Raman Analysis of Dilute Aqueous Samples by Localized Evaporation of Submicroliter Droplets on the Tips of Superhydrophobic Copper Wires

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• 作者：Melody Cheung ; Wendy W. Y. Lee ; John N. McCracken ; Iain A. Larmour ; Steven Brennan ; Steven E. J. Bell
• 刊名：Analytical Chemistry
• 出版年：2016
• 出版时间：April 19, 2016
• 年：2016
• 卷：88
• 期：8
• 页码：4541-4547
• 全文大小：468K
• 年卷期：0
• ISSN：1520-6882

文摘

Raman analysis of dilute aqueous solutions is normally prevented by their low signal levels. A very general method to increase the concentration to detectable levels is to evaporate droplets of the sample to dryness, creating solid deposits which are then Raman probed. Here, superhydrophobic (SHP) wires with hydrophilic tips have been used as supports for drying droplets, which have the advantage that the residue is automatically deposited at the tip. The SHP wires were readily prepared in minutes using electroless galvanic deposition of Ag onto copper wires followed by modification with a polyfluorothiol (3,3,4,4,5,5,6,6,7,7,8,8,9,9,10,10,10-heptadecafluoro-1-decanethiol, HDFT). Cutting the coated wires with a scalpel revealed hydrophilic tips which could support droplets whose maximum size was determined by the wire diameter. Typically, 230 μm wires were used to support 0.6 μL droplets. Evaporation of dilute melamine droplets gave solid deposits which could be observed by scanning electron microscopy (SEM) and Raman spectroscopy. The limit of detection for melamine using a two stage evaporation procedure was 1 × 10^–6 mol dm^–3. The physical appearance of dried droplets of sucrose and glucose showed that the samples retained significant amounts of water, even under high vacuum. Nonetheless, the Raman detection limits of sucrose and glucose were 5 × 10^–4 and 2.5 × 10^–3 mol dm^–3, respectively, which is similar to the sensitivity reported for surface-enhanced Raman spectroscopy (SERS) detection of glucose. It was also possible to quantify the two sugars in mixtures at concentrations which were similar to those found in human blood through multivariate analysis.