Removal of microplastics and nanoplastics from urban waters: Separation and degradation.

High-efficiency decontamination of Pb(II) and tetracycline in contaminated water using ball-milled magnetic bone derived biochar

The sustainable production of green hydrogen via water electrolysis necessitates cost-effective electrocatalysts. By following the circular economy principle, the utilization of waste-derived catalysts significantly promotes the sustainable development of green hydrogen energy. Currently, diverse waste-derived catalysts have exhibited excellent catalytic performance toward hydrogen evolution reaction (HER), oxygen evolution reaction (OER), and overall water electrolysis (OWE). Herein, we systematically examine recent achievements in waste-derived electrocatalysts for water electrolysis. The general principles of water electrolysis and design principles of efficient electrocatalysts are discussed, followed by the illustration of current strategies for transforming wastes into electrocatalysts. Then, applications of waste-derived catalysts (i.e., carbon-based catalysts, transitional metal-based catalysts, and carbon-based heterostructure catalysts) in HER, OER, and OWE are reviewed successively. An emphasis is put on correlating the catalysts' structure-performance relationship. Also, challenges and research directions in this booming field are finally highlighted. This review would provide useful insights into the design, synthesis, and applications of waste-derived electrocatalysts, and thus accelerate the development of the circular economy-driven green hydrogen energy scheme. 

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Waste-Derived Catalysts for Water Electrolysis: Circular Economy-Driven Sustainable Green Hydrogen Energy

Iron-rich digestate biochar toward sustainable peroxymonosulfate activation for efficient anaerobic digestate dewaterability.

The invention discloses a UAV navigation system and method used for positioning of a pipeline robot, and belongs to the field of UAV automatic navigation. The system is composed of a UAV system, a pipeline robot device and a ground control platform. During work, the ground control platform determines the working modes of a UAV according to different pipeline laying conditions, and sends a tracking instruction at the same time; and after receiving the instruction, the UAV carries out navigational flight according to a set navigation mode. The speed of navigational flight is set according to requirements by a worker at first, when the pipeline robot is found by monitoring, the UAV navigation system adjusts the navigational flight speed of the UAV automatically according to the state of the robot, and coordinate information of the pipeline robot is sent to the ground control platform. The system and method can be used to realize navigational flight of the UAV for positioning of the pipeline robot, it is ensured that the pipeline robot is positioned and tracked rapidly in real time, the adaptability is high, and the automatic level is higher.

UAV (Unmanned Aerial Vehicle) navigation system and method used for positioning of pipeline robot

Water pollution is a major concern for public health and a sustainable future. It is urgent to purify wastewater with effective methods to ensure a clean water supply. Most wastewater remediation techniques rely heavily on functional materials, and cost-effective materials are thus highly favorable. Of great environmental and economic significance, developing waste-derived materials for wastewater remediation has undergone explosive growth recently. Herein, the applications of waste (e.g., biowastes, electronic wastes, and industrial wastes)-derived materials for wastewater purification are comprehensively reviewed. Sophisticated strategies for turning wastes into functional materials are firstly summarized, including pyrolysis and combustion, hydrothermal synthesis, sol–gel method, co-precipitation, and ball milling. Moreover, critical experimental parameters within different design strategies are discussed. Afterward, recent applications of waste-derived functional materials in adsorption, photocatalytic degradation, electrochemical treatment, and advanced oxidation processes (AOPs) are analyzed. We mainly focus on the development of efficient functional materials via regulating the internal and external characteristics of waste-derived materials, and the material’s property-performance correlation is also emphasized. Finally, the key future perspectives in the field of waste-derived materials-driven water remediation are highlighted. 

Recent advances in waste-derived functional materials for wastewater remediation

The invention discloses a submarine oil pipeline leakage system and method based on an unmanned underwater vehicle. The system comprises a detection subsystem based on the unmanned underwater vehicle and a detection subsystem based on an underwater robot. The detection subsystem based on the unmanned underwater vehicle comprises the unmanned underwater vehicle and a pipeline position detection module and an oil overflowing detection module which are arranged on the unmanned underwater vehicle and is used for implementing large-area fast inspection. The detection subsystem based on an underwater robot comprises the underwater robot, an umbilical cable winding and unwinding module, a precision pipeline position detection module and a precision oil overflowing detection module and is used for implementing pipeline position detection, highly precision positioning and precision detection of micro leakage, and the precision pipeline position detection module and the precision oil overflowing detection module are arranged on the underwater robot. The system is high in detection speed and low in cost, and the requirements on offshore oil production safety can be met.

Submarine oil pipeline leakage system and method based on unmanned underwater vehicle

ABSTRACT The computational fluid dynamics (CFD) simulation method is commonly used for large-scale computational engineering problems. However, it usually leads to higher computational costs. The deep learning method has gained significant attention in recent years. However, the traditional methods fail to achieve high-precision pixel-level predictions. They are difficult to predict more detailed, multi-scale features of complex engineering. This study proposes a novel deep U-shaped network-long short term memory (U-Net-LSTM) framework for the rapid time-sequenced hydrodynamic prediction of the SUBOFF. First, a novel framework composed of a deep U-shaped network, two LSTM layers, and a skip connection part is proposed for time-sequenced hydrodynamics prediction. Second, the CFD simulation results of the SUBOFF AFF-8 are validated by referring to published experimental data. Finally, three types of AFF-8 motions are investigated to demonstrate the advantages of the proposed framework in detail. The results demonstrate that the predicted outputs agree well with the CFD simulation results, show good stability and ability to predict additional future results. Compared with the traditional hybrid convolutional neural network-LSTM (CNN-LSTM) framework, the mean square error and mean absolute error are reduced by almost one order of magnitude and two orders of magnitude, respectively, showing that the proposed framework is highly competitive. The GPU cost utilized for running the deep U-Net-LSTM is only 0.33 s for each result, making it possible to achieve real-time prediction. In addition, the computation costs are reduced by six orders of magnitude compared with those in the CFD method.

https://www.tandfonline.com/doi/pdf/10.1080/19942060.2022.2030802?needAccess=true

A novel deep U-Net-LSTM framework for time-sequenced hydrodynamics prediction of the SUBOFF AFF-8

The utility model discloses a leakage detecting device for a submarine oil pipeline based on an unmanned underwater vehicle. The leakage detecting device comprises an unmanned autonomous vehicle and an underwater robot, wherein a magnetic anomaly detector for detecting the position of the pipeline and a fluorometer sensor group for detecting oil overflow are carried by the unmanned autonomous vehicle which is used for quick inspection in wide range; a pipeline position accurate detection mechanism and fluorometer sensors are carried by the underwater robot which is used for realizing the pipeline position detection, high-precision positioning and accurate detection of small leakage. The leakage detection device is high in detection speed and lower in cost; the requirement on safe production of offshore oil can be met.

Wei Wei

Papers

Recent advances in waste-derived functional materials for wastewater remediation

Submarine oil pipeline leakage system and method based on unmanned underwater vehicle

Removal of microplastics and nanoplastics from urban waters: Separation and degradation.

A novel deep U-Net-LSTM framework for time-sequenced hydrodynamics prediction of the SUBOFF AFF-8

Leakage detecting device for submarine oil pipeline based on unmanned underwater vehicle