Hierarchical ZnO Nanoflowers with Tunable Defect Chemistry for Highly Selective Formaldehyde Detection: Elucidating Structure−Property−Kinetics Relationships

Achieving highly selective and sensitive formaldehyde detection remains a critical challenge for reliable indoor air-quality monitoring. Here, we report hierarchical ZnO nanoflowers with tunable defect chemistry that enables a direct and quantitative correlation between structure, surface defects, and sensing kinetics. Controlled variation of growth temperature systematically modulates crystallinity, microstrain, and oxygen vacancy concentration, leading to pronounced differences in sensing performance. The optimized ZnO-110 architecture exhibits a high response of 362 toward 300 ppm formaldehyde at 270 °C, along with rapid response/recovery times of 58/91 s and excellent selectivity against interfering gases. The experimentally estimated limit of detection (LOD) was calculated to be 5.93 ppb, which is significantly lower than the World Health Organization (WHO) indoor formaldehyde exposure guideline (∼80 ppb), demonstrating strong potential for practical indoor air-quality monitoring applications. The sensing response follows a power-law dependence on concentration, consistent with surface reaction-controlled kinetics. Kinetic analysis based on an Eley−Rideal-type mechanism, supported by Arrhenius behavior, reveals a low activation energy of 0.383 eV, indicating favorable adsorption−reaction pathways. Photoluminescence and EPR analyses further confirm the critical role of optimized oxygen vacancy concentration in governing adsorption behavior and charge-transfer dynamics. Beyond conventional analysis, a data-driven artificial neural network captures concentration-dependent deviations and nonlinear sensing trends associated with defect-mediated surface interactions, reinforcing the experimentally observed behavior. The superior sensing performance arises from the synergistic coupling of hierarchical morphology, optimized defect density, and efficient charge transport. This work establishes a unified structure−property−kinetics framework and provides a scalable strategy for designing high-performance metal oxide gas sensors without noble metal functionalization.