分析物
多路复用
校准
传感器阵列
测距
灵敏度(控制系统)
功勋
检出限
生物系统
组分(热力学)
计算机科学
色谱法
分析化学(期刊)
化学
生物信息学
数学
机器学习
物理
统计
电子工程
生物
工程类
计算机视觉
热力学
电信
作者
Zahra Jafar-Nezhad Ivrigh,Arafeh Bigdeli,Somayeh Jafarinejad,M. Reza Hormozi-Nezhad
标识
DOI:10.1016/j.snb.2022.131855
摘要
Pattern-based sensing with multi-component sensor arrays, despite its merits, may be laborious and time-consuming. As an alternative approach, herein, a condition-based single component sensor array has been provided which represents an elegantly simple, low cost and minimally instrumented format for the quantification and classification of antidepressants (ADs). Tuning the pH and ionic strength enabled the single component probe to interact with the target analytes through different binding modes, providing the required cross-reactivity for multiplex detection. The analytical figures of merit verified that the condition-based sensor array is precise and accurate in both the discrimination and quantification of the ADs. Excellent sensitivity and selectivity were achieved in the discrimination of the ADs. Moreover, low limit of detections (as low as 0.009 μg.mL−1) and wide linear ranges (up to four orders of magnitude) were attained in the multivariate calibration of each AD. The results of multivariate calibration (R2cal>0.99 and R2cv>0.99) and classification (sensitivity 100% and specificity 100%) of ADs in human urine ensured the practicability of the array in complex biological fluids. Furthermore, the wide-ranging colorimetric responses that appeared due to the different environment sensitive aggregation patterns allowed visual detection.
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