There are still several aspects for improving the current approach. First, although it it is impressive how well using the overall barrier worked as a cost function, many more informative alternatives are readily at hand that will likely prove advantageous. A trivial extension would be to use the overall barrier, then next largest barrier, and so on, to break ties for nodes that share the same rate limiting step. A more quantitative approach would be to use the results of microkinetic modeling on the partially explored network to determine the most relevant nodes to explore. Second, the current network only considered catalyzed unimolecular reactions. This is a fine assumption for the vast majority of intermediates with negligible concentration, but bimolecular reactions amongst moderate to high concentration intermediates are certainly expected in general. Here too, a more sophisticated cost function or microkinetic modeling will be necessary for determining when an intermediate should be considered as potentially available for bimolecular reactions. Third, although the current study considered the catalytic effects of water, some reactions (e.g., keto-enol tautomerization) prefer double-water catalyzed mechanisms. Thus, a systematic investigation of the catalytic effects of multiple water molecules can provide even more accurate reaction network prediction. Finally, although the reaction network exploration was done automatically, reaction mechanisms summarization and classification remain manual tasks. Automatically interpreting reaction network data and utilizing this information to speed exploration will be essential as the scale of networks being explored increase, as we expect them to.