拉曼散射
材料科学
分析化学(期刊)
准确度和精密度
化学
线性
检出限
微流控
琼脂糖
拉曼光谱
响应时间
干扰(通信)
相对标准差
持续监测
色谱法
灵敏度(控制系统)
航程(航空)
光电子学
线性范围
散射
理论(学习稳定性)
作者
Yan Chen,Zhiyang Zhang,Yanzhou Wu,Peng Liu,Yifan Sui,Xiao‐Tong Su,Jiadong Chen,Jaebum Choo,Lingxin Chen
出处
期刊:ACS Sensors
[American Chemical Society]
日期:2025-11-04
卷期号:10 (11): 8975-8982
标识
DOI:10.1021/acssensors.5c03124
摘要
Surface-enhanced Raman scattering (SERS)-based pH sensors have been widely applied; However, the used 4-mercaptobenzoic acid (4-MBA) probes exhibit small pH-sensitive peak changes (carboxyl group) and strong susceptibility to interference, leading to inaccurate measurements. To address these limitations, we developed a SERS pH sensor using 2,5-dimercaptoterephthalic acid (2,5-DMTA) as the probe, which contains dual carboxyl groups. These carboxyl groups undergo reversible protonation-deprotonation, producing pronounced and reproducible spectral responses that enhance detection accuracy. The developed sensor enabled reliable detection across the acidic pH range of 0-7, showing good linearity (R2 = 0.9786) and compensating for the weak acidic response of 4-MBA. Importantly, the 2,5-DMTA-based pH sensor demonstrated much better detection accuracy (detection relative standard deviation RSD less than 5%) than the 4-MBA-based SERS pH sensor (detection RSD ≈ 20%). To further improve measurement accuracy in complex matrices, the sensor was embedded in hot agarose to form an AuNP@hydrogel substrate, effectively suppressing interference from small molecules. Moreover, the developed sensor also shows satisfactory online pH monitoring features, including good reversibility (≥6 cycles), high stability of continuous measurements (30 min), and long-term storage stability (30 days). Integrated with a microfluidic 3D-printed flow cell, the system enabled rapid response (∼120 s) and online pH monitoring, and was successfully applied to continuous testing in lake water. Overall, this SERS platform provides a robust and accurate solution for SERS-based pH detection under acidic and complex environmental conditions.
科研通智能强力驱动
Strongly Powered by AbleSci AI