The optimization of the surface-enhanced Raman scattering for quantitative analysis and detection of molecules. Issue 14 (September 2016)

• Record Type: Journal Article
• Authors: Jeffrey Kuo, Chung-Feng; Su, Te-Li; Tsai, Jia-Cheng; Pan, Sheau-Shi
• Is Part Of: Textile research journal. Volume 86:Issue 14(2016)
• Page Start: 1474
• Page End: 1486
• Publication Date: 2016-09
• Subjects: surface-enhanced Raman scattering -- Taguchi method -- genetic algorithm -- back-propagation neural network; Textile industry -- Periodicals; Textile fabrics -- Periodicals; Textile research -- Periodicals; Textiles et tissus -- Industrie et commerce -- Périodiques; Textiles et tissus -- Périodiques; Textiles et tissus -- Recherche -- Périodiques; Electronic journals; 677.005
• DOI: 10.1177/0040517515576330
• Languages: English
• ISSNs: 0040-5175

Abstract

This study produced colloidal silver nanoparticle solution, and used the silver nanoparticles in the colloidal silver solution to adsorb dye molecule rhodamine 6 G, measure the surface-enhanced Raman scattering (SERS), and test the ability of colloidal silver nanoparticle solution to detect unimolecules. The Taguchi method was used for optimizing experimental parameters. The SERS and Blinking signals were measured. The two groups of single quality optimum parameter combinations were used as the parental gene of the first-generation population in the genetic algorithm, evolving the next-generation population of high fitness function value. The back-propagation neural system was used as the fitness function indicator of the genetic algorithm, until the gene combination of multi-quality optimization is evolved. Finally, the multi-quality optimal preparation parameter combination was determined as sodium chloride content of 600 μl, mixing time of 90 min, sodium borohydride concentration of2 × 10 - 2 M, and dye molecule concentration of10 - 11 M . The intensity of SERS and unimolecule detection capability were validated by confirmation experimentation.