Self-Assembled 2D Networks of Metal Oxide Nanomaterials Enabling Sub-ppm Level Breathalyzers.

Abstract

For extremely sensitive acetone sensors, here, we introduced an alcohol-assisted surfactant-free Langmuir-Blodgett process to rapidly assemble a single-layered two-dimensional (2D) network as a suitable percolation strategy of metal oxide semiconductor nanomaterials. The single-layered 2D network formation mechanism was investigated using zinc oxide (ZnO) nanobeads (NBs). Furthermore, the correlation between the response of the gas sensor and the average percolation number of the ZnO NBs, controlled by multi-stacking the 2D network, was investigated. It was inferred that a reduction in the number of percolations led to maximization of the response. Additionally, the versatility of the optimal percolation strategy was experimentally verified by confirming similar results to that achieved with ZnO NBs when utilizing different sizes, shapes, and compositions of metal oxides. Finally, the practical effectiveness of our extremely sensitive strategy was solidified by illustrating the response enhancement in a commercial exhalation diagnostic system that measures the amount of acetone in only 1 mL of exhalation.