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基于拉曼特征峰平移的SERS研究进展 被引量:4

Advances on SERS Based on Shifting of Raman Characteristic Peaks
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摘要 表面增强拉曼散射(SERS)属于分子振动光谱,具有灵敏度高、选择性好、检测无损等特点,在材料、生物医学、军事等领域具有广泛的应用。目前的研究主要利用拉曼信号分子特征峰强度变化进行检测。由于受到各种因素的影响,拉曼信号分子特征峰会发生移动,相比峰强度变化,拉曼特征峰平移具有更高的稳定性和更好的重现性,由此基于拉曼特征峰平移的SERS检测应用逐渐受到关注。在总结拉曼特征峰平移机制的基础上,介绍了基于拉曼特征峰平移的SERS在癌症与疾病诊断、环境监测及食品安全检测等领域的研究进展,这些研究进展为发展具有高稳定性SERS检测方法提供了新的策略与思路。 Surface-enhanced Raman scattering(SERS)is a type of molecular vibration spectroscopy with numerous applications in materials,biomedicine,and the military due to its high sensitivity,good selectivity,and nondestructive nature.At present,the main strategy for SERS detection is using the intensity change of characteristic peaks of Raman reporters.The characteristic peaks of the Raman reporters would shift,resulting from the influence of various factors.SERS applications involving the shifting of Raman characteristic peaks have gradually gained popularity due to their higher stability and more reliable reproducibility when compared to intensity changes.In this review,we summarized the mechanism of Raman characteristic peak shifting and discussed recent advances in SERS detection based on Raman characteristic peak shifting in cancer and disease diagnosis,environmental monitoring,and food safety detection.These examples will provide new strategies and ideas for the development of high-stability SERS methods.
作者 杨建明 翁国军 李剑君 朱键 赵军武 Yang Jianming;Weng Guojun;Li Jianjun;Zhu Jian;Zhao Junwu(Key Laboratory of Biomedical Information Engineering,Ministry of Education,School of Life Science and Technology,Xi’an Jiaotong University,Xi’an,Shaanxi 710049,China;Research Institute of Xi’an Jiaotong University,Hangzhou,Zhejiang 311200,China)
出处 《激光与光电子学进展》 CSCD 北大核心 2022年第6期230-238,共9页 Laser & Optoelectronics Progress
基金 陕西省自然科学基础研究计划(2020JM-028) 陕西省重点研发计划(2020GXLH-Z-003) 浙江省自然基金-基础公益研究计划(LGF20H180017)。
关键词 生物技术 表面增强拉曼散射 拉曼特征峰平移 癌症与疾病诊断 环境监测 食品安全检测 biotechnology surface enhanced Raman scattering shifting of Raman characteristic peak diagnosis of cancer and disease environmental monitoring food safety detection
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