Large-Area Au-Nanoparticle-Functionalized Si Nanorod Arrays for Spatially Uniform Surface-Enhanced Raman Spectroscopy

Abstract

In this study, large-area hexagonal-packed Si nanorod (SiNR) arrays in conjunction with Au nanoparticles (AuNPs) were fabricated for surface-enhanced Raman spectroscopy (SERS). We have achieved ultrasensitive molecular detection with high reproducibility and spatial uniformity. A finite-difference time-domain simulation suggests that a wide range of three-dimensional electric fields are generated along the surfaces of the SiNR array. With the tuning of the gap and diameter of the SiNRs, the produced long decay length (>130 nm) of the enhanced electric field makes the SERS substrate a zero-gap system for ultrasensitive detection of large biomolecules. In the detection of R6G molecules, our SERS system achieved an enhancement factor of >10 with a relative standard deviation as small as 3.9-7.2% over 30 points across the substrate. More significantly, the SERS substrate yielded ultrasensitive Raman signals on long amyloid-β fibrils at the single-fibril level, which provides promising potentials for ultrasensitive detection of amyloid aggregates that are related to Alzheimer's disease. Our study demonstrates that the SiNRs functionalized with AuNPs may serve as excellent SERS substrates in chemical and biomedical detection.

Surface-Enhanced Raman Spectroscopy-Based Label-Free Insulin Detection at Physiological Concentrations for Analysis of Islet Performance

“…To the best of our knowledge, this is the first demonstration of clinically-relevant, spatially uniform protein sensing on-chip using a highly enhancing nonresonant SERS substrate, whereas other reports have achieved highly uniform and sensitive detection only with smaller molecules such as Rhodamine 6G. [31][32][33][34] Based on surface interactions, other gold-based SERS surfaces should elicit similar adsorption behavior and allow detection of insulin in principle although the resulting accuracy and sensitivity of qualitative sensing may vary from substrate to substrate. The limit of detection far exceeds previously reported label-free optical sensing-based results and can be further improved by using molecule-concentrating techniques and post-measurement signal processing.…”

“…[27][28][29][30] In this study, we report highly sensitive SERS-based insulin sensing at clinically relevant concentrations using a non-resonant SERS substrate with strong signal enhancement and wafer- 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 5 scale uniformity. [31][32][33][34] The sensors were batch-fabricated using a simple two-step process that produced 3 dimensional (3D) gold-nanoparticle (Au-NP) clusters packed densely in a vertical, pillar-like arrangement. 33 The 3D pillar-like geometry of the clusters adsorb and excite insulin molecules with vertically packed plasmonic hotspots uniformly over a large surface area for enhanced Raman emissions.…”

“…Given the size of insulin molecules, even if there were a second layer sitting on top of the first layer, the second layer would be too far away from the surface to significantly benefit from the near-field enhancement on the surface, and the Raman-emission contribution by the second and/or third layers would be minimal. 39 The signal-to-noise ratio (SNR) at 100 pM was calculated to be approximately 8.5, and the theoretical detection limit was calculated to be 35 pM for a minimum acceptable SNR of 3.For typical SERS substrates, even a small displacement of the incident laser could often lead to a huge change in Raman signal intensity due to non-uniformly distributed SERS hotspots.In order to improve the consistency of SERS measurements, recent focus has been placed on improving the chip-scale measurement uniformity either by implementing better substrates, [31][32][33][34] or employing better measurement strategies such as areal averaging, 35-36 which involves scanning a larger area on the substrate to collect and average more Raman-signal data points as opposed to 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 7 making a single point measurement. Two-dimensional (2D) mapping of Raman spectra was performed over a 1×1 mm 2 area with a step size of 20 µm on a chip coated with a 10-nM insulin solution (Figure 2c).…”

“…In order to improve the consistency of SERS measurements, recent focus has been placed on improving the chip-scale measurement uniformity either by implementing better substrates, [31][32][33][34] or employing better measurement strategies such as areal averaging, [35][36] which involves scanning a larger area on the substrate to collect and average more Raman-signal data points as opposed to 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 making a single point measurement. Two-dimensional (2D) mapping of Raman spectra was performed over a 1×1 mm 2 increasing the average scan area from 50×50 µm 2 to 400×400 µm 2 reduces the RSD from 3.6% to 1.7%.…”

Quantitative SERS by hot spot normalization – surface enhanced Rayleigh band intensity as an alternative evaluation parameter for SERS substrate performance

“…38 Since I Rayleigh reflects the “hot spot” efficiency from a single pixel across a SERS substrate, the variation in I Rayleigh is expected to be an indicator of SERS substrate uniformity. To illustrate this, two SERS substrates – AuNP/BC-1.2 and AgNP/BC-250 that exhibited large differences in uniformity, were used as test samples.…”