Qi Man Qing, Sun Yin Xia, Liu Mei Hui, Liu Wen Jun, Li Kun, Zhou Xin Yuan
Tianjin Key Laboratory of Life and Health Detection, Life and Health Intelligent Research Institute, Tianjin University of Technology, Tianjin 300384, P. R. China.
Tianjin Key Laboratory of Film Electronic and Communication Device, Tianjin University of Technology, Tianjin 300384, P. R. China.
ACS Omega. 2025 Aug 25;10(35):39955-39961. doi: 10.1021/acsomega.5c04357. eCollection 2025 Sep 9.
Gas sensors are critical for environmental monitoring, industrial safety, and healthcare; yet, achieving target-specific selectivity in complex gas mixtures remains a challenge. Metal oxide semiconductor sensors, though cost-effective, suffer from cross-sensitivity due to poorly understood surface reaction dynamics. While noble metal functionalization improves sensitivity, selectivity mechanisms are often ambiguously attributed to oxygen activation or spillover effects without direct molecular-level evidence. Here, we demonstrate that noble metal-tailored surface engineering of InO/ITO matrices (functionalized with Au, Pt, Pd, or Ag) enables programmable selectivity by controlling catalytic pathways, as revealed through time-resolved in situ Raman spectroscopy. Unlike conventional approaches, this strategy links selectivity to gas-specific intermediate formation (e.g., formate for HCHO, nitrate/nitrite for NO), providing direct spectroscopic validation of reaction mechanisms previously inferred only indirectly. A four-channel sensor array integrating these materials achieves real-time discrimination of HCHO, NH, HS, and NO at parts per billion levels, validated by principal component analysis. This work bridges surface chemistry with device design, offering a molecular-level blueprint for gas sensors that transcends trial-and-error methodologies. By elucidating catalytic pathways and enabling multicomponent detection in dynamic environments, the approach advances applications in air quality monitoring, industrial Internet of Things, and personalized healthcare, where precise analyte discrimination in complex matrices is paramount.
气体传感器对于环境监测、工业安全和医疗保健至关重要;然而,在复杂气体混合物中实现针对特定目标的选择性仍然是一项挑战。金属氧化物半导体传感器虽然具有成本效益,但由于表面反应动力学尚不清楚,存在交叉敏感性问题。虽然贵金属功能化提高了灵敏度,但选择性机制往往被模糊地归因于氧活化或溢流效应,而没有直接的分子水平证据。在这里,我们证明,通过时间分辨原位拉曼光谱揭示,对InO/ITO基体进行贵金属定制的表面工程(用Au、Pt、Pd或Ag功能化)可以通过控制催化途径实现可编程选择性。与传统方法不同,该策略将选择性与特定气体的中间体形成联系起来(例如,HCHO的甲酸盐、NO的硝酸盐/亚硝酸盐),为以前仅间接推断的反应机制提供了直接的光谱验证。集成这些材料的四通道传感器阵列能够在十亿分之一水平上实时区分HCHO、NH、HS和NO,并通过主成分分析得到验证。这项工作将表面化学与器件设计联系起来,为超越试错方法的气体传感器提供了分子水平的蓝图。通过阐明催化途径并在动态环境中实现多组分检测,该方法推动了空气质量监测、工业物联网和个性化医疗保健等领域的应用,在这些领域中,在复杂基质中精确区分分析物至关重要。