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Updated: Jul 18, 2026

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同时识别和检测五种抗生素使用机器学习增强的玻璃毛细血管SERS传感器

Sisi Tang¹, Ruili Li¹, Yujun Cheng¹

¹College of Chemistry and Chemical Engineering, Central South University, Changsha 410083, China.

Journal of hazardous materials

|December 24, 2025

概括

这项研究介绍了一种新的玻璃毛细血管传感器,用于检测环境样本中的多种抗生素. 表面增强的拉曼散射 (SERS) 平台实现了高精度,为污染物监测提供了一个有前途的解决方案.

科学领域:

分析化学分析化学
环境科学环境科学
材料科学材料科学材料科学

背景情况:

在复杂的环境样本中同时检测新出现的污染物,如抗生素,在分析上具有挑战性.
样本复杂性和重叠的光谱特征的干扰阻碍了实际应用.

研究的目的:

开发一个敏感和选择性的平台,在复杂的环境矩阵中同时检测多种抗生素.
为了提高分析性能,在微流体毛细体格式内利用表面增强的拉曼散射 (SERS).

主要方法:

一个玻璃毛细血管平台用银纳米粒子 (AgNPs) 稳定了由聚烯 (PVP),以创建一个SERS激活的传感表面.
使用毛细血管进行微抽样,并为五种不同的抗生素获得SERS光谱.
主要组件分析 (PCA) 和支持矢量机器 (SVM) 机器学习算法用于数据分析和分类.

主要成果:

激活SERS的毛细血管平台显示,抗生素的低检测极限 (LOD) 低至7.62 × 10-9 M.
开发的方法成功地区分和分类了五种不同的抗生素,甚至在混合样本和复杂矩阵中.
使用微升尺度样本体积的SVM模型实现了99%的高分类准确度.

结论:

激活SERS的玻璃毛细血管传感器提供了一种灵敏有效的方法,用于在复杂的环境样本中同时检测多种抗生素.
集成PCA和ML算法使得可靠的数据分析和准确的抗生素混合物的识别.
这项技术为环境监测和污染物分析提供了有前途的解决方案.

关键词:

抗生素抗生素是一种抗生素.一个毛细血管.机器学习机器学习银纳米颗粒银纳米粒子表面增强的拉曼光谱学

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