We start by screening all 35,588 singly and doubly substituted DHAs because they are most synthetically accessible and can be screened without machine learning models using semiempirical electronic structure methods (SQM). Figure (a) shows a plot of the SQM barriers plotted vs the storage densities for 32,623 singly and doubly substituted DHA/VHF couples. We want to select roughly 100 of the most promising molecules for further study with M06-2X/6-31G(d). As discussed in Supplementary Information, PM3 tends to overestimate the barrier relative to the parent molecule (the horizontal red line) so the barrier should be significantly higher than that. Similarly, GFN2-xTB tends to underestimate the reaction energy relative to the parent system (the vertical red line) and, hence, the energy storage density, so molecules with only somewhat higher storage density are potentially promising candidates. After some experimentation we found that cutoffs of 178 kJ/mol (15 kJ/mol higher than the parent compound) and 0.33 kJ/g leads to 109 molecules for further study using DFT (green box in Figure ). For all 109 molecules we optimize the lowest energy GFN2-xTB DHA, VHF, and PM3 TS structures with M06-2X/6-31G(d) and the results are shown in Figure . As expected, the majority of the molecules have higher energy storage densities than the parent compound, but some have lower barriers with DFT. This indicates that by using PM3 energies, we are more likely to get false-positives than false-negatives. More false-positives will increase the number of redundant calculations; however, this is preferred over missing potentially excellent candidates.