饮料和制食品中酸盐的量化使用高灵敏度的电压计生物传感器,增强了多层感知神经网络
Zhongwei Liang1, Guang Yang1, Zidong Chen1
1School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 518055, PR China. chaozhanchen@foxmail.com.
Analytical methods : advancing methods and applications
|February 25, 2026
概括
使用-纳米粒子和人工智能的新电化学传感器有效检测食品和饮料中的酸盐. 它克服了盐度干扰,提高了可靠食品安全分析的准确性.
科学领域:
- 电化学 电化学 电化学
- 纳米材料科学 科学 纳米材料科学
- 食品科学 食品科学 食品科学
背景情况:
- 准确的亚酸盐检测对于食品安全至关重要,特别是在饮料和制食品等复杂的矩阵中.
- 盐度是一个重大挑战,导致传统检测方法的干扰.
研究的目的:
- 开发一种高度灵敏的电化学传感器,用于准确量化酸盐.
- 解决和补偿食品样本中的矩阵干扰,特别是盐度.
- 整合人工智能,以提高电化学传感的准确性.
主要方法:
- 用-纳米颗粒/黄金 (Pt-Pd NPs/Au/SPE) 修改的丝网打印电极的制造.
- 使用传感器增强的电催化性能,通过电化学检测化物.
- 实现多层感知子 (MLP) 神经网络与盐度计相结合,以纠正盐度诱导的矩阵效应.
主要成果:
- 该Pt-Pd NPs/Au/SPE传感器显示了1.60倍的灵敏度增强.
- 实现了广泛的线性范围 (1-7500μM),低检测极限 (0.11μM) 和高灵敏度 (226.03μA mM-1 cm-2).
- 人工智能辅助的盐度补偿显著减少了量化误差,从45.99%降至4.14%的绝对平均误差.
结论:
- 开发的传感器提供了一种可靠和灵敏的方法,用于在多种食物矩阵中检测亚酸盐.
- 由人工智能驱动的方法有效地克服了盐度干扰,提高了量化准确性.
- 本文介绍了一种实际的人工智能辅助策略,用于改善食品分析复杂样品中的电化学传感.
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