The coupled Computational Fluid Dynamics (CFD)-Population Balance Model (PBM) and the Gibbs-energy minimization based thermodynamic model are presented for the continuous supercritical hydrothermal synthesis of nanopartices. The coupled model is tested with published experimental data of ceria nanoparticle synthesis. Three different flow configurations of the T-mixer are evaluated based on the mixing index, an average temperature of the mixture, product particle size distribution (PSD), and time scales for various stages of nanoparticle production. The product PSD is broader, when back-mixing is dominant, whereas it is narrower when mixing is limited over a small volume. Time scale analysis reveals that the overall synthesis process can be either reaction controlled or mixing controlled based on the flow configuration and operating conditions. Further, scaling relationships between an average particle size and the process conditions are derived for three flow configurations, which are useful for design and optimization of the hydrothermal process for nanoparticle production.