期刊
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
卷 163, 期 -, 页码 76-85出版社
ELSEVIER
DOI: 10.1016/j.chemolab.2017.02.012
关键词
Time-of-flight secondary ion mass spectrometry; Non-negative matrix factorization; Multivariate analysis; Hyperspectral imaging; Fingerprints; MapReduce; Large datasets; Big data
类别
资金
- Coordination for the Improvement of Higher Education Personnel - CAPES/Brazil [11995-13-0]
The development of state-of-art time-of-flight secondary ion mass spectrometry (ToF-SIMS) results in extremely large datasets. In order to perform multivariate analysis of such datasets without loss of mass and spatial resolution, appropriate data handling methods must be developed. The work in this paper presents an approach that can be taken to perform non-negative matrix factorisation (NMF) of large ToF-SIMS datasets. A large area stage raster scan of a chemically contaminated fingerprint is used as an example and the results show that the fingerprint signal was successfully separated from the substrate signal. Pre-processing challenges and artefacts that arises from the results are also discussed and an alternative approach, using the MapReduce programming model, is suggested for even larger datasets.
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