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22. Cottonseed meal derived porous carbon prepared via the protease pretreatment and reduced activator dosage carbonization for supercapacitor.

Author

Peng, Lina, Wu, Dongling, Wang, Tao, Guo, Jia, and Jia, Dianzeng

Subjects
*COTTONSEED meal, *CARBONIZATION, *ENZYME specificity, *CARBON-based materials, *ENERGY density
Abstract

The high catalytic activity and specificity of enzymes can be used to pretreat biomass. Herein, the resourceful, reproducible, cheap, and crude protein-rich cottonseed meal (CM) is selected as a precursor and the protease in the K2CO3–KHCO3 buffer solution is used as the enzyme degradation substance to pretreat CM. The crude protein content is significantly reduced by the protease degradation, and, meanwhile, it results in a looser and porous structure of CM. What is more, it significantly reduces the amount of activator. In the subsequent carbonization process, the K2CO3–KHCO3 in the buffer solution is also used as an activating agent (the mass ratio of CM to activator is 2:1), and after carbonization, the O, S, and N doped porous carbon is obtained. The optimized PCM-800-4 exhibits high heteroatom contents and a hierarchical porous structure. The specific capacitance of the prepared porous carbon reaches up to 233 F g−1 in 6M KOH even when 10 mg of active material is loaded. In addition, a K2CO3–KHCO3/EG based gel electrolyte is prepared and the fabricated flexible capacitor exhibits an energy density of 15.6 Wh kg−1 and a wide temperature range (−25 to 100 °C). This study presents a simple enzymatic degradation and reduced activator dosage strategy to prepare a cottonseed meal derived carbon material and looks forward to preparing porous carbon using other biomass. [ABSTRACT FROM AUTHOR]

Published
2023
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37. A Computational Fluid Dynamics and Support Vector Regression Combined Method for Predicting the Flow Performance of the Five‐Strand Tundish.

Author

Wu, Di, Liu, Junda, Wu, Dongling, and Zhou, Ping

Subjects
COMPUTATIONAL fluid dynamics, GENETIC algorithms, PREDICTION models, STEEL
Abstract

To optimize the flow field of a multistrand tundish and improve the steel quality, a prediction model integrating the techniques of computational fluid dynamics (CFD) and support vector regression (SVR) is proposed. A total of 125 cases with different structure parameters, i.e., the diameter and inclination angle of the orifices, are designed. The flow field of liquid steel in the tundish is calculated by CFD, and a sample dataset is established. Then, the SVR, combining the genetic algorithm with K‐fold, is employed to train and predict the sample dataset. In the results, it is shown that the SVR model demonstrates good learning performance on the training dataset. The average absolute errors of predictions for dead volume fraction and consistency are 0.50% and 0.71%. In addition, the SVR model takes much less computational cost than the CFD method to predict the flow performance of tundish in a given baffle structure. [ABSTRACT FROM AUTHOR]

Published
2024
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50. Application of Multibody Dynamics and Bonded-Particle GPU Discrete Element Method in Modelling of a Gyratory Crusher.

Author

Xiong, Youwei, Chen, Wei, Ou, Tao, Zhao, Guoyan, and Wu, Dongling

Subjects
DISCRETE element method, ENERGY consumption, MINERAL processing, SIZE reduction of materials, ASSETS (Accounting)
Abstract

The gyratory crusher is one of the most important mineral processing assets in the comminution circuit, and its production performance directly impacts the circuit throughput. Due to its higher energy utilisation rate for rock breakage than semi-autogenous (SAG/AG) milling, it is a common practice in operations to promote and optimise primary crushing before the downstream capacity can be enhanced. This study aims to develop a discrete element modelling (DEM) and multibody dynamics (MBD) cosimulation framework to optimise the performance of the gyratory crusher. An MBD model was initially established to simulate the gyratory crusher's drivetrain system. A GPU-based DEM was also developed with a parallel bond model incorporated to simulate the particle breakage behaviour. Coupling of the MBD and GPU-based DEM resulted in a cosimulation framework based on the Function Mock-up Interface. An industrial-scale gyratory crusher was selected to test the developed numerical framework, and results indicated that the developed method was capable of modelling normal and choked working conditions. The outcome of this study enabled more realistic gyratory crusher improvement and optimisation strategies for enhanced production. [ABSTRACT FROM AUTHOR]

Published
2024
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