Effects of pH and Nanoparticle Concentration on Al2O3–H2O Nanofluid Stability

Abstract

Nanofluid stability is crucial for their long-term effectiveness in heat transfer applications. The current study evaluates parametrically the impact of several preparation methods, pH levels, and volumetric concentrations on the stability of Al₂O₃–H₂O nanofluids as opposed to the most common approach of additive surfactants. Characterization techniques, including scanning electron microscopy (SEM), optical sedimentation imaging, transmission electron microscopy (TEM), zeta potential measurements, and dynamic light scattering (DLS), were employed to quantify the short- and long-term stability of the resulting nanofluids based on nanoparticle morphology, agglomeration state, and electrostatic stabilization potential without the use of surfactants. This unique parametric study applies a wide array of characterization techniques on the same created samples for the first time to provide new insights of the colloid stability processes at play. In addition, the study uniquely assesses long-term (up to two months) surfactant-free electrostatic stabilization, offering a sustainable approach to nanofluid stability. The findings contribute to the development of universal nanofluid preparation guidelines, supporting their commercial scalability across diverse applications. The new insights indicated that an optimal pH level, around 4, significantly enhances the stability of Al₂O₃-H₂O nanofluids by maximizing the electrostatic repulsion between the suspended nanoparticles. Additionally, lower nanoparticle concentrations were found to improve stability, likely due to reduced particle interactions and aggregation. The study also highlights the importance of preparation methods in achieving stable nanofluids, as different methods can influence the dispersion and stability of the suspended nanoparticles. These results underscore the critical role of pH control, nanoparticle concentration, and preparation methods in achieving stable nanofluids. This study also provides a framework for long-term, surfactant-free nanofluid characterization using multiple techniques applied to the same samples, supporting reproducibility and future thermophysical analysis.