200 K. For the first time, thanks to the high sensitivity of single-crystal XRD, it was possible to determine the sites where CO2 is adsorbed, the increase in their occupancy while the temperature is decreased, and the correlated motion of active species, i.e. CO2, H2O and Na+. PCA allowed identification and elimination of problematic data sets, and better understanding of the trends of the occupancies of CO2, Na+ and water. The quality of the data allowed for the first time calculation of the enthalpy (ΔH) and entropy (ΔS) of the CO2 adsorption by applying the van 't Hoff equation to in situ single-crystal data. The calculation of thermodynamic values was carried out by both traditional and PCA-based approaches, producing comparable results. The obtained ΔH value is significant and involves systems (CO2 and Y zeolite) with no toxicity, superb stability and chemical inertness. Such features, coupled with the absence of carbonate formation and framework inertness upon adsorption, were demonstrated for the bulk crystal by the single-crystal experiment, and suggest that the phenomenon can be easily reversed for a large number of cycles, with CO2 released on demand. The main advantages of PCA-assisted analysis reside in its speed and in the possibility of it being applied directly to raw data, possibly as an `online' data-quality test during data collection, without any a priori knowledge of the crystal structure.
Highlights
The availability of faster detectors and brighter laboratory and large-scale facility X-ray sources allows the collection of a full single-crystal X-ray diffraction (XRD) data set within seconds to minutes and the automatic collection of data sets increases dramatically the number of collected crystal structure data sets
The novel approach named ‘serial crystallography’ at X-ray free-electron laser (XFEL) facilities will further increase the amount of data and crystal structure data sets to be analysed (Standfuss & Spence, 2017 and references therein)
We recently demonstrated that principal component analysis (PCA) can unravel kinetic trends without a structural model when applied to X-ray powder diffraction (XRPD) data (Guccione et al, 2018; Palin et al, 2015, 2016) and in the present article we extend for the first time its application to single-crystal XRD data
Summary
In situ single-crystal structural studies can be carried out to examine simple and slow kinetics (minutes to hours, or while studying systems at equilibrium as in the present work), with laboratory facilities (Vergentev et al, 2015). Taking into account these considerations, the number of collected data sets will soon greatly override the capacity of structure refinement analysis by the traditional manual approach, where the human operator analyses one crystal data set at a time. It is evident that there is an increasing need for efficient tools to manage and analyse large single-crystal data sets coming from in situ and/or serial crystallography.
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