Electroreduction of CO 2 into formic acid (HCOOH) is of great economical value and potential for industrialization. However, it is still a substantial challenge due to the lack of efficient catalysts with simultaneously high activity, selectivity, and durability. Herein, a single‐atom bismuth loaded on N‐doped hollow carbon sphere (Bi–SA/NHCS) catalyst is reported and its catalytic activity and selectivity are modulated by changing the coordination structure of Bi center. The obtained Bi–SA/NHCS with a Bi–N 3 site exhibits significantly enhanced electrocatalytic activity and selectivity of HCOOH synthesis from CO 2 reduction. The HCOOH production rate achieves 16.2 mmol L −1 h −1 cm −2 at a current density of 20 mA cm −2 , and its Faradaic efficiency remains 100% during a long‐term reaction. The HCOOH production rate normalized by catalyst loading is at a molar level of nearly 1.5 mol h −1 g cat −1 . The production rate and Faradaic efficiency of HCOOH electrosynthesis on Bi–SA/NHCS are significantly boosted as compared with other catalysts reported in the literature. Experimental and density‐functional theory results demonstrate that the boosted activity and selectivity of HCOOH synthesis owe to the electronic structure modulation to the Bi center via threefold coordinated N‐ligands, leading to a proper binding energy of HOCO* intermediates.
Unbridled anthropogenic activities severely disrupt natural nitrogen cycles, leading to significant environmental and energy-related issues, including eutrophication of water and high levels of energy consumption in industrial nitrogen fixation. A feasible and promising approach towards attaining sustainable zero-carbon nitrogen cycles is the utilization of clean electrical energy to convert nitrate pollutants in water bodies into high-value nitrogen products. In this study, metal (Ru/Co/Ni) doped Cu electrodes were synthesized for the electrocatalytic synthesis of NH4+ at room temperature. The Ru-Cu CF electrode demonstrated exceptional performance, achieving a nitrate removal rate of 99.9% (2000 mg/L NO3--N) and a selectivity of 91.2% for the synthesis of NH4+. Furthermore, the feasibility of practical application was verified using electroplating wastewater, where it was found that the Ru-Cu CF electrode not only effectively converted NO3- to NH4NO3, but also successfully recovered Cu2+ from the wastewater. This discovery has the potential to optimize laborious and environmentally damaging industrial synthetic processes into efficient, green alternatives, thereby providing important theoretical guidance and practical value for the development of green and clean ammonia synthesis processes.
Multi-robot systems have increasingly become instrumental in tackling search and coverage problems. However, the challenge of optimizing task efficiency without compromising task success still persists, particularly in expansive, unstructured environments with dense obstacles. This paper presents an innovative, decentralized Voronoi-based approach for search and coverage to reactively navigate these complexities while maintaining safety. This approach leverages the active sensing capabilities of multi-robot systems to supplement GIS (Geographic Information System), offering a more comprehensive and real-time understanding of the environment. Based on point cloud data, which is inherently non-convex and unstructured, this method efficiently generates collision-free Voronoi regions using only local sensing information through spatial decomposition and spherical mirroring techniques. Then, deadlock-aware guided map integrated with a gradient-optimized, centroid Voronoi-based coverage control policy, is constructed to improve efficiency by avoiding exhaustive searches and local sensing pitfalls. The effectiveness of our algorithm has been validated through extensive numerical simulations in high-fidelity environments, demonstrating significant improvements in both task success rate, coverage ratio, and task execution time compared with others.
Abstract Finding efficient and sustainable methods for the remove of 2,4,6-trinitrotoluene (TNT) from industrial wastewater is an important research area in the field of environment. This paper explores the application of sustainable biomass-derived carbon produced from rice straw for the adsorption of 2,4,6-trinitrotoluene (TNT) red water. The rice straw-derived biochar (SBC) materials were synthesized by two-step reactions through hydrothermal carbonization and chemical activation with KOH. Characterization of the fabricated biochar was conducted using various techniques. Here the chemical oxygen demand (COD) was used as an evaluation index for adsorption efficiency. The adsorption kinetics showed a good fit with the pseudo-second-order model, and the adsorption equilibrium was achieved in 30 min. The biochar’s high surface area (1319 m 2 /g) and large pore volume (1.058 cm 3 /g) gave it a large adsorption capacity. The Langmuir model exhibited better correlation for equilibrium data analysis, with a maximum adsorption capacity of 173.9 mg/g at 298 K. The SBC was found to have a high removal effect over a wide pH range (from 1 to 13) and showed remarkable stability after undergoing five desorption-adsorption cycles using ethanol and acetone as eluent. The results provide a simple and low-cost method for the efficient treatment of TNT red water.
The traditional visual servoing of robot is difficult to calibrate the parameters accurately. At present, Kalman filter is used to estimate the image Jacobian matrix, but the noise parameter setting is not appropriate, so the servoing is not accurate. The traditional STOA(Sooty Tern Optimization Algorithm) algorithm is improved by using the adaptive search radius strategy to improve its local convergence ability, and the improved STOA algorithm is used to optimize the noise parameters of Kalman filter, and the penalty term coefficient of the objective function is improved to find the optimal noise parameters under the current system model. Based on the optimal noise parameters obtained in this paper, the noise parameters are applied to the robot eye-in-hand structure, and the image Jacobian matrix is estimated online at each moment, so as to realize the calibration free visual servoing of the robot.
Unbridled anthropogenic activities severely disrupt natural nitrogen cycles, leading to significant environmental and energy-related issues, including the eutrophication of water and high levels of energy consumption in industrial nitrogen fixation. A feasible and promising approach toward attaining sustainable zero-carbon nitrogen cycles is the utilization of clean electrical energy to convert nitrate pollutants in water bodies into high-value nitrogen products. In this study, metal (Ru/Co/Ni)-doped Cu electrodes were synthesized for the electrocatalytic synthesis of NH4+ at room temperature. The Ru–Cu CF electrode demonstrated exceptional performance, achieving a nitrate removal rate of 99.9% (2000 mg·L–1 NO3––N) and a NH4+–N selectivity of 91.2%. Furthermore, the feasibility of practical application was verified using electroplating wastewater, where it was found that the Ru–Cu CF electrode not only effectively converted NO3– to NH4NO3, but also successfully recovered Cu2+ from the wastewater. This discovery has the potential to optimize laborious and environmentally damaging industrial synthetic processes into efficient green alternatives, thereby providing important theoretical guidance and practical value for the development of green and clean ammonia synthesis processes.
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