A General Method for Large-Scale Fabrication of Semiconducting Oxides with High SERS Sensitivity
- 17 April 2017
- journal article
- research article
- Published by American Chemical Society (ACS) in ACS Applied Materials & Interfaces
- Vol. 9 (16) , 14534-14544
Abstract
Surface-enhanced Raman spectroscopy (SERS) is a versatile and powerful spectroscopic technique for substance analysis and detection. So far, the highest detection sensitivities have been realized on noble nanostructure substrates, which, however, are costly, unstable, and non-biocompatible. While semiconductor substrates could in principle be used, existing realizations have either resulted in substrates with low sensitivities or used methods that have poor technical control. Here we report a general and versatile method, based on ion irradiation and vacuum annealing, for fabricating large-scale reduced semiconducting oxide SERS substrates with high sensitivities. The SERS enhancement mainly stems from oxygen vacancy-associated electronic states created by the ion irradiation of sample; these states enhance the charge-transfer (CT) mechanism between the oxide substrate and the adsorbed molecules and thus significantly magnify SERS signals. The improved carrier mobility by vacuum annealing and the introduction of impurity energy levels and nanostructures enhances further the CT efficiency. A detection limit as low as 5 × 10–8 M was achieved; this is the highest sensitivity among the reported semiconductors, and it even compares to noble metals without the aid of “hot spots”. The method is general—we demonstrate it on WO3, ZnO, and TiO2 substrates using Ar+ and N+ ion beam irradiation—and broadly applicable to produce noble-metal-free SERS substrates with high sensitivities.Keywords
Funding Information
- Program for New Century Excellent Talents in University (NCET-13-0438)
- Ministry of Education of the People's Republic of China (2042017kf0194)
- Natural Science Foundation of Jiangsu Province (BK20161247)
- Natural Science Foundation of Hubei Province (2016CFA080)
- National Natural Science Foundation of China (11375134, 11475129, 11522543, 51571153)
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