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.

中文翻译：

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Y 型沸石中的 CO2 吸附：新型主成分分析辅助原位单晶 X 射线衍射实验的结构和动态视图


实验室和大型设施中探测器效率和 X 射线亮度不断提高，可以在几分钟内收集完整的单晶 X 射线数据集。对这些“晶体学大数据”的分析需要新的工具和方法。为了满足这些需求，提出使用主成分分析（PCA）来提高分析的效率和速度。使用在 Y 沸石上原位收集的单晶 X 射线衍射 (XRD) 数据研究了 PCA 的潜力和局限性，其中 CO2 作为活性物质，在从 300 K 冷却到 200 K 的同时被热吸附。随着时间的推移，由于单晶 XRD 的高灵敏度，可以确定 CO2 被吸附的位点、温度降低时其占有率的增加以及活性物质（即 CO2、H2O 和 Na+）的相关运动。 PCA 可以识别和消除有问题的数据集，并更好地了解 CO2、Na+ 和水的占用趋势。数据的质量使得首次能够通过将范特霍夫方程应用于原位单晶数据来计算 CO2 吸附的焓 (ΔH) 和熵 (ΔS)。热力学值的计算通过传统方法和基于主成分分析的方法进行，产生了可比较的结果。获得的ΔH值显着，涉及的系统（CO2和Y沸石）无毒性、极好的稳定性和化学惰性。 这些特征，加上不存在碳酸盐形成和吸附时骨架惰性，通过单晶实验证明了块状晶体的特性，并表明这种现象可以很容易地在大量循环中逆转，并根据需要释放二氧化碳。 PCA 辅助分析的主要优点在于其速度以及直接应用于原始数据的可能性，可能作为数据收集期间的“在线”数据质量测试，而无需任何晶体结构的先验知识。