A Monolithic Nano-Scale Sensor Architecture with Tuneable Gas Diffusion for Molecular Fingerprinting

Semiconducting metal oxide (SMO) gas sensors have emerged as an invaluable technology due to their high sensitivity and ease of fabrication. However, they have limited selectivity and require relatively high operational temperatures. Here, we present a monolithic membrane-chemoresistive sensor consisting of a hierarchical metal oxide (MO) and a metal-organic framework (MOF) layer. Both layers were made by sequential aerosol deposition of SnO2 and ZnO nanoparticles, with the latter being thereafter converted to zeolitic imidazolate framework (ZIF-8) by chemical vapour conversion. The SnO2 fractal network provides a high surface area for chemical sensing, while the multi-scale porous ZIF-8 membrane offers a controlled gateway for gas molecule diffusion. Notably, our hierarchical dual-layer architecture can tune the analyte sensor response time, allowing discrimination of a variety of gases, including NO2, ethanol, acetone, methanol, propane, and ethyl benzene. Density Functional Theory (DFT) calculations were implemented to gain further insights into the selectivity mechanism revealing the key role of surface adsorption sites. This approach enables us to develop unique response profiles, fingerprinting the presence of specific gas molecules, with application ranging from industrial safety to environmental monitoring and medical diagnostics. Selective chemoresistive gas sensors using a monolithic membrane-sensing layer architecture.