The predictions are all relatively accurate. Most R 2 values are above 0.96, with the exceptions being predictions of specific thermal energy in a TVSA process, specific electricity in an S-TVSA process, and purity for both processes. Working capacity and productivity are predicted very accurately due to being the simplest two performance indicators as they only involve the amount of CO2 recovered, the mass or volume of the adsorbent, and the cycle time in the case of productivity. In contrast, purity seems 10 Email: jpy1@hw.ac.uk RCCS, Heriot-Watt University to be the most challenging performance indicator to predict for the ANNs. The distributions of purity of the processes are relatively narrow. As a result, there are fewer examples of outliers in the dataset of detailed model simulations and potentially more numerical noise from the detailed model. This is likely having an impact on the ANN predictions. Additionally, only a very small number of points exhibit greater than 10% of error when considering that there are ~3000 test samples, as shown in Figure .