Export citation

Export citation

Choose format for download:

Download Citation

    Nanoparticle dynamics and aggregation behavior in nanofluids: A particle-scale simulation study

    Shun-Jie Wu, Rong-Rong Cai*, and Li-Zhi Zhang†

    • Key Laboratory of Enhanced Heat Transfer and Energy Conservation of Education Ministry, School of Chemistry and Chemical Engineering, South China University of Technology, Guangzhou, 510640, PR China

    • *Contact author: cerrcai@scut.edu.cn
    • †Contact author: lzzhang@scut.edu.cn

    Phys. Rev. E 112, 015103 – Published 11 July, 2025

    DOI: https://doi.org/10.1103/5yrx-9nxt

    Abstract

    Particle aggregation plays a crucial role in determining the performance of nanofluids. A particle-scale understanding of nanoparticle dynamics and aggregation behavior is a prerequisite for accurately characterizing their functionality. In this study, the complex factors affecting nanoparticle aggregation are innovatively condensed into two key dimensionless numbers, the Brownian number (Br) and the adhesion number (Ad). The influence mechanisms of Br and Ad on aggregation are investigated through simulations of typical particle dynamics, including collision, adhesion, rebound, and separation, using discrete element method coupled with a lattice Boltzmann model and immersed moving boundary (DEM-LBM-IMB), along with comprehensive force analysis. Simulation results reveal that both Brownian motion and adhesion exert nonmonotonic effects on aggregation. Specifically, Brownian motion promotes aggregation by increasing the frequency of particle collisions. However, excessive Brownian motion beyond the interparticle adhesion threshold reduces the adhesion ratio after collisions and amplifies particle separation, thus inhibiting aggregation. On the other hand, enhanced interparticle adhesion improves particle capture after collisions, but excessive adhesion restricts continuous particle movement and collisions, moderately suppressing aggregation. Based on these findings, an aggregation phase diagram is proposed as a function of Br and Ad and further validated by experiments, providing insights into predicting the aggregation behavior of nanofluids under complex conditions.

    Physics Subject Headings (PhySH)

    Authorization Required

    We need you to provide your credentials before accessing this content.

    References (Subscription Required)

    Outline

    Information

    Sign In to Your Journals Account

    Filter

    Filter

    Article Lookup

    Enter a citation