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Flexible Sensor Array Based on Polythiophene/Cu-MOF-Derived CuO and Polyaniline/MXene Composites for Room-Temperature Detection of Hydrogen Sulfide and Ammonia.

Created on 20 Aug 2026

Authors

Kuo Zhao, Yunbo Shi, Haodong Niu, Jinzhou Liu, Xiaohui Yang, Bolun Tang

Published in

ACS sensors. Aug 19, 2026. Epub Aug 19, 2026.

Abstract

Real-time detection of hydrogen sulfide (H2S) and ammonia (NH3) is important for occupational safety in humid, mixed-gas environments, yet conventional chemiresistive sensors remain limited by cross-sensitivity, humidity dependence, and poor portability at room temperature. Here, we report a flexible dual-channel sensor array coupled with a gated recurrent unit-convolutional neural network (GRU-CNN). A polythiophene/Cu-MOF-derived CuO composite (PTh/CuO) targets H2S through sulfur-affinitive CuO surface sites, whereas a polyaniline/Ti3C2Tx MXene composite (PANI/MXene) targets NH3 through PANI deprotonation and interfacial charge modulation. At 25 ± 1 °C, the optimized PTh/CuO and PANI/MXene channels exhibited responses of 87.5% to 100 ppm H2S and 189% to 100 ppm NH3, respectively, together with linear responses over 1-10 ppm (R2 = 0.997 and 0.998) and theoretical limits of detection of 73.3 and 40.4 ppb. Distinct responses were retained at 300 ppb H2S and 200 ppb NH3, with response/recovery times of 15/22 and 25/43 s, respectively. A GRU-CNN model trained using dynamic four-channel signals supported gas classification and concentration estimation across 0-10 ppm and 30%-80% relative humidity within the tested dataset; the maximum concentration-prediction mean squared errors were 0.020 for H2S and 0.015 for NH3. The channels retained 98.4% and 98.1% of their initial responses under 30° bending. Integration with a wireless wristband enabled remote signal acquisition and a wearable monitoring demonstration. This work combines chemically differentiated sensing channels, humidity-inclusive data analysis, and flexible wireless readout within a single room-temperature platform.

PMID:
42619411
Bibliographic data and abstract were imported from PubMed on 20 Aug 2026.

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