Ordered arrays of Raman nanosensors for ultrasensitive and location predictable biochemical detection.
Ordered arrays of Raman nanosensors for ultrasensitive and location predictable biochemical detection.
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DOI：
10.1002/adma.201201820
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发表时间：
2012-10-23
影响因子：
29.4
通讯作者：
Fan, D. L.
中科院分区：
文献类型：
--
作者：
Xu, Xiaobin;Kim, Kwanoh;Li, Huifeng;Fan, D. L.
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Localized surface plasmon resonance (LSPR), owing to collective oscillation of conduction-band electrons in noble-metal (Au, Ag) nanostructures, induces greatly enhanced electric (E) fields in confined nanoscale locations, such as on the tips of nanorods or in the junctions of nanodimers.[1] These locations are called hotspots. In the vicinity of hotspots, Raman scattering spectra of biochemicals can be substantially amplified with E 4 dependence due to E-field enhancement of both the incident light and Raman scattering spectra.[1c] This phenomenon is called Surface Enhanced Raman Scattering (SERS)[2] and has drawn intensive research interest due to the potential applications in label-free and multiplex biochemical detection.[3] The effect of SERS is so pronounced that the enhancement factor (EF) can reach 10 10 at the junctions of Ag nanoparticles,[4] where singlemolecule events can be readily observed.[1c, 4a, 5] However, the practical applications of SERS for ultrasensitive biochemical detection is still challenging because (1) it is difficult to create a large number of hotspots with controlled junctions at a low cost for sensitive and relatively reproducible detection.[6](2) It is even more arduous to flexibly assemble the hotspots at desirable positions for location predicable sensing. Previous research in biochemical detection with SERS spectroscopy utilized aggregates of colloidal plasmonic nanoparticles, where the hotspots are random in dimensions, quantity, and location by nature.[7] The recent breakthrough of On-Wire Lithography (OWL)[8] has made it possible to control the gap sizes of metallic nanodisk/rod pairs to a few nanometers and has demonstrated single-molecule sensitivity for various biochemicals such as methylene blue,[1d] p-mercaptoaniline,[9] and Cy-3-labeled DNA.[10] However, the OWL applications are still limited by the low density of hotspots. Other methods including E-beam lithography,[11] nanosphere/colloidal lithography,[12] and porous template assisted deposition [13] were explored for sensitive and location-predictable SERS sensing. However, creating a large number of strong hotspots remains challenging due to the difficulty in controlling the gap size to only a few nanometers. Recently, an elegant concept for manufacturing self-assembled nanofingers has been explored to tackle the aforementioned problems. Li et al. have successfully created ordered arrays of gold-capped-polymer nanofingers in a large area by nanoimprint lithography.[14] Controlled numbers of nanofingers can be readily snapped together by surface tension from solvent evaporation where hotspots were created in the junctions with an EF of∼ 10 11.[14a, b] However, nanoimprint lithography requires elaborate instruments and once the mask pattern is made, the arrangement of hotspots cannot be easily altered. Based on a similar concept, Schmidt et al. economically created hotspots in assembled silver-capped Si nanopillars via maskless reactive ion etching. At the most closely packed configuration of the nanopillars, a hotspot density of 30/μm 2 and an EF 2.1× 10 11 were achieved. However, the positions of the hotspots cannot be precisely controlled due to the irregular positioning of nanopillars.[15]In this work, we tackle the aforementioned problems by economically synthesizing SERS nanocapsules and flexibly assembling them into designed arrays with electric fields for ultrasensitive and location-predictable biochemical sensing. A plasmonic nanocapsule consists of a tri-layer structure with a threesegment Ag/Ni/Ag nanorod as the core, a thin layer of silica as the capsulating layer, and uniformly distributed Ag NPs on silica as the hotspot …
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影响因子：
41.2
作者：
Lim, Dong-Kwon;Jeon, Ki-Seok;Suh, Yung Doug
通讯作者：
Suh, Yung Doug
影响因子：
3.9
作者：
Graf, C;Vossen, DLJ;van Blaaderen, A
通讯作者：
van Blaaderen, A
影响因子：
17.1
作者：
Banholzer, Matthew J.;Osberg, Kyle D.;Mirkin, Chad A.
通讯作者：
Mirkin, Chad A.
影响因子：
10.8
作者：
Kang, Taejoon;Yoo, Seung Min;Kim, Bongsoo
通讯作者：
Kim, Bongsoo
影响因子：
4.3
作者：
McMahon, Jeffrey M.;Henry, Anne-Isabelle;Schatz, George C.
通讯作者：
Schatz, George C.