Cluster method for analysing surface X-ray diffraction data sets using area detectors

作     者：Leake, Steven J. Reinle-Schmitt, Mathilde L. Kalichava, Irakli Pauli, Stephan A. Willmott, Philip R. 

作者机构：Paul Scherrer Inst Swiss Light Source CH-5232 Villigen Switzerland 

出 版 物：《JOURNAL OF APPLIED CRYSTALLOGRAPHY》 (应用结晶学杂志)

年 卷 期：2014年第47卷第1期

页      面：207-214页

核心收录：

学科分类：07[理学] 070205[理学-凝聚态物理] 08[工学] 080501[工学-材料物理与化学] 0805[工学-材料科学与工程（可授工学、理学学位）] 0703[理学-化学] 0702[理学-物理学] 

基　　金：Schweizerischer Nationalfonds zur Forderung der wissenschaftlichen Forschung 

主　　题：cluster algorithms data analysis image processing surface X-ray diffraction area detectors 

摘      要：An automated cluster algorithm is described, applicable to any image where a signal is to be analysed. The algorithm is employed in the context of surface X-ray diffraction data and extended to automate the data reduction process, which at present limits both the lead time to and the reliability of the retrieved structural information. A detailed evaluation of the constraints used to automate surface X-ray diffraction data analysis is provided. To overcome limitations of the algorithm and the experiment itself in certain geometries, the full field of view of area detectors is exploited to obtain orders of magnitude improvements in data collection. The method extends the surface X-ray diffraction technique to new systems and highlights the often archaic approach to the analysis of data collected with a two-dimensional detector.