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Quantitative and Qualitative Examination of Particle-particle Interactions Using Colloidal Probe Nanoscopy

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

Shun-Jie Wu¹, Rong-Rong Cai¹, Li-Zhi Zhang¹

¹South China University of Technology, Key Laboratory of Enhanced Heat Transfer and Energy Conservation of Education Ministry, School of Chemistry and Chemical Engineering, Guangzhou, 510640, PR China.

Physical Review. E

|August 19, 2025

Summary

This summary is machine-generated.

Nanofluid particle aggregation is influenced by Brownian motion (Br) and adhesion (Ad). Both factors have non-monotonic effects, with an optimal balance needed for effective aggregation and performance.

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Area of Science:

Nanofluidics
Materials Science
Computational Physics

Background:

Particle aggregation significantly impacts nanofluid performance.
Understanding nanoparticle dynamics at the particle scale is essential for accurate characterization.

Purpose of the Study:

To investigate the influence mechanisms of Brownian number (Br) and adhesion number (Ad) on nanoparticle aggregation.
To condense complex aggregation factors into two key dimensionless numbers.

Main Methods:

Discrete Element Method coupled with Lattice Boltzmann Model and Immersed Moving Boundary (DEM-LBM-IMB) simulations.
Analysis of particle dynamics: collision, adhesion, rebound, and separation.
Comprehensive force analysis.

Main Results:

Both Br and Ad exhibit non-monotonic effects on aggregation.
Brownian motion initially promotes aggregation but inhibits it at excessive levels.
Enhanced adhesion improves particle capture but excessive adhesion suppresses aggregation.

Conclusions:

An aggregation phase diagram based on Br and Ad is proposed.
The diagram provides insights into predicting nanofluid aggregation behavior.
Experimental validation confirms the simulation findings.