整合环氧烯光传感器阵列和机器学习,快速选和检测 perfluoroalkyl 物质
Jiancheng Zha1, Feng Liu1, Muyuan Ma1
1School of Chemistry and Chemical Engineering, Jiangxi Science and Technology Normal University, Nanchang, 330013, PR China.
Analytica chimica acta
|October 15, 2025
概括
一个新的光传感器阵列使用宿主-客户化学和机器学习来快速地在现场检测水中的多重 perfluoroalkyl 和 polyfluoroalkyl 物质 (PFAS). 这种具有成本效益的方法实现了实验室级准确性,克服了传统测试的局限性.
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:
- 和多醇基物质 (PFAS) 是饮用水中发现的持久性环境毒素.
- 目前的检测方法,如LC-MS是昂贵的,复杂的,并不是便携式快速查.
- 现有的光传感器缺乏多重复合能力或需要复杂的制造.
研究的目的:
- 开发一种便携式,具有成本效益的传感器,用于快速,多重检测水中的PFAS.
- 克服当前单分析仪传感器和实验室分析仪器的局限性.
- 将宿主-客人化学与机器学习相结合,以进行增强的PFAS分析.
主要方法:
- 用四种染料构建了一个4x6传感器阵列,使用β-环氧化聚合物 (β-CDP) 复合物.
- 利用六个目标PFAS的差异性竞争性结合来产生独特的光模式.
- 雇佣线性歧视分析 (LDA) 和一个用于歧视和定量化的深度学习平台.
主要成果:
- 在10分钟内同时检测并量化了6种PFAS (PFOA,PFOS,PFDA,PFNA,PFHpA,PFHxA).
- 达到较低的检测极限 (PFOA为38 ng/L,PFOS为31 ng/L).
- 在真实水样 (0.66%相对误差与LC-MS) 和分类PFAS混合物中证明了高精度.
结论:
- 建立了一个主机-客户光阵列,并与机器学习相结合,用于多重PFAS检测.
- 提供了一个便携式,具有成本效益的平台,用于现场查,并具有LC-MS级准确度.
- 突出了现场部署设备的潜力,以快速评估水质和遵守法规.
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