Ordered Ag/Si Nanowires Array: Wide-Range Surface-Enhanced Raman Spectroscopy for Reproducible Biomolecule Detection

Nano Letters ◽  
2013 ◽  
Vol 13 (11) ◽  
pp. 5039-5045 ◽  
Author(s):  
Jian-An Huang ◽  
Ying-Qi Zhao ◽  
Xue-Jin Zhang ◽  
Li-Fang He ◽  
Tai-Lun Wong ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Surface Enhanced Raman Spectroscopy ◽  
Si Nanowires ◽  
Biomolecule Detection ◽  
Wide Range ◽  
Surface Enhanced ◽  
Surface Enhanced Raman ◽  
Nanowires Array

scholarly journals Visible wavelength surface-enhanced Raman spectroscopy from In-InP nanopillars for biomolecule detection

2016 ◽  
Vol 109 (25) ◽  
pp. 253105 ◽  
Author(s):  
B. J. Murdoch ◽  
J. F. Portoles ◽  
S. Tardio ◽  
A. J. Barlow ◽  
I. W. Fletcher ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Surface Enhanced Raman Spectroscopy ◽  
Biomolecule Detection ◽  
Visible Wavelength ◽  
Surface Enhanced ◽  
Surface Enhanced Raman

scholarly journals Defect engineering in semiconductor-based SERS

2021 ◽  
Author(s):  
Ge Song ◽  
Shan Cong ◽  
Zhi-Gang Zhao
Keyword(s):  
Raman Spectroscopy ◽  
Surface Enhanced Raman Spectroscopy ◽  
Semiconductor Materials ◽  
Defect Engineering ◽  
Wide Range ◽  
Surface Enhanced ◽  
Surface Enhanced Raman

Semiconductor-based surface enhanced Raman spectroscopy (SERS) platforms take advantage of the multifaceted tunability of semiconductor materials to realize specialized sensing demands in a wide range of applications. However, until quite...

Morphological evolution of gold nanoparticles on silicon nanowires and their plasmonics

RSC Advances ◽  
2015 ◽  
Vol 5 (61) ◽  
pp. 49708-49718 ◽  
Author(s):  
Yuan Li ◽  
Wenwu Shi ◽  
Aditya Gupta ◽  
Nitin Chopra
Keyword(s):  
Gold Nanoparticles ◽  
Raman Spectroscopy ◽  
Silicon Nanowires ◽  
Au Nanoparticles ◽  
Morphological Evolution ◽  
Surface Enhanced Raman Spectroscopy ◽  
Si Nanowires ◽  
One Dimensional ◽  
Surface Enhanced ◽  
Surface Enhanced Raman

One-dimensional heterostructures composed of silicon (Si) nanowires and uniformly decorated with gold (Au) nanoparticles were fabricated and used as a substrate for organic detection based on the surface-enhanced Raman spectroscopy.

On-Line Spectroscopic Characterization of Sodium Cyanide with Nanostructured Gold Surface-Enhanced Raman Spectroscopy Substrates

2002 ◽  
Vol 56 (12) ◽  
pp. 1524-1530 ◽  
Author(s):  
Peter M. Tessier ◽  
Steven D. Christesen ◽  
Kate K. Ong ◽  
Eva M. Clemente ◽  
Abraham M. Lenhoff ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Surface Enhanced Raman Spectroscopy ◽  
Sodium Cyanide ◽  
Raman Signal ◽  
Gold Films ◽  
Porous Gold ◽  
Wide Range ◽  
Surface Enhanced ◽  
Surface Enhanced Raman ◽  
On Line

To implement surface-enhanced Raman spectroscopy as a practical detection method, highly enhancing, stable, and reproducible substrates need to be fabricated in an efficient manner, and their performance in different solution environments should be well characterized. In this work structured porous gold films have been fabricated using colloidal crystals to template gold nanoparticles. These films were integrated into an on-line flow chamber and used to study the effects of pH and other additives on the detection of sodium cyanide. The gold films proved to be highly enhancing and were used to detect cyanide over a wide range of pH values in the concentration range of ∼2 to 200 ppb. The Raman signal intensity could be increased by lowering the pH after the adsorption of cyanide, which was likely due to both a change in the ionization state and a conformational change of the bound molecules. The peak intensity could also be enhanced multifold by treating the substrate with silver nitrate. Cyanide could be removed from the substrates using hydrochloric acid, although this also passivated the structures, and the activity could only be restored partially with tannic acid. These results provide a rational method to optimize the online detection of cyanide in water.

The development of “fab-chips” as low-cost, sensitive surface-enhanced Raman spectroscopy (SERS) substrates for analytical applications

The Analyst ◽  
2015 ◽  
Vol 140 (3) ◽  
pp. 779-785 ◽  
Author(s):  
Ashley M. Robinson ◽  
Lili Zhao ◽  
Marwa Y. Shah Alam ◽  
Paridhi Bhandari ◽  
Scott G. Harroun ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Silver Nanoparticles ◽  
Chemical Sensing ◽  
Low Cost ◽  
Surface Enhanced Raman Spectroscopy ◽  
Sers Substrates ◽  
Sensing Applications ◽  
Wide Range ◽  
Surface Enhanced ◽  
Surface Enhanced Raman

Modification of metal-coated zari fabric chips with silver nanoparticles results in sensitive, affordable SERS substrates which are useful for a wide range of chemical sensing applications.

