Microheater Integrated Nanotube Array Gas Sensor for Parts-Per-Trillion Level Gas Detection and Single Sensor-Based Gas Discrimination

Real-time monitoring of health threatening gases for chemical safety and human health protection requires detection and discrimination of trace gases with proper gas sensors. In many applications, costly, bulky, and power-hungry devices, normally employing optical gas sensors and electrochemical gas sensors, are used for this purpose. Using a single miniature low-power semiconductor gas sensor to achieve this goal is hardly possible, mostly due to its selectivity issue. Herein, we report a dual-mode microheater integrated nanotube array gas sensor (MINA sensor). The MINA sensor can detect hydrogen, acetone, toluene, and formaldehyde with the lowest measured limits of detection (LODs) as 40 parts-per-trillion (ppt) and the theoretical LODs of ∼7 ppt, under the continuous heating (CH) mode, owing to the nanotubular architecture with large sensing area and excellent surface catalytic activity. Intriguingly, unlike the conventional electronic noses that use arrays of gas sensors for gas discrimination, we discovered that when driven by the pulse heating (PH) mode, a single MINA sensor possesses discrimination capability of multiple gases through a transient feature extraction method. These above features of our MINA sensors make them highly attractive for distributed low-power sensor networks and battery-powered mobile sensing systems for chemical/environmental safety and healthcare applications.

Medienart:

E-Artikel

Erscheinungsjahr:

2022

Erschienen:

2022

Enthalten in:

Zur Gesamtaufnahme - volume:16

Enthalten in:

ACS nano - 16(2022), 7 vom: 26. Juli, Seite 10968-10978

Sprache:

Englisch

Beteiligte Personen:

Tang, Wenying [VerfasserIn]
Chen, Zhesi [VerfasserIn]
Song, Zhilong [VerfasserIn]
Wang, Chen [VerfasserIn]
Wan, Zhu'an [VerfasserIn]
Chan, Chak Lam Jonathan [VerfasserIn]
Chen, Zhuo [VerfasserIn]
Ye, Wenhao [VerfasserIn]
Fan, Zhiyong [VerfasserIn]

Links:

Volltext

Themen:

Gas sensor
Gases
Journal Article
Machine learning algorithm
Nanotubes, Carbon
Pulse-heating
Research Support, Non-U.S. Gov't
Single-sensor gas discrimination
Trace gas detection

Anmerkungen:

Date Completed 11.11.2022

Date Revised 08.12.2022

published: Print-Electronic

Citation Status MEDLINE

doi:

10.1021/acsnano.2c03372

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM343180340