Dual-functional Z-scheme CdSe/Se/BiOBr photocatalyst: Generation of hydrogen peroxide and efficient degradation of ciprofloxacin.

The major challenges of clean energy and environmental pollution have resulted in the development of photocatalysis technologies for energy conversion and the degradation of refractory pollutants. Herein, a novel CdSe/Se/BiOBr hydrangea-like photocatalyst was used to produce hydrogen peroxide (H2O2) and degrade ciprofloxacin (CIP). The Z-scheme heterojunction structure of the photocatalyst and the doping of selenium (Se) led to the efficient separation of electron-hole pairs and charge transfer. The optimized sample of 2 wt% CdSe/Se/BiOBr produced 142.15 mg·L-1 rate of H2O2, which was much higher than that produced by pure BiOBr (89.4 mg·L-1) or CdSe/Se (10.9 mg·L-1). Additionally, almost 100 % of CIP was degraded within 30 min, with a first order rate constant of nearly 5.35 times that of pure BiOBr and 81.44 times that of pure CdSe/Se. The excellent removal efficiency of CIP from natural water matrices confirmed that the composites are promising for the removal of contaminants from natural waterways. Based on trapping experiments, electron spin resonance spectra (ESR) spectroscopy, and density functional theory (DFT) calculations, the photocatalytic mechanisms of H2O2 and CIP degradation by the Z-scheme CdSe/Se/BiOBr composites were proposed. Overall, the dual-functional CdSe/Se/BiOBr composite could potentially be applied for photocatalytic production of H2O2 and treatment of organic pollutants in water.

Trajectory Tracking and Obstacle Avoidance for Wheeled Mobile Robots Based on EMPC With an Adaptive Prediction Horizon.

This article develops an event-triggered model-predictive control (EMPC) strategy to realize trajectory tracking and obstacle avoidance for a wheeled mobile robot (WMR) subject to input constraints and external disturbances. In the EMPC strategy, a potential field is introduced in the cost function to guarantee a smooth path for the WMR. An event-triggered mechanism is designed to reduce the computational load of solving an optimal control problem (OCP). Moreover, an adaptive prediction horizon is utilized to further achieve computation reduction. Both recursive feasibility of the OCP and practical stability of the resulting closed-loop system are analyzed for the WMR with the input constraints and the external disturbances. Simulation results are provided to demonstrate the effectiveness and superiority of the proposed EMPC strategy.