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<p>The motion of bubbles in stirred reactors exerts a significant influence on heat and mass transfer, as well as reaction rates within the reactor. This study examines the chaotic mixing characteristics and dynamic behavior of bubbles in a stirred reactor by introducing pulsed air flow. Deep learning is employed to track and analyze bubble motion, thereby revealing the mechanistic insights of bubble dynamics in stirred reactors. Additionally, mechanical stirring chaos characteristics are quantified using 0-1 tests, coupled with a comprehensive evaluation of mixing systems based on mixing times. The results demonstrate that pulsed air flow induces nonlinear bubble motion, generating complex mixing patterns and flow structures within the reactor. Quantitative analysis of bubble trajectories and distributions elucidates the impact mechanisms of pulsed air flow on mixing efficiency. Further research reveals that optimizing parameters of pulsed air flow can enhance bubble motion, improve mixing efficiency, accelerate reaction rates, and enhance reactor performance. Under optimal conditions, mixing times are reduced by 3.26 times compared to conventional mixing systems. This study offers novel insights and methodologies for the design and optimization of mixing reactors.</p> Graphical Abstract <p></p>

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Evaluation of Mixing Efficiency Using Hybrid Impeller Synergistic with Pulsed Air Bubbles in Liquid–Liquid System

  • 期刊论文

  • 发表日期：

    2025年3月13日

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  • Yan Zhang,
  • Xinyu Li,
  • Gai Zhang,
  • Zhiqiang Li,
  • Jianxin Xu,
  • Hua Wang

摘要

The motion of bubbles in stirred reactors exerts a significant influence on heat and mass transfer, as well as reaction rates within the reactor. This study examines the chaotic mixing characteristics and dynamic behavior of bubbles in a stirred reactor by introducing pulsed air flow. Deep learning is employed to track and analyze bubble motion, thereby revealing the mechanistic insights of bubble dynamics in stirred reactors. Additionally, mechanical stirring chaos characteristics are quantified using 0-1 tests, coupled with a comprehensive evaluation of mixing systems based on mixing times. The results demonstrate that pulsed air flow induces nonlinear bubble motion, generating complex mixing patterns and flow structures within the reactor. Quantitative analysis of bubble trajectories and distributions elucidates the impact mechanisms of pulsed air flow on mixing efficiency. Further research reveals that optimizing parameters of pulsed air flow can enhance bubble motion, improve mixing efficiency, accelerate reaction rates, and enhance reactor performance. Under optimal conditions, mixing times are reduced by 3.26 times compared to conventional mixing systems. This study offers novel insights and methodologies for the design and optimization of mixing reactors.

Graphical Abstract