Recently, we developed a population balance framework describing the precipitation of calcium-silicate-hydrate, a key nanomaterial in the construction industry and with potential applications in biomedicine, environmental remediation, and catalysis. In this article, we first refine our computational workflow by developing a more efficient and robust method for the solution of the moment-transformed population balance equations. Then, we generalize our framework by coupling to PHREEQC, a widely used opensource speciation solver, to enhance the adaptability of the framework to new systems. Using this improved computational model, we perform global uncertainty/sensitivity analysis (UA/SA) to understand the effect of variations in the model parameters and experimental conditions on the properties of the product. With the specific surface area of particles as an example, we show that UA/SA identifies the factors whose control would allow a fine-tuning of the desired properties. This general approach can be transferred to other nanoparticle synthesis schemes as well. (C) 2020 The Authors. Published by Elsevier Ltd.