College of Control Science and Engineering, China University of Petroleum (East China), Qingdao 266580, China.
ACS Sens. 2024 Apr 26;9(4):2000-2009. doi: 10.1021/acssensors.3c02793. Epub 2024 Apr 7.
This study presents a colorimetric/electrical dual-sensing system (CEDS) for low-power, high-precision, adaptable, and real-time detection of hydrogen sulfide (HS) gas. The lead acetate/poly(vinyl alcohol) (Pb(Ac)/PVA) nanofiber film was transferred onto a polyethylene terephthalate (PET) flexible substrate by electrospinning to obtain colorimetric/electrical sensors. The CEDS was constructed to simultaneously record both the visual and electrical response of the sensor, and the improved Manhattan segmentation algorithm and deep neural network (DNN) were used as its intelligent algorithmic aids to achieve quantitative exposure to HS. By exploring the mechanism of color change and resistance response of the sensor, a dual-sensitivity mechanism explanation model was proposed to verify that the system, as a dual-mode parallel system, can adequately solve the sensor redundancy problem. The results show that the CEDS can achieve a wide detection range of HS from 0.1-100 ppm and identify the HS concentration in 4 s at the fastest. The sensor can be stabilized for 180 days with excellent selectivity and a low limit of detection (LOD) to 0.1 ppm of HS. In addition, the feasibility of the CEDS for measuring HS levels in underground waterways was validated. This work provides a new method for adaptable, wide range of applications and low-power, high-precision HS gas detection.
本研究提出了一种用于低功耗、高精度、自适应和实时检测硫化氢 (HS) 气体的比色/电双传感系统 (CEDS)。通过静电纺丝将醋酸铅/聚乙烯醇 (Pb(Ac)/PVA) 纳米纤维膜转移到聚对苯二甲酸乙二醇酯 (PET) 柔性基底上，得到比色/电传感器。CEDS 被构建为同时记录传感器的视觉和电响应，改进的曼哈顿分割算法和深度神经网络 (DNN) 被用作其智能算法辅助，以实现对 HS 的定量暴露。通过探索传感器颜色变化和电阻响应的机制，提出了一种双灵敏度机制解释模型，以验证该系统作为双模式并行系统，可以充分解决传感器冗余问题。结果表明，CEDS 可以实现从 0.1-100 ppm 的宽 HS 检测范围，并在最快的 4 s 内识别 HS 浓度。传感器可以稳定 180 天，对 0.1 ppm 的 HS 具有出色的选择性和低检测限 (LOD)。此外，还验证了 CEDS 用于测量地下水道中 HS 水平的可行性。这项工作为自适应、宽应用范围和低功耗、高精度 HS 气体检测提供了一种新方法。
