Noble Metal-Tailored Surface Engineering Enables Programmable Selectivity in MOS Gas Sensors via Catalytic Pathway Control

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 In<sub>2</sub>O<sub>3</sub>/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<sub>3</sub>, H<sub>2</sub>S, 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.

Authors

Institutions

Publication Details

Journal
ACS Omega
Published
2025-08-25
DOI
https://doi.org/10.1021/acsomega.5c04357
Citations
2
Primary Topic
Gas Sensing Nanomaterials and Sensors
Type
article
Field-Weighted Citation Impact
1.46

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Noble Metal-Tailored Surface Engineering Enables Programmable Selectivity in MOS Gas Sensors via Catalytic Pathway Control

Y. Sun, Xinyuan Zhou, Mei Hui Liu, Kun Li et al.
2 citations
ACS Omega
Gas Sensing Nanomaterials and Sensors
1.46
article

Noble Metal-Tailored Surface Engineering Enables Programmable Selectivity in MOS Gas Sensors via Catalytic Pathway Control

Y. Sun, Xinyuan Zhou, Mei Hui Liu, Kun Li, Wenjun Liu, Ming Qi
article en
2 citations

Abstract

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 In<sub>2</sub>O<sub>3</sub>/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<sub>3</sub>, H<sub>2</sub>S, 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.

ACS OmegaVol. 10(35)
Tianjin University of Science and Technology (CN), Tianjin University of Technology (CN), Intelligent Health (United Kingdom) (GB)
Tianjin University of Technology, National Natural Science Foundation of China, Chinese Academy of Sciences, China Postdoctoral Science Foundation, Tianjin University, Natural Science Foundation of Tianjin City
Openalex Percentile: Top 15%
Gas Sensing Nanomaterials and Sensors
1.46
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.