Low-power biomimetic ionic thermoelectric device for multi-gas olfaction

Clicks: 21
ID: 315166
2026
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Popular

Ranked #197 of 423 articles by views in national science review

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 423 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Abstract The escalating demand for intelligent multi-gas sensing has driven the need for high-performance artificial olfactory systems with enhanced power efficiency. This work proposes an innovative gas sensing mechanism enabled by the giant ionic-thermoelectric effects in solid-state ionic polymer, which overcomes the low thermopower-to-thermal conductivity (S/κ) limitation of the conventional electronic thermoelectric materials. Using wafer-scale microfabrication technology, we demonstrate the first functional ionic-thermoelectric biomimetic olfactory device that can simultaneously resolve mixed gas analytes. This monolithic platform integrates multiple sub-100 μm sensing units, each combining an ionic-thermoelectric module with a narrow-bandpass optical filter, to selectively resolve the contributions of individual gas species in mixed-gas environments. The device achieves a record responsivity of 2340 V/W, a 20-fold improvement over commercial detectors (typically <200 V/W) and achieves limits of detection of 1.42 ppm, 0.15 ppm, and 1.16 ppb for CO2, CH4 and CO, respectively. This work establishes a promising route to next-generation artificial olfactory systems based on the ionic-thermoelectric effects.
Reference Key
openalex_W7162636041 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Gongze Liu, Cheng Chi, Jiacheng Ji, Keqiao Li, Meng Li, Yucheng Ding, Weiqi Zhang, Wenying Tang, Zhiyong Fan, Baoling Huang
Are you one of these authors? Claim your profile
Journal national science review
Year 2026
DOI
10.1093/nsr/nwag320
URL
https://doi.org/10.1093/nsr/nwag320
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.