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Adsorption of hydrated Fe(OH)2+ on the kaolinite surface : A density functional theory study

Wu Hongqiang, Miao Yuqi, Long Qibang, Yan Huashan, Li Yong, Qiu Sen, Wu Hao, Zhao Guanfei, Qiu Tingsheng

Physicochemical Problems of Mineral Processing

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2023

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Vol. 59, iss. 6

art. no. 174415

EN

The present study employed density functional theory (DFT) to analyze the adsorption configuration and mechanism of Fe(OH)2+ on the kaolinite (001) surface. The findings demonstrated that Fe(OH)2(H2O)4+ is the main type in which hydrated Fe(OH)2+ can be found in aqueous solution. On the surface of kaolinite, Fe(OH)2(H2O)4+ will be adsorbed. There are two forms of adsorption: outer-sphere and inner-sphere coordination (monodentate/bidentate) adsorption. Fe(OH)2(H2O)4+ has a moderate propensity to adsorb on the alumina octahedral sheet of kaolinite when the outer-sphere coordination adsorption takes place. In cases of inner-sphere coordination adsorption, Fe exhibits a tendency to form monodentate adsorption compounds in conjunction with Ou atoms. Additionally, it prefers to create bidentate adsorption compounds through coordination with both Ot and Ou atoms. The adsorption mechanism analysis results show that the ionic property of Fe atom decreases after outer-sphere coordination adsorption. After inner-sphere coordination adsorption, some electrons of Fe atom are transferred to the surface O atom. The presence of electrons between the Fe and O atoms enhances the formation of bonds, hence enhancing the covalent nature of the Fe-O bond. Theoretical FT-IR (Fourier transform infrared spectroscopy) calculations show that the formation of Fe-O chemical bonds. Because of the lower adsorption energy and more chemical bonds, hydrate Fe(OH)2+ is more likely to be bidentate adsorbed on the kaolinite surface.

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Parameter identification approach using improved teaching and learning based optimization for hub motor considering temperature rise

Li Yong, Wang Yuan, Zhang Taohua, Hu Han, Wu Hao

Metrology and Measurement Systems

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2023

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Vol. 30, nr 1

99--115

EN

Temperature rise of the hub motor in distributed drive electric vehicles (DDEVs) under long-time and overload operating conditions brings parameter drift and degrades the performance of the motor. A novel online parameter identification method based on improved teaching-learning-based optimization (ITLBO) is proposed to estimate the stator resistance, 𝑑-axis inductance, 𝑞-axis inductance, and flux linkage of the hub motor with respect to temperature rise. The effect of temperature rise on the stator resistance, 𝑑-axis inductance, 𝑞-axis inductance, and magnetic flux linkage is analysed. The hub motor parameters are identified offline. The proposed ITLBO algorithm is introduced to estimate the parameters online. The Gaussian perturbation function is employed to optimize the TLBO algorithm and improve the identification speed and accuracy. The mechanisms of group learning and low-ranking elimination are established. After that, the proposed ITLBO algorithm for parameter identification is employed to identify the hub motor parameters online on the test bench. Compared with other parameter identification algorithms, both simulation and experimental results show the proposed ITLBO algorithm has rapid convergence and a higher convergence precision, by which the robustness of the algorithm is effectively verified.

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Grey wolf optimization-based variational mode decomposition for magnetotelluric data combined with detrended fluctuation analysis

Zhang Xian, Li Diquan, Li Jin, Li Yong

Acta Geophysica

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2022

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Vol. 70, no 1

111--120

EN

We present a magnetotelluric data denoising method that uses grey wolf optimization to optimize variational mode decomposition and combines it with detrended fluctuation analysis. First, envelope entropy is selected as the fitness function for grey wolf optimization and is used to determine the number of modes K and the penalty factor, which are the key parameters of the variational mode decomposition method. Then, the optimized variational mode decomposition method is used to decompose magnetotelluric data. Finally, the scaling exponent in detrended fluctuation analysis is used to determine the corresponding intrinsic mode function components to superimpose and reconstruct the useful magnetotelluric data. Extensive experiments and thorough analyses are performed on the synthetic data and field data. The results of the proposed method are compared with the results of the remote reference, variational mode decomposition, variational mode decomposition and matching pursuit, variational mode decomposition and detrended fluctuation analysis methods; the proposed method can improve the denoising performance and reliability of low-frequency magnetotelluric data. The reconstructed data are closer to the natural magnetotelluric data. The satisfactory performance in the results verifies the effectiveness of the design and optimization method.

4

Theoretical and experimental analysis on the interaction properties between tracks and sediments considering sand content for unmanned underwater tracked bulldozer

Li Yong, He Dingchang, Si Qiaorui

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2021

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Vol. 69, nr 1

art. no. e136036

EN

The unmanned underwater tracked bulldozer (UUTB) is an indispensable equipment for dredging and cleaning obstacles on the river bed in the flood season. The investigation on the interaction properties between the UUTB tracks and sediments provides foundation for the evaluation of operation performance when it works on the inland river bed. Based on the current worldwide research, the sediments mixed by sand, bentonite and water with sand content 0%, 10% and 20% were configured in this study to replace the real sediments on the inland river bed in China. The current pressure-sinkage model and shear stress-shear displacement model were discussed. Three different tracks were tested for the pressure-sinkage and the shear stress-shear displacement on the platform. The relationship between pressure and sinkage under sand content 0%, 10% and 20% are revealed based on the experimental results. The modulus of cohesive deformation and friction deformation of the sediments under said sand content are presented. The curves of shear stress and shear displacement are also obtained, which demonstrates the properties between the tracks and configured sediments under sand content 0%, 10% and 20%. The relationship between the tractive force and slip ratio with three different tracks under said sand content is also presented based on the quantitative analysis, which provides reference for the dynamics control and performance evaluation of UUTB on the inland river bed.