Versatile Silicon‐Based Surface‐Enhanced Raman Spectroscopy Chip for Quantitative Sensing and Point‐of‐Care Applications
Abstract This study presents the development of highly sensitive, uniform, and reproducible silicon‐based Surface‐Enhanced Raman Scattering (SERS) substrates using super‐aligned carbon nanotubes (SACNT) networks as an etching mask. These substrates have been scaled up to the wafer level, offering a...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley-VCH
2025-07-01
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| Series: | Advanced Materials Interfaces |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/admi.202500375 |
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| Summary: | Abstract This study presents the development of highly sensitive, uniform, and reproducible silicon‐based Surface‐Enhanced Raman Scattering (SERS) substrates using super‐aligned carbon nanotubes (SACNT) networks as an etching mask. These substrates have been scaled up to the wafer level, offering a cost‐effective solution for point‐of‐care testing (POCT) applications. The substrates provide a dual role as both a support for high‐density hot spots and an external spectral reference, enhancing the accuracy of quantitative SERS detection. The substrates' sensitivity is demonstrated by achieving quantitative detection of BPE solution as low as 10−12 M with a monitoring deviation of less than 5%. The application of these SERS substrates in monitoring caffeine citrate concentration in urine samples for the treatment of infant apnea of prematurity is also presented, showing a strong linear relationship between SERS signal intensity and caffeine citrate concentration across clinically relevant ranges. The use of a portable Raman spectrometer with these substrates further aligns with the principles of POCT, offering convenient and cost‐effective semi‐quantitative detection. This work underscores the potential of SERS technology in advancing POCT, particularly in neonatal care, where rapid and accurate diagnostic testing is crucial for optimizing treatment plans and improving patient outcomes. |
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| ISSN: | 2196-7350 |