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2023
DOI: 10.1039/d3sm00170a
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Confocal Raman microscopy to evaluate anisotropic structures and hydration development. Methodological considerations

Abstract: This study demonstrates using confocal Raman microscopy to identify water regions and map the composition of various phases in situ, without sample disruption or the addition of dyes, while emphasizing the importance of proper data handling.

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Cited by 5 publications
(2 citation statements)
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“…52 Concurrently, the majority of the most recent confocal Raman microscopy studies show a preference on using automatic, unsupervised true component analysis than the other spectral analysis approaches. 51,52 However, the other analytical approaches, either based on reference spectra or cluster analysis have been also widely used for Raman Microscopy. 37,38,69,70 It is known that the use of reference spectra can potentially over-simplify the obtained information, while cluster analysis could provide biased maps with higher sampling errors, as each cluster constitutes of a mini representation of the entire population based on simple random sampling.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…52 Concurrently, the majority of the most recent confocal Raman microscopy studies show a preference on using automatic, unsupervised true component analysis than the other spectral analysis approaches. 51,52 However, the other analytical approaches, either based on reference spectra or cluster analysis have been also widely used for Raman Microscopy. 37,38,69,70 It is known that the use of reference spectra can potentially over-simplify the obtained information, while cluster analysis could provide biased maps with higher sampling errors, as each cluster constitutes of a mini representation of the entire population based on simple random sampling.…”
Section: Resultsmentioning
confidence: 99%
“…50 From area scans, image reconstruction was performed utilizing WITec Project software true component analysis function as has been described before. 51,52 This post-processing feature integrated into the WITec software determines the quantity of components within a dataset, identifies their positions within the image, and distinguishes their spectra. This function computes the hyperspectral dataset by combining the most distinct spectra using a basis analysis algorithm.…”
Section: Methodsmentioning
confidence: 99%