A Refined Molecular Dynamics Approach to Predict the Thermophysical Properties of Positively Charged Alumina Nanoparticles Suspended in Water

An enhanced Molecular Dynamics (MD) approach, synergistically combined with a fine-tuned Force Field (FF) model, is introduced to predict the behavior and thermophysical properties of cationic alumina (γ-Al2O3) nanoparticles (NPs) dispersed in water at 4 different volumetric concentrations (1%, 2%, 3%, 4%) and over a temperature range of 5 to 40°C. Prior MD models have been limited to simplified force field models which fail in the representation of the actual chemical bonding, surface chemistry, and interfacial interactions of nanoparticles in aqueous solutions. In this contribution, a hybrid potential field model along with pH-resolved surface structure for alumina nanoparticles has been integrated with the MD model to represent the intermolecular interactions, dynamics and ultimately the thermophysical properties of the nanofluid that is in excellent quantitative agreement with the experimental data. In fact, our enhanced model performs better than the MD models found in the literature. The analysis of the numerically obtained properties emphasizes that at lower φ, the system shows a higher propensity for enhancement, especially at high temperatures. On the other hand, for volume fractions higher than 2%, the system's thermal performance is expected to exhibit a critical condition of aggregation and deteriorates due to higher dynamic viscosity. With all the above findings, we establish that the MD framework presented in this paper represents an improved step towards a precise and computationally balanced modelling that bridges the relation between the molecular signatures of the nanoparticles with pH resolved surface and the macroscopic behavior and thermal features of alumina-water nanofluids at different volumetric concentrations and temperatures.