Using the hydrolysis of tetraethylorthosilicate, a uniform and conformal layer of porous SiO(2) with controlled thickness has been coated onto the oblique angle deposited Ag nanorod (AgNR) array to form an aligned AgNR-SiO(2) core-shell array nanostructure. The morphology, optical property, SERS response, and surface wettability of the AgNRs with different SiO(2) shell thicknesses have been obtained by multiple characterization techniques. The morphological characterization shows that each AgNR on the array is coated with a uniform and porous silica shell independently and the growth of shell thickness follows a linear function versus the coating time. Thickening of the shell induces a monotonic decrease of the apparent contact angle, red-shift of the transverse mode of the localized surface plasmon resonance peak, and makes the SiO(2) shell more compact. The SERS response of 4-Mercaptophenol on these substrates exhibits an exponential decay behavior with the increasing coating time, which is ascribed to the decreasing Ag surface coverage of core-shell nanorods. Under the assumption that the Ag surface coverage is proportional to the SERS intensity, one can estimate the evolution of SiO(2) coverage on AgNRs. Such coverage evolution can be used to qualitatively explain the LSPR wavelength change and quantitatively interpret the contact angle change based on a double Cassie's law.
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http://dx.doi.org/10.1021/la203772u | DOI Listing |
ACS Sens
June 2024
Department of Physics and Astronomy, The University of Georgia, Athens, Georgia 30602, United States.
An integrated approach combining surface-enhanced Raman spectroscopy (SERS) with a specialized deep learning algorithm to rapidly and accurately detect and quantify SARS-CoV-2 variants is developed based on an angiotensin-converting enzyme 2 (ACE2)-functionalized AgNR@SiO array SERS sensor. SERS spectra with concentrations of different variants were collected using a portable Raman system. After appropriate spectral preprocessing, a deep learning algorithm, CoVari, is developed to predict both the viral variant species and concentrations.
View Article and Find Full Text PDFRSC Adv
January 2024
Department of Electrical Engineering and Department of Physics, National Central University Chungli 32001 Taiwan
The thermoelectric properties of armchair graphene nanoribbons (AGNRs) with array characteristics are investigated theoretically using the tight-binding model and Green's function technique. The AGNR structures with array characteristics are created by embedding a narrow boron nitride nanoribbon (BNNR) into a wider AGNR, resulting in two narrow AGNRs. This system is denoted as -AGNR/-BNNR, where '' and '' represent the widths of the wider AGNR and narrow BNNR, respectively.
View Article and Find Full Text PDFChem Soc Rev
January 2024
School of Electrical and Computer Engineering, College of Engineering, The University of Georgia, Athens, GA 30602, USA.
Recently, there has been an exponential growth in the number of publications focusing on surface-enhanced Raman scattering (SERS), primarily driven by advancements in nanotechnology and the increasing demand for chemical and biological detection. While many of these publications have focused on the development of new substrates and detection-based applications, there is a noticeable lack of attention given to various practical issues related to SERS measurements and detection. This review aims to fill this gap by utilizing silver nanorod (AgNR) SERS substrates fabricated through the oblique angle deposition method as an illustrative example.
View Article and Find Full Text PDFJ Phys Condens Matter
August 2023
School of Materials and Chemical Technology, Tokyo Institute of Technology, Yokohama, Kanagawa 226-8502, Japan.
Formation and electronic states of graphene nanoribbons with arm-chair edges (AGNR) are studied on the SiC(0001) vicinal surfaces toward the [11-00] direction. The surface step and terrace structures of both 4H and 6H-SiC substrates are used as the growth templates of one-dimensional arrays of AGNRs, which are prepared using the carbon molecular beam epitaxy followed by hydrogen intercalation. A band gap is observed above the-band maximum by angle-resolved photoelectron spectroscopy (ARPES) for the both samples.
View Article and Find Full Text PDFACS Sens
January 2023
Department of Physics and Astronomy, The University of Georgia, Athens, Georgia30602, United States.
A rapid and cost-effective method to detect the infection of SARS-CoV-2 is fundamental to mitigating the current COVID-19 pandemic. Herein, a surface-enhanced Raman spectroscopy (SERS) sensor with a deep learning algorithm has been developed for the rapid detection of SARS-CoV-2 RNA in human nasopharyngeal swab (HNS) specimens. The SERS sensor was prepared using a silver nanorod array (AgNR) substrate by assembling DNA probes to capture SARS-CoV-2 RNA.
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