Inverse heat transfer problem for the characterization of nanofluids produced with different types of palladium nanoparticles

The objective of this work is the measurement of physical properties of distilled water nanofluids containing palladium nanocubes, palladium cerium oxide nanoparticles, and their respective hydrides. Due to their biocompatibility and favorable photothermal effects, palladium nanoparticles can be used to promote localized absorption of external energy sources in the thermal treatment of cancer, aiming at a thermal damage constrained to the tumor region without significant effects to the healthy tissues. An inverse problem is solved here within the Bayesian framework of statistics with the Markov Chain Monte Carlo method, by using nonintrusive transient measurements taken with an infrared camera during the heating of different water-based nanofluids. The mathematical model used in this work takes into account natural convection effects, due to the nonuniform heat source caused by the diode-laser that heats the nanofluids. Prior distributions for the model parameters were selected based on additional independent measurements, theoretical models and by the careful implementation of the experiments. The proposed model and the estimated parameters were validated, with an excellent agreement between the measured temperatures and those obtained from stochastic simulations during the solution of the inverse problem.