HAMR Emulation Using Plasmonic SERS Sensor As Near Field Transducer

2018 ◽  
Author(s):  
M. Yanagisawa ◽  
M. Kunimoto ◽  
M. Saito ◽  
T. Homma
Keyword(s):  
Raman Spectroscopy ◽  
Laser Heating ◽  
Heating Temperature ◽  
Near Field ◽  
Surface Enhanced Raman Spectroscopy ◽  
Lubricant Film ◽  
Wide Range ◽  
Surface Enhanced ◽  
Surface Enhanced Raman ◽  
Continuous Power

A plasmonic Surface-enhanced Raman Spectroscopy (SERS) sensor has been used for emulation of Near Field Transducer (NFT) in Heat-Assisted Magnetic Recording (HAMR). Laser heating mechanism by the sensor is the same as that by NFT with electro-magnetic near-field or plasmonic field, which is different from far field heating. Heating behavior for a lubricant film on a carbon overcoat for a hard disk medium was observed using Surface-enhanced Raman Spectroscopy with the plasmonic SERS sensor. Spectral change of lube films in laser heating with a continuous power changer was measured with heating temperature, calculated by anti-Stokes/Stokes intensity ratio in Raman spectra. As a result, it is found that the lubricant film composed of a tetraol perfluoro-polyether (PFPE) is evaporated above 290°C, which shows good agreement with that by TGA (Thermogravimetric Analysis). The evaporation occurs in wide range of spacing between the lubricant film and the SERS sensor from 0 (contact) to 50nm, and more. After laser heating, lubricant film with free surface in a large gap area, i.e. spacing of 3nm, is recovered with elapsed time. However it is difficult to be recovered in confined (contact) area, because lubricant mobility is small. Lost lubricant can be recovered in head flying by surface diffusion or centrifugal force during disk rotation.

Surface enhanced Raman spectroscopy substrates with advanced spectral sensitivity prepared from five years old silver nanoplatelets

2016 ◽  
Vol 09 (06) ◽  
pp. 1642003 ◽  
Author(s):  
Anna A. Semenova ◽  
Eugene A. Goodilin
Keyword(s):  
Raman Spectroscopy ◽  
Silver Nanoparticles ◽  
Spectral Sensitivity ◽  
Surface Enhanced Raman Spectroscopy ◽  
Sers Substrates ◽  
Wide Range ◽  
Surface Enhanced ◽  
Surface Enhanced Raman ◽  
Flexible Applications ◽  
First Time

A new simple approach is suggested to prepare surface enhanced Raman spectroscopy (SERS) substrates with high effectiveness for various laser excitation wavelengths and analytes with different light absorption features by impregnation of porous cellulose materials by a mixture of silver nanoplatelets with a wide range of sizes and anisotropy. The suggested route provides a much better spectral sensitivity and flexible applications since SERS as a phenomenon is essential on the nanometer scale only. The mixing provides always a proper fraction of silver nanoparticles deposited onto the substrate thus guaranteeing the enhancement of Raman signals under given excitation conditions for a wider set of given analytes. The substrates were successfully prepared for the first time from silver nanoplatelets aged for five years. This confirms high chemical and morphological stability of stabilized silver nanoparticles and the ability to use them as precursors for application - ready materials.

scholarly journals SERSNet: Surface-Enhanced Raman Spectroscopy Based Biomolecule Detection Using Deep Neural Network

Biosensors ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 490
Author(s):  
Seongyong Park ◽  
Jaeseok Lee ◽  
Shujaat Khan ◽  
Abdul Wahab ◽  
Minseok Kim
Keyword(s):  
Machine Learning ◽  
Raman Spectroscopy ◽  
Test Performance ◽  
Model Development ◽  
Surface Enhanced Raman Spectroscopy ◽  
Learning Models ◽  
Biomolecule Detection ◽  
Surface Enhanced ◽  
Surface Enhanced Raman ◽  
Machine Learning Models

Surface-Enhanced Raman Spectroscopy (SERS)-based biomolecule detection has been a challenge due to large variations in signal intensity, spectral profile, and nonlinearity. Recent advances in machine learning offer great opportunities to address these issues. However, well-documented procedures for model development and evaluation, as well as benchmark datasets, are lacking. Towards this end, we provide the SERS spectral benchmark dataset of Rhodamine 6G (R6G) for a molecule detection task and evaluate the classification performance of several machine learning models. We also perform a comparative study to find the best combination between the preprocessing methods and the machine learning models. Our best model, coined as the SERSNet, robustly identifies R6G molecule with excellent independent test performance. In particular, SERSNet shows 95.9% balanced accuracy for the cross-batch testing task.

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