Ice slurry has remarkable energy storage density due to significant amount of latent heat during phase change, making it a unique environmentally friendly alternative. This technology can be used for renewable cooling in buildings, foods, and medical products. Nanofluid ice slurry offers higher thermal conductivity and lower supercooling degree as compared to conventional ice slurry which improves its effectiveness in applications. Therefore, an efficient nanofluid ice slurry generator needs to be developed. In this study, a novel continuous nanofluid ice slurry generator is developed using an opposed nozzle impinging jet where Alumina (Al2O3) nanofluid (ANF) impinged with cold air jet. To achieve an optimal thermal performance and maximize slurry production, a model of the slurry generator should be developed. To accomplish this, a novel mathematical framework incorporating multiscale nanofluid freezing, i.e. liquid supercooling, nucleation, recalescence, equilibrium freezing, and solid subcooling, along with a spray-droplet dynamics model is developed and validated against experimental data. The results suggest that the performance of the impinging jet nanofluid ice slurry generator is superior to that of the non-impinging counterpart (up to 3.4 times more ice produced). The addition of Alumina nanoparticle expedites freezing time by about 20%. The ice packing fraction was found to increase with nanofluid concentration and peak at concentration of 0.2 weight percentage. The ice packing fraction decreases with the increase of the initial temperatures of nanofluid and air. Conducting a parametric study, it is shown that the ice slurry production can be maximized via an appropriate selection of the generator size, spray pressure and configuration, and nanoparticle concentration.