Interface engineering of mesoporous SnO2/TiO2 heterojunction with tailored defects for light-motivated gas sensor
Year: 2026
Type: article
Abstract: The convergence of embodied intelligence, neuromorphic computing, and the Internet of Things has propelled intelligent gas sensors to the forefront of artificial olfaction, enabling adaptive, context-aware, and biologically inspired odor perception. Tailoring active sites or defects in sensing materials is an efficient strategy to confer selective gas-surface recognition constitutes for amplifying sensor sensitivity. Herein, a facile ligand-mediated interfacial co-assembly strategy was developed to construct mesoporous crystalline SnO2/TiO2 composites, which enables a composition-dependent structural evolution from Sn-substituted TiO2 solid solutions to well-defined n-n heterojunctions. Density functional theory (DFT) calculations reveal that Sn4+ ions can be substitutionally incorporated into the TiO2 lattice to form charge-balanced Sn-O-Ti bridging units, whereas excessive Sn induces spontaneous phase separation to establish SnO2/TiO2 heterojunctions. The optimized mesoporous hybrids exhibit ∼22-fold higher photocurrent and ∼4-fold stronger light-motivated ethanol sensing response than pristine mesoporous TiO2 under identical conditions. The outstanding performance was attributed to the site-selective doping that effectively tune the local electronic structure and promote the efficient separation and directional transport of photogenerated charges. In-situ doping allows for the tailoring engineering of the pore wall chemical microenvironment, affording an active interface conducive to target gas adsorption and detection reactions. This study establishes a design paradigm for coupling surface reactivity regulation with charge transfer engineering in light-activated gas sensors.
Source: National Science Review
DOI: 10.1093/nsr/nwag584
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,000
OpenAlex ID: W7212049633
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