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Effect of frother on bubble entraining particles in coal flotation

Author

Listed:
  • Shi, Qinghui
  • Zhu, Hongzheng
  • Shen, Tuo
  • Qin, Zhiqian
  • Zhu, Jinbo
  • Gao, Lei
  • Ou, Zhanbei
  • Zhang, Yong
  • Pan, Gaochao

Abstract

Understanding the effect of frother on bubble entraining coal particles is an important guidance for regulating coal flotation behavior. The bubble properties and the flow field surrounding the bubble were investigated using the particle image velocimetry (PIV) technique. The bubble equivalent diameter, bubble deformation rate and low-velocity region area reduced as the frother concentration increased due to a decrease in surface tension. The oscillation of the bubble and low-velocity region were subsequently analyzed. As the frother concentration increased, the oscillation frequency of the bubble and low-velocity region gradually decreased until 1.6 × 10−4 mol/L after that it tended to be stable. The oscillation amplitude of the bubble and low-velocity region slightly varied with the frother concentration but increased as the distance away from the bubble increased. The coal particle trajectories and entrainment phenomenon under the effect of frother were explored via the high-speed motion acquisition equipment. Three typical trajectories that Escape, Offset entrainment, and Entrainment were used to describe the coal particle behavior around the bubble. A predictive model of coal particle entrainment probability influenced by frothers was established. Our findings can provide valuable insight into the development of technology for mineral flotation.

Suggested Citation

  • Shi, Qinghui & Zhu, Hongzheng & Shen, Tuo & Qin, Zhiqian & Zhu, Jinbo & Gao, Lei & Ou, Zhanbei & Zhang, Yong & Pan, Gaochao, 2024. "Effect of frother on bubble entraining particles in coal flotation," Energy, Elsevier, vol. 288(C).
  • Handle: RePEc:eee:energy:v:288:y:2024:i:c:s0360544223031055
    DOI: 10.1016/j.energy.2023.129711
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    References listed on IDEAS

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    1. Yang, Xiaolin & Zhang, Kefei & Ni, Chao & Cao, Hua & Thé, Jesse & Xie, Guangyuan & Tan, Zhongchao & Yu, Hesheng, 2022. "Ash determination of coal flotation concentrate by analyzing froth image using a novel hybrid model based on deep learning algorithms and attention mechanism," Energy, Elsevier, vol. 260(C).
    2. Vershinina, K.Yu. & Shlegel, N.E. & Strizhak, P.A., 2019. "Recovery of waste-derived and low-grade components within fuel slurries," Energy, Elsevier, vol. 183(C), pages 1266-1277.
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