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Permeability of 3D Templates Plays a Considerable Role in Improving the Activity of 3D Composite Surface-Enhanced Raman Scattering Substrates

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posted on 2021-04-14, 07:30 authored by Guoqiang Fang, Xiang Lin, Shuang Lin, Xinxin Li, Jinlei Wu, Xuesong Xu, Bin Dong
In recent years, anisotropic nanostructures have emerged as one of the representative surface-enhanced Raman scattering (SERS) substrates due to their outstanding characteristics, including unique morphology and tunable localized surface plasmon resonance (LSPR) properties. Herein, a spinous WO3 nanourchin (NU) array composited with anisotropic Au@Ag nanorods (NRs) as a SERS substrate with high sensitivity and reproducibility was fabricated using a layer-by-layer assembly method. In particular, the WO3 NU array with a large specific surface area was selected as a supporting platform for Au@Ag NR deposition to promote the formation of three-dimensional (3D) high-density hot spots. Subsequently, we not only demonstrate that the permeability of the 3D template vastly affects the SERS performance of the 3D composite substrate but also suggest that management of the distribution of metal nanoparticles is a novel strategy for enhancing the activity of the composite substrate. In addition, the SERS performance of the composite substrate was optimized by adjusting the length of Au@Ag NRs, and the highest SERS sensitivity was obtained with an enhancement factor of up to 1.7 × 109. Benefiting from the effective interfacial self-assembly approach, the as-prepared 3D SERS substrate exhibits excellent repeatability with a signal intensity deviation as low as 6.73%. More importantly, the dense hot spots and Raman enhancement mechanism of the WO3/Au@Ag NR substrate were also verified by the finite-difference time-domain simulation results of the electromagnetic field distributions. The WO3/Au@Ag NR composite substrate was applied to identify malachite green and crystal violet molecules with a limit of detection as low as 10–10 M. As a result, this WO3/Au@Ag NR substrate is expected to be an efficient SERS platform for reliable and sensitive chemical analysis in environmental monitoring.

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