High-Wavenumber Raman Analysis

Yang, Shan

doi:10.5772/intechopen.100474

Cited by 3 publications

(1 citation statement)

References 32 publications

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“…All spectra were collected with an accumulation time of 1 s and 100 iterations. A full range of wavelength shifts (10–4000 cm −1 ) was collected for all samples and was later truncated to 300–2000 cm −1 representing the fingerprint region, which is generally sufficient for material identification 47 .…”

Section: Methodsmentioning

confidence: 99%

A microfluidic approach for label-free identification of small-sized microplastics in seawater

Gong

Martínez

Mesquita

et al. 2023

Sci Rep

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Marine microplastics are emerging as a growing environmental concern due to their potential harm to marine biota. The substantial variations in their physical and chemical properties pose a significant challenge when it comes to sampling and characterizing small-sized microplastics. In this study, we introduce a novel microfluidic approach that simplifies the trapping and identification process of microplastics in surface seawater, eliminating the need for labeling. We examine various models, including support vector machine, random forest, convolutional neural network (CNN), and residual neural network (ResNet34), to assess their performance in identifying 11 common plastics. Our findings reveal that the CNN method outperforms the other models, achieving an impressive accuracy of 93% and a mean area under the curve of 98 ± 0.02%. Furthermore, we demonstrate that miniaturized devices can effectively trap and identify microplastics smaller than 50 µm. Overall, this proposed approach facilitates efficient sampling and identification of small-sized microplastics, potentially contributing to crucial long-term monitoring and treatment efforts.

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Section: Methodsmentioning

confidence: 99%

A microfluidic approach for label-free identification of small-sized microplastics in seawater

Gong

Martínez

Mesquita

et al. 2023

Sci Rep

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Comparison of clinical efficacy of three different dentin matrix biomaterials obtained from different devices

Dłucik¹,

Orzechowska-Wylęgała

Dłucik³

et al. 2023

Expert Review of Medical Devices

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Multi-layered silicone-based breast tissue phantom for multi-modal optical spectroscopy

Jayasankar,

Narayanan Unni

2024

Biomed. Phys. Eng. Express

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The heterogeneity, non-uniform nature, and ethical concerns in sourcing biological tissues pose several challenges to designing, calibrating, standardizing, and evaluating the performance of spectroscopy-based diagnostic methods. A synthetic phantom module that can resemble a multi-layered tissue structure while including multiple tissue biomarkers with long-shelf life and stability is vital to overcome these challenges. This work uses a multi-layered silicone phantom to incorporate multiple biomarkers suitable for multi-modal spectroscopy testing and calibration. The phantom mimics the microcalcification distribution in the breast tissues using hydroxyapatite and the endogenous fluorescence seen in the tissues using Flavin Adenine Dinucleotide (FAD) and Nicotinamide Adenine Dinucleotide (NADH). The utility of this phantom for tumor margin analysis is analyzed using Diffuse reflectance, fluorescence, and Raman spectroscopy. The observed relative differences in intensity with changes in the silicone tumor layer depth and thickness are suitable for instrument calibration and fiber-optic probe design for tumor margin analysis.

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High-Wavenumber Raman Analysis

Cited by 3 publications

References 32 publications

A microfluidic approach for label-free identification of small-sized microplastics in seawater

A microfluidic approach for label-free identification of small-sized microplastics in seawater

Comparison of clinical efficacy of three different dentin matrix biomaterials obtained from different devices

Multi-layered silicone-based breast tissue phantom for multi-modal optical spectroscopy

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