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

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.