Aligned Silver Nanorod Array as SERS Substrates for Viral Sensing

Content Provider	Semantic Scholar
Author	Zhao, Yiping Shanmukh, Saratchandra Chaney, Stephen B. Jones, Les P. Dluhy, Richard A. Tripp, Ralph A.
Copyright Year	2006
Abstract	A detailed discussion on a so-called glancing angle deposition technique will be presented. This technique can fabricate well-aligned three-dimensional nanostructures through computer programming. By rotating the substrate in both polar and azimuthal directions, one can fabricate desired nanostructures, such as nano-rod arrays with different shapes, nano-spring arrays, and even multilayer nanostructures. This method offers full three-dimensional control of the nanostructure with the additional capability of self-alignment. Those nanostructures can be used as biosensors. As an example, aligned silver nanorod array substrates prepared by the oblique angle deposition method are capable of providing extremely high enhancement factors (~109) at near-infrared wavelengths (785 nm) for a standard reporter molecule 1,2 trans-(bis)pyridyl-ethene (BPE). The enhancement factor depends strongly on the length of the Ag nanorods, the substrate coating, as well as the polarization of the excitation light. With the current optimum structure, we demonstrate that the detection limit for BPE can be lower than 0.1 fM. The applicability of this substrate to the detection of bioagents has been investigated by looking several viruses, such as Adenovirus, HIV, Rhinovirus and Respiratory Syncytial Virus (RSV), at low quantities (~0.5uL). Different viruses have different fingerprint Raman spectrum. The detection of virus presented in infected cells has also been demonstrated. All the results have demonstrated that the aligned Ag nanorod arrays are reproducible, high sensitive SERS substrates that have the capability to detect extremely low quantities of viruses with sensitivity, specificity and speed.
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Alternate Webpage(s)	http://fsb.missouri.edu/seminars/2006/w2006zhao.pdf
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article