Structure-Function Relationship of Highly Reactive CuO x Clusters on Co 3 O 4 for Selective Formaldehyde Sensing at Low Temperatures.
Matteo D'AndriaFrank KrumeichZhangyi YaoFeng Ryan WangAndreas T GüntnerPublished in: Advanced science (Weinheim, Baden-Wurttemberg, Germany) (2023)
Designing reactive surface clusters at the nanoscale on metal-oxide supports enables selective molecular interactions in low-temperature catalysis and chemical sensing. Yet, finding effective material combinations and identifying the reactive site remains challenging and an obstacle for rational catalyst/sensor design. Here, the low-temperature oxidation of formaldehyde with CuO x clusters on Co 3 O 4 nanoparticles is demonstrated yielding an excellent sensor for this critical air pollutant. When fabricated by flame-aerosol technology, such CuO x clusters are finely dispersed, while some Cu ions are incorporated into the Co 3 O 4 lattice enhancing thermal stability. Importantly, infrared spectroscopy of adsorbed CO, near edge X-ray absorption fine structure spectroscopy and temperature-programmed reduction in H 2 identified Cu + and Cu 2+ species in these clusters as active sites. Remarkably, the Cu + surface concentration correlated with the apparent activation energy of formaldehyde oxidation (Spearman's coefficient ρ = 0.89) and sensor response (0.96), rendering it a performance descriptor. At optimal composition, such sensors detected even the lowest formaldehyde levels of 3 parts-per-billion (ppb) at 75°C, superior to state-of-the-art sensors. Also, selectivity to other aldehydes, ketones, alcohols, and inorganic compounds, robustness to humidity and stable performance over 4 weeks are achieved, rendering such sensors promising as gas detectors in health monitoring, air and food quality control.
Keyphrases
- room temperature
- quality control
- aqueous solution
- metal organic framework
- low cost
- high resolution
- healthcare
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- ionic liquid
- hydrogen peroxide
- single molecule
- air pollution
- computed tomography
- mental health
- human health
- risk assessment
- highly efficient
- health information
- carbon dioxide
- quantum dots
- contrast enhanced