| 光谱学与光谱分析 |
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| Surface-Enhanced Raman Spectra Analysis of Trace Degradation Products from Goat Horn |
| PAN Yan-ting1, AO Ning-jian1, SHAN Guang-hua2, ZHANG Gang-ping1, ZHANG Quan-bin1, YANG Ji-wang1, HE Chun-lan1, HUANG Yao-xiong1* |
1. Department of Biomedical Engineering, Jinan University, Guangzhou 510632, China
2. Department of Cardiology, The First Affiliated Hospital of Jinan University, Guangzhou 510630, China |
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Abstract Nano-silver colloid was synthesized by using microwave method on the mixtures of sodium citrate solution and silver nitrate solution. The method has advantages of fast heating speed, uniform temperature distribution and easily controlled reaction conditions. The sizes and size distributions of the silver particles were characterized by means of quasi-elastic laser scattering (QLS). The average particles size was (53.27±2.65) nm and the size of the particles was mainly distributed around 56 nm. Surface-enhanced Raman spectra of the degradation products from goat horn were obtained with silver colloid as active substrate. It was observed that the Raman signal of SERS was enhanced significantly compared with that of regular Raman spectrum, especially at the Raman bands of 659, 830, 850, 929, 999, 1 028, 1 280, 1 439 and 1 599 cm-1 which reflect the biochemical components in degradation products. The characteristic Raman bands of degradation products from goat horn were preliminary assigned. The assignments showed that the main constituents of the degradation products from goat horn were amino acids and polypeptides. It was for the first time that Surface-enhanced Raman spectroscopy was used to detect trace degradation products from the horns. Raman signal enhancement can be obtained with high sensitivity for the trace concentrations as low as ppm level. It is concluded that surface-enhanced Raman spectroscopy can provide a fast, direct and precise detecting method for the detection of trace degradation solution from horns.
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Received: 2013-06-09
Accepted: 2013-11-09
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Corresponding Authors:
HUANG Yao-xiong
E-mail: tyxhuang@jnu.edu.cn
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