From the 1078 molecules predicted to have the desired properties, a subset of 208 molecules was chosen for subsequent analysis with DFT to verify the accuracy of the ML models. Most top-performing candidates had close to the maximum molecule size. As smaller molecules satisfying the constraints were desired, the top 100 molecules were selected from each size. The subset consisted of 100 radicals containing twelve heavy atoms, 100 containing eleven heavy atoms, six radicals with ten heavy atoms, and two radicals with nine heavy atoms. In Fig. , we plot the ML-predicted redox voltages for the chosen subset, which all lie within the target triangle to permit a single radical to function as both the electron donor and acceptor in an aqueous redox flow battery with a total voltage of at least 1V. For radicals for which the DFT calculations converged, 83.3% fell within the desired target region (Fig. ). The stability scores of the radicals predicted via machine learning were then checked against those obtained via DFT. Fig. shows the distribution of stability scores for both approaches and that stability scores obtained via DFT tended to be lower than those predicted with the surrogate objective function. Using a cutoff score of 85, well within the stability scores observed for experimentally known stable species, 63.3% of radicals were still classified as stable. As shown in Fig. , while buried volume predictions for optimized radicals were highly consistent with those obtained from DFT, accurate prediction of spin density was more difficult for these highly delocalized radicals. Additional training data in this region of molecular space may improve accuracy in subsequent experiments, as the generated radicals tended to be much more stable than those found in the training data (Fig. ). Evaluation of the synthesizability of generated molecules The synthesizability of molecules proposed by generative algorithms has been identified as an area of concern, as theoretically optimized molecules that cannot be experimentally tested are of limited practical value. To address this concern, the ASKCOS retrosynthesis prediction web service was applied post hoc to evaluate the 1,078 top-ranked candidates in addition to on-the-fly constraints imposed during optimization to prioritize the search of synthetically tractable space (see Methods). Of these, 87 returned putative synthetic routes with a median of 5 synthetic routes per candidate and an average depth of 7.9 steps. We performed DFT confirmation for all high-scoring molecules found to be synthetically accessible. A total of 32 molecules were confirmed to satisfy the redox requirements while having high stability (>90). Chemical structures for a representative subset of these molecules are depicted in Fig. . The RL-optimized molecules show structural variability through the varied inclusion of N, S, and O heteroatoms and extended delocalized structures, frequently with unsaturated carbo-and heterocyclic (e.g., cyclopentadienyl, pyrrole, furan, thiophene) cores. As required by the objective function, all radicals demonstrate high spin delocalization and high steric protection of the site of highest spin density. In Fig. , we visually compare spin delocalization and buried volumes for both experimentally known and RLoptimized radicals. As expected, a high predicted stability is achieved by delocalizing the radical electron density across multiple atoms and centering the location of highest spin density on an atom with a high buried volume. We note that in Fig. , the surrogate model correctly predicts that the spin is predominantly focused at the location of highest buried volume, matching DFT results, even though the radical center is formally specified at a different atom in the SMILES string. We next investigated predicted retrosynthetic pathways by which the wide variety of top-performing radicals might be experimentally prepared. In Fig. , we show a putative pathway from ASKCOS for the hydrogenated form of a thiophene-based radical. Thiophenes are well-known fragments in organic electronics, where their semi-conducting properties are exploited for high efficiency. The retrosynthetic route consists of a minimum of two well-established transformations involving a Friedel-Crafts alkylation and an acidic methyl ether cleavage, starting from commercially available 2-methoxythiophene and tert-Butyl chloride.