TAGRA 2025

The thermal conductivity of nanofluids, suspensions of nanoparticles in base fluids, can be significantly influenced by the fractal nature of nanoparticle aggregates. Fractal structures, characterized by self-similarity across multiple scales, determine how nanoparticles cluster and form conductive pathways within the fluid. This study investigates the effect of fractal phenomena on the thermal conductivity of nanofluids by integrating theoretical models, computational simulations, and experimental observations. The fractal dimension of aggregates, a measure of their structural complexity, is found to play a critical role: low-fractal-dimension aggregates, which are open and chain-like, promote continuous heat transfer pathways and enhance effective thermal conductivity, while high-fractal-dimension aggregates, which are more compact, disrupt connectivity and reduce thermal transport efficiency. Factors such as nanoparticle concentration, temperature, and interparticle forces significantly influence aggregation behavior and fractal dimension, thereby modulating thermal performance. Experimental studies on copper oxide and silicon dioxide nanofluids confirm that fractal clustering creates low-resistance conductive networks, validating the predictive capabilities of fractal-informed models. Understanding the fractal characteristics of nanoparticles enables the optimization of nanofluid formulations for enhanced heat transfer, improved cooling efficiency, and greater operational stability. Overall, the integration of fractal theory with nanofluid research offers a robust framework for predicting and tailoring thermal properties, opening pathways for the design of high-performance thermal fluids and advanced energy management systems. This approach provides fundamental insights into the interplay between microstructure and heat transport in nanofluids, highlighting the critical role of fractal aggregation in thermal enhancement.