After a comprehensive validation of the model, we further use it to explore the formulation space at low temperatures. Given the limited accuracy of classical MD, it is still difficult to achieve a quantitative prediction of all physical properties. Furthermore, while electrical conductivity is one of the most relevant key properties in electrolyte screening, high conductivity at room temperature alone does not necessarily make it a good electrolyte. As mentioned in the Introduction, a more important issue is that aqueous electrolytes are at risk of freezing, which is the main factor preventing their industrial application in low temperature environments. However, freezing behavior is difficult to approach directly using either experimental or simulation methods. Therefore, in this part, our aim is to assess whether the optimized model could accurately distinguish good and bad performers at low temperatures, especially if it can help us identifying freezing failures before experimental trials.