This technology integrates metal-organic frameworks (MOFs) with surface acoustic wave (SAW) or quartz crystal microbalance (QCM) devices to detect gas mixtures through precise frequency shifts and mass variations. A thin MOF layer, typically 100–300 nm, is deposited on SAW devices operating at 436 MHz on Y-Z LiNbO3, while alternate implementations use QCM to monitor mass-induced oscillations. Tunable MOFs such as ZIF-8, IRMOF-1, and others are selected based on their pore characteristics, with gas adsorption behavior modeled via Grand Canonical Monte Carlo simulations at 298 K and 1 bar. Data is processed through wired or wireless electronic devices, enabling real-time assessment of gas compositions.
Description
What sets this technology apart is its elimination of traditional sensor training and reduction of sensor drift through an integrated simulation-based interpretation algorithm. The method employs advanced array optimization using metrics like the Sensor Array Gas Space score and Kullback-Liebler divergence to select optimal MOF combinations. This approach leverages the predictable, tunable nature of MOF materials, offering enhanced reliability and selectivity compared to conventional polymer, metal oxide, and carbon nanotube sensors while providing robust and adaptable gas detection performance.
Applications
- Industrial gas leak detection
- Ambient air quality monitoring
- Process emission control
- Chemical plant hazard detection
- Homeland security gas detection
Advantages
- Enhanced gas detection accuracy and selectivity due to optimized MOF sensor arrays.
- Elimination of traditional sensor training requirements and significant reduction in sensor drift.
- Adaptable MOF tunability for targeting specific gas mixtures effectively.
- Versatile integration with both wired and wireless electronic devices.
- Efficient, simulation-based array optimization for cost-effective sensor configurations.
IP Status
https://patents.google.com/patent/WO2018140696A1
