Four-Dimensional Big Data Analysis Using Two-Step Multivariate Curve Resolution Technique

摘要

For research and development in material science, it is important to understand the three-dimensional (3D) distributions of chemical species in samples. The effective utilization of 4D big data which contain a lot of information about the 3D distributions is a key factor. This paper demonstrates a new 4D data analysis technique called “two-step multivariate curve resolution (MCR)”. To obtain an intuitive expression of 4D data, we devised a process involving two iterations of MCR with digitization in between. The new technique was applied to the analysis of time-of-flight secondary ion mass spectrometry data derived from a thin-film sample to assist in the interpretation of complex three-dimensional local microstructures. Compared to conventional methods of data presentation, two-step MCR was found to greatly facilitate the clarification and understanding of the 4D analysis data.