2022
DOI: 10.1016/j.snb.2022.132273
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A plug-and-play 3D hydrodynamic focusing Raman platform for label-free and dynamic single microparticle detection

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Cited by 7 publications
(3 citation statements)
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References 39 publications
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“…This ultimately resulted in the emergence of a single-stream focus by the time the particles arrived at loops 12 and 13. The results showed that similar to other studies, implementing consecutive channel lengths within the SLDCOM channel can facilitate the enhancement of particle focusing. It is worth noting that due to the limitation of fluorescent microsphere trajectories, this experimental phenomenon did not prove that the focusing locations of different-sized particles were completely consistent.…”
Section: Resultssupporting
confidence: 89%
“…This ultimately resulted in the emergence of a single-stream focus by the time the particles arrived at loops 12 and 13. The results showed that similar to other studies, implementing consecutive channel lengths within the SLDCOM channel can facilitate the enhancement of particle focusing. It is worth noting that due to the limitation of fluorescent microsphere trajectories, this experimental phenomenon did not prove that the focusing locations of different-sized particles were completely consistent.…”
Section: Resultssupporting
confidence: 89%
“…11a). 78 The platform assembled by a coaxial needle, a quartz capillary, a 3D printing holder and soft silicone tube (Fig. 11b).…”
Section: D-printed Biosensors and Biomedical Detection Devicesmentioning
confidence: 99%
“…Raman spectroscopy has been utilized extensively in the biological sector to analyze the composition, characteristics, and interactions of substances because of its noninvasive measurement capabilities and label-free molecular fingerprinting capabilities. Raman spectral data typically contains rich intrinsic information about samples, which exhibit continuity with high-dimensional characteristics and reflect the scattering features of substances at continuous wavenumbers . Numerous chemical compositions with distinctive molecular information are present in various cell phenotypes, which have the ability to be utilized to identify and analyze individual cells at the single-cell level. However, cells have similar chemical composition and biomolecular structure, especially with the low Raman scattering cross-section, which brings about the subtle spectral differences, low signal-to-noise ratio, and Raman peak overlap . In traditional machine learning methods, feature engineering is typically employed to effectively extract relevant information due to the low signal-to-noise ratio characteristic of raw Raman spectra.…”
mentioning
confidence: 99%