scholarly journals The use of principal component analysis for fast and efficient kinetic analysis of combined in situ X-ray diffraction and spectroscopic data

2018 ◽  
Vol 74 (a2) ◽  
pp. e157-e157
Author(s):  
Marco Milanesio ◽  
Rocco Caliandro ◽  
Luca Palin ◽  
Eleonora Conterosito
2005 ◽  
Vol 77 (20) ◽  
pp. 6563-6570 ◽  
Author(s):  
Zeng Ping Chen ◽  
Julian Morris ◽  
Elaine Martin ◽  
Robert B. Hammond ◽  
Xiaojun Lai ◽  
...  

2007 ◽  
Vol 79 (5) ◽  
pp. 2091-2095 ◽  
Author(s):  
Charlene R. S. Matos ◽  
Maria José Xavier ◽  
Ledjane S. Barreto ◽  
Nivan B. Costa ◽  
Iara F. Gimenez

2019 ◽  
Vol 75 (2) ◽  
pp. 214-222 ◽  
Author(s):  
Eleonora Conterosito ◽  
Luca Palin ◽  
Rocco Caliandro ◽  
Wouter van Beek ◽  
Dmitry Chernyshov ◽  
...  

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.


2015 ◽  
Vol 48 (6) ◽  
pp. 1619-1626 ◽  
Author(s):  
Karena W. Chapman ◽  
Saul H. Lapidus ◽  
Peter J. Chupas

Developments in X-ray scattering instruments have led to unprecedented access toin situand parametric X-ray scattering data. Deriving scientific insights and understanding from these large volumes of data has become a rate-limiting step. While formerly a data-limited technique, pair distribution function (PDF) measurement capacity has expanded to the point that the method is rarely limited by access to quantitative data or material characteristics – analysis and interpretation of the data can be a more severe impediment. This paper shows that multivariate analyses offer a broadly applicable and efficient approach to help analyse series of PDF data from high-throughput andin situexperiments. Specifically, principal component analysis is used to separate features from atom–atom pairs that are correlated – changing concentration and/or distance in concert – allowing evaluation of how they vary with material composition, reaction state or environmental variable. Without requiring prior knowledge of the material structure, this can allow the PDF from constituents of a material to be isolated and its structure more readily identified and modelled; it allows one to evaluate reactions or transitions to quantify variations in species concentration and identify intermediate species; and it allows one to identify the length scale and mechanism relevant to structural transformations.


2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Tong Chen ◽  
Xingpu Qi ◽  
Zaiyong Si ◽  
Qianwei Cheng ◽  
Hui Chen

Abstract In this work, a method was established for discriminating geographical origins of wheat flour based on energy dispersive X-ray fluorescence spectrometry (ED-XRF) and chemometrics. 68 wheat flour samples from three different origins were collected and analyzed using ED-XRF technology. Firstly, the principal component analysis method was applied to analyze the feasibility of discrimination and reduce data dimensionality. Then, Competitive Adaptive Reweighted Sampling (CARS) was used to further extract feature variables, and 12 energy variables (corresponding to mineral elements) were identified and selected to characterize the geographical attributes of wheat flour samples. Finally, a non-linear model was constructed using principal component analysis and quadratic discriminant analysis (QDA). The CARS-PCA-QDA model showed that the accuracy of five-fold cross-validation was 84.25%. The results showed that the established method was able to select important energy channel variables effectively and wheat flour could be classified based on geographical origins with chemometrics, which could provide a theoretical basis for unveiling the relationship between mineral element composition and wheat origin.


2012 ◽  
Vol 10 (12) ◽  
pp. 121202-121205 ◽  
Author(s):  
Dongbo Xu Dongbo Xu ◽  
Xiangzhao Wang Xiangzhao Wang ◽  
Yang Bu Yang Bu ◽  
Lifeng Duan Lifeng Duan ◽  
Guanyong Yan Guanyong Yan ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document