In the present study, a series of Ce-Zr binary metal oxides (Ce x Zr 1−x -T, x = 0.2, 0.5, 0.8) with variable physicochemical characteristics were developed for fast pyrolysis of cellulose, wherein thermal decomposition behaviors and kinetics were investigated using TG-MS and Py-GC/MS methods. Comprehensive characterizations including XRD, NH 3 -TPD, CO 2 -TPD, and SEM were conducted to unveil the essential structural properties of as-prepared Ce x Zr 1−x -T materials. Ce x Zr 1−x -T calcined at 450 °C and 550 °C could supply suitable medium to strong acid–base sites and good porosity for the pyrolysis of cellulose into ketones, aldehydes, and hydrocarbons, especially for Ce 0.8 Zr 0.2 –550. Elevation of heating rate and catalyst usage significantly promoted the yielding of ketones, aliphatic hydrocarbons, and aromatic hydrocarbons. Moreover, the activation energy for cellulose pyrolysis was lowered to 96.9 kJ/mol in the presence of Ce 0.8 Zr 0.2 –550, due to the promotional role of existing acid–base sites.
Given the level of phosphate ion (Pi) is a significant indicator of eutrophication in environmental waters, it becomes quite important to develop efficient methods for its monitoring. In this research, we developed a smartphone-assisted off─on photometric approach for Pi analysis based on the analyte-promoted peroxidase-mimicking catalytic activity of porous Ce x Zr 1-x O 2 (x ≥ 0.5) nanocomposites. The Ce 4+ /Ce 3+ redox pair in Ce x Zr 1-x O 2 endowed it with certain activity to catalyze the 3,3′,5,5′-tetramethylbenzidine (TMB) color reaction with the participation of H 2 O 2 , and both the existing Zr 4+ and Ce 4+ species enabled the nanozyme to specifically recognize Pi. It was observed that the bonded Pi could greatly promote the peroxidase-like activity of the Ce x Zr 1-x O 2 nanocomposite towards positively charged TMB. According to the new finding, high-performance sensing of Pi with wide detection range, high sensitivity and good selectivity was realized, giving a detection limit down to 0.09 μM. Further, a 3D-printed smartphone-based signal reading system was designed and coupled with the sensing method, enabling the rapid, convenient, in-field and instrument-free analysis of Pi for environmental monitoring.
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