The parameters outlined in Table have been made available in PyBaMM and can used as inputs for different physics-based models to predict battery behaviour in various conditions. To validate the determined parameters, we compared experimental data to simulations using the DFN model coupled to a thermal model. These equations are outlined in Tables and. The model was used to predict the voltage and temperature profiles at C-rates of 0.5C, 1C, and 2C, at 0 °C, 10 °C and 25 °C. These 9 datasets are available in a data repository, however for this paper we study five cases: (i) 0.5C|25 °C, (ii) 0.5C|0 °C, (iii) 0.5C|10 °C, (iv) 1C|25 °C, and (v) 2C|25 °C. The initial concentrations for the positive and negative electrodes were set to 13975 mol m -3 and 28866 mol m -3 , respectively, which correspond to stoichiometries of 0.27 and 0.98. Note that the initial concentrations can vary significantly from cell to cell, so their values were determined by manually adjusting the rest voltage at the beginning of the simulation to the experimental data. To achieve good agreement between the simulated and experimental data adjusting of a few other parameters values is needed. This was initially carried out based on the voltage profile of the 1C|25 °C case, for this only one parameter needed manual tuning: the positive electrode diffusivity. This tuning was done manually by trial and error by setting a multiplicative factor to the diffusivity function (illustrated in Fig S8 ) until a good qualitative agreement was observed with the experimental data. We found that a factor of 2.7, the same as used in a previous work, gave good agreement with experimental data, and even though this can seem a significant adjustment, note that it is within the typical variability between different cells (see Fig ). The negative electrode diffusivity, on the other hand, was adjusted but instead of manual tuning we used the factor of 3.03 found earlier, which gives a good agreement with experimental data. This contrasts to the previous electrochemical parameterisation for this cell, requiring the negative electrode diffusion coefficient to be increased 1800% from the experimentally determined value, which demonstrates the improvement in simulated data when parameter value variability is considered and not taken to be a constant. The temperature profiles for the 1C and 2C cases demonstrated good agreement, although as the 0.5C is dominated by reversible heat it is more sensitive to entropic term. Therefore, in the 0.5C|25 °C case the negative electrode entropic term had to be tuned. This adjustment involved excluding the lower entropic term values, see Figure . In summary, the values of three parameters had to be adjusted to achieve good agreement for the temperature and voltage profiles.