Figure shows the MRE of network predicted ammonia molar fraction in equilibrium over a wide range of process conditions. Focusing the attention to the inside of the trained area, the maximum MRE is > 100 % for the SU data set and > 10 % for the LL data set. While this seems like a large error, it should be noted that this occurs only at high temperatures and low pressures. Under these conditions, the ammonia fraction in equilibrium is small, resulting in large MREs even for low absolute deviations. Considering the hydrogen fraction instead, which is large under the aforementioned conditions, the MRE is well below 1 % in the entire training range for both data sets, as shown in the SI. Furthermore, it can clearly be seen that extrapolation capability increases with training range.