3D Interconnected Porous Carbon Derived from Spontaneous Merging of the Nano-sized ZIF-8 Polyhedrons for High-Mass-Loading Supercapacitor Electrodes

Interconnected porous carbons show great potential for high-rate capacitive energy storage, especially at high electrode mass loadings, due to their continuous conductive network and ion migration channels. Herein, we show...

Electrochemical Recovery to Overcome Direct Osmosis Concentrate-Bearing Lead: Optimization of Treatment Process via RSM-CCD

The use of electrochemistry is a promising approach for the treatment of direct osmosis concentrate that contains a high concentration of organic pollutants and has high osmotic pressure, to achieve the safe discharge of effluent. This work addresses, for the first time, this major environmental challenge using perforated aluminum electrodes mounted in an electrocoagulation–flotation cell (PA-ECF). The design of the experiments, the modeling, and the optimization of the PA-ECF conditions for the treatment of DO concentrate rich in Pb were explored using a central composite design (CCD) under response surface methodology (RSM). Therefore, the CCD-RSM was employed to optimize and study the effect of the independent variables, namely electrolysis time (5.85 min to 116.15 min) and current intensity (0.09 A to 2.91 A) on Pb removal. Optimal values of the process parameters were determined as an electrolysis time of 77.65 min and a current intensity of 0.9 A. In addition to Pb removal (97.8%), energy consumption, electrode mass-consumed material, and operating cost were estimated as 0.0025 kWh/m3, 0.217 kg Al/m3, and 0.423 USD/m3, respectively. In addition, it was found that DO concentrate obtained from metallurgical wastewater can be recovered through PA-ECF (almost 94% Pb removal). This work demonstrated that the PA-ECF technique could became a viable process applicable in the treatment of DO concentrate containing Pb-rich for reuse.

Battery Electrode Mass Loading Prognostics and Analysis for Lithium-Ion Battery–Based Energy Storage Systems

With the rapid development of renewable energy, the lithium-ion battery has become one of the most important sources to store energy for many applications such as electrical vehicles and smart grids. As battery performance would be highly and directly affected by its electrode manufacturing process, it is vital to design an effective solution for achieving accurate battery electrode mass loading prognostics at early manufacturing stages and analyzing the effects of manufacturing parameters of interest. To achieve this, this study proposes a hybrid data analysis solution, which integrates the kernel-based support vector machine (SVM) regression model and the linear model–based local interpretable model-agnostic explanation (LIME), to predict battery electrode mass loading and quantify the effects of four manufacturing parameters from mixing and coating stages of the battery manufacturing chain. Illustrative results demonstrate that the derived hybrid data analysis solution is capable of not only providing satisfactory battery electrode mass loading prognostics with over a 0.98 R-squared value but also effectively quantifying the effects of four key parameters (active material mass content, solid-to-liquid ratio, viscosity, and comma-gap) on determining battery electrode properties. Due to the merits of explainability and data-driven nature, the design data–driven solution could assist engineers to obtain battery electrode information at early production cases and understand strongly coupled parameters for producing batteries, further benefiting the improvement of battery performance for wider energy storage applications.

Investigation on Mass Sensitivity of N-M Type Electrode Quartz Crystal Microbalance

Mass sensitivity plays a crucial role in the practical application of quartz crystal microbalances (QCMs)-based quantitative analysis. n-m type QCMs have many applications, so it is necessary to clarify the relationship between the mass sensitivity and the electrode of the n-m type QCM. The performance of gold-plated films with different electrodes was studied by theoretical calculation and experiment. The results show that the mass sensitivity on the surface of the n electrode and the surface of the m electrode are essentially the same. Meanwhile, the mass sensitivity of n-m type QCMs varies with the diameter of the n and m electrodes. When the diameter of the n electrode is close to half the diameter of the m electrode, mass sensitivity is at maximum value. These results are important for the further designs and applications of n-m type QCMs.

Preparation of a Self-Lubricating Cu/h-BN Coating on Cemented Carbide

In this work, a Cu/h-BN self-lubricating coating was prepared on cemented carbide by electrospark deposition (ESD). The microstructure and properties of the coating were examined. The results showed that no decomposition of or reactions with h-BN occurred. As the h-BN content and capacitance increased, the number of pores and microcracks in the coatings increased. Additionally, as the capacitance increased, the electrode mass loss increased. However, the specimen mass increased first and then decreased. The coating thickness was affected by the capacitance, deposition time, and volume ratio of h-BN to Cu. The results exhibited were consistent over the tests. The self-lubricating coating exhibited excellent tribological behavior under the test conditions, and the worn surface showed features consistent with shear slippage and abrasive wear.