Gas Recognition‐Signal Transduction Binary Synergism in Bioinspired 2D Nanoconfined Ionic Membranes Enables Ultrasensitive NH <sub>3</sub> Perception
Conventional gas devices suffer from interfacial impedance limitations, resulting in limited sensitivity and increased power consumption due to their heterogeneous function architecture. Inspired by the uniquely integrated "recognition-transduction" mechanism discovered in insect odorant-binding proteins, 2D nanoconfined ionic membranes are developed through graphene oxide assembly-confined with ionic liquids, achieving monolithic integration of gas recognition and ion transduction. Graphene oxide nanosheets facilitate interlayer gas diffusion pathways, achieving response and recovery times of 10.86 and 13.76 s, respectively. Simultaneously, nanoconfinement enhances directional ion migration, resulting in exceptional NH<sub>3</sub> selectivity, with a theoretical detection limit of 50.14 ppb and a sensitivity of 71.55%/ppm. The gas-ion interaction enhances ion transport by promoting ion dissociation and partially releasing nanoconfinement. Operating at room temperature with an ultralow power consumption of 0.52 µW, this system enables efficient monitoring of fresh food spoilage stages, supporting artificial intelligence-assisted classification. This bioinspired platform provides a new avenue to design integrated olfactory perception systems based on ionic signal transmission to achieve intelligent operation (e.g., food packaging), further promoting the development of living organism-like intelligent systems.
Authors
- Zhihao Zhao (ORCID: https://orcid.org/0000-0001-6808-8385)
- Zhe Chen (ORCID: https://orcid.org/0000-0002-6483-6056)
- Lingyun Xu (ORCID: https://orcid.org/0009-0006-6487-6505)
- Yupeng Chen (ORCID: https://orcid.org/0000-0003-1605-9480)
- Hongyang Liu (ORCID: https://orcid.org/0000-0003-1368-3296)
- Xiaohan Sun (ORCID: https://orcid.org/0009-0004-2724-4205)
- Xingwei Jiang (ORCID: https://orcid.org/0000-0002-3429-6888)
- Lei Jiang
- Gongmo Xiang
- Weijie Wang
Institutions
- Beijing Forestry University (CN)
- Technical Institute of Physics and Chemistry (CN)
- Ministry of Education (TW)
- Beihang University (CN)
Publication Details
- Journal
- Small
- Published
- 2025-12-26
- DOI
- https://doi.org/10.1002/smll.202507249
- Primary Topic
- Gas Sensing Nanomaterials and Sensors
- Type
- article
- Field-Weighted Citation Impact
- 0.00