We can use the PCA, along with the projected features, to get information about which features are important for grouping the elements according to product selectivity. We observe from Fig. Fig. shows a 3D plot of *H vs. *CO vs. LC (Fig. ), along with corresponding 2D subplots for *H vs. CO (Fig. ), *H vs. LC (Fig. ), and LC vs. *CO (Fig. ). Note that this plot contains additional metal catalysts compared to Fig. , as not all elements investigated had data for all the required 22 features to be part of the PCA. Despite being based on 19 fewer features than the PCA and only requiring simple adsorbate calculations, the 3D plot (Fig. ), as well as the 2D plots of *H vs. LC and *CO vs. LC (Fig. ) group the elements just as well if not better than the PCA. To our knowledge, Fig. is the best descriptor plot for CO 2 RR product selectivities, and the first one to fully separate the different elements according to their main product. We already know that ∆E *H decides whether a metal has hydrogen underpotential deposition (H UPD ), while ∆E *CO seems to decide whether a metal does mainly HER or CO 2 RR. The question is what new insight the lattice constant as a descriptor gives us, seeing as how it clearly separates CO-and HCOOH-producing metals.