A three-dimensional discriminant analysis approach for hyperspectral images

Morais, Camilo L. M.; Giamougiannis, Panagiotis; Grabowska, R; Wood, N; Martin‐Hirsch, Pierre L.; Martin, Francis

doi:10.1039/d0an01328e

Cited by 9 publications

(2 citation statements)

References 33 publications

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“…The contribution of each of these chemical species can be further discriminated with the help of multivariate methods, such as Principal Components Analysis (PCA), which decompose the dataset in new representations (loadings or eigenvectors) 48 – 50 . Such procedure is especially appealing in the case of spectroscopic data, as the extracted eigenvectors can be regarded as spectra on their own, enabling their interpretation in terms of the chemical species present 36 , 51 – 60 . While such methods are often prone to sample-to-sample variations 52 , 61 , requiring extensive pre-processing of the data sets and risking the introduction of artifacts, our surface potential modulation strategy allows acquisition of a large number of spectra locally (e.g., at a given spot and sample).…”

Section: Resultsmentioning

confidence: 99%

Surface potential modulation as a tool for mitigating challenges in SERS-based microneedle sensors

Brasiliense

Park

Berns

et al. 2022

Sci Rep

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Raman spectroscopic-based biosensing strategies are often complicated by low signal and the presence of multiple chemical species. While surface-enhanced Raman spectroscopy (SERS) nanostructured platforms are able to deliver high quality signals by focusing the electromagnetic field into a tight plasmonic hot-spot, it is not a generally applicable strategy as it often depends on the specific adsorption of the analyte of interest onto the SERS platform. This paper describes a strategy to address this challenge by using surface potential as a physical binding agent in the context of microneedle sensors. We show that the potential-dependent adsorption of different chemical species allows scrutinization of the contributions of different chemical species to the final spectrum, and that the ability to cyclically adsorb and desorb molecules from the surface enables efficient application of multivariate analysis methods. We demonstrate how the strategy can be used to mitigate potentially confounding phenomena, such as surface reactions, competitive adsorption and the presence of molecules with similar structures. In addition, this decomposition helps evaluate criteria to maximize the signal of one molecule with respect to others, offering new opportunities to enhance the measurement of analytes in the presence of interferants.

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Section: Resultsmentioning

confidence: 99%

Surface potential modulation as a tool for mitigating challenges in SERS-based microneedle sensors

Brasiliense

Park

Berns

et al. 2022

Sci Rep

View full text Add to dashboard Cite

show abstract

“…Many feature extraction techniques have also been developed, such as determinant estimation from the three-dimensional data (such as a hyperspectral image) with a combination of matrix decomposition. 21,22 Thus, we examined the critical factors that affect the PEC performance of hematite data with a variety of performances by applying ML using a limited number of fabricated photoelectrodes in combination with various analytical data.…”

Section: Introductionmentioning

confidence: 99%