A monolithic nano-scale sensor architecture with tuneable gas diffusion for molecular fingerprinting
Date
2024
Authors
John, A.T.
Taheri, M.
Yuwono, J.A.
Kumar, P.
Nisbet, D.R.
Murugappan, K.
Tricoli, A.
Editors
Advisors
Journal Title
Journal ISSN
Volume Title
Type:
Journal article
Citation
Journal of Materials Chemistry A, 2024; 12(14):8155-8166
Statement of Responsibility
Alishba T. John, Mahdiar Taheri, Jodie A. Yuwono, Priyank Kumar, David R. Nisbet, Krishnan Murugappan and Antonio Tricoli
Conference Name
Abstract
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.
School/Discipline
Dissertation Note
Provenance
Description
Access Status
Rights
This journal is © The Royal Society of Chemistry 2024