In order to identify SGs focusing on the large ∆d C-O max , i.e., associated with more outstanding distributions of the target, we analyzed the Pareto front of SGD solutions with respect to the objectives coverage and utility function (magenta points in Fig. ). In multi-objective optimization, a Pareto front is defined as the set of solutions for which no single objective can be improved without deteriorating at least one other objective. Thus, the solutions in the Pareto front reflect an optimal tradeoff between competing objectives. This analysis allows us to take into account multiple tradeoffs between the two conflicting objectives of SGD: coverage and utility. We focus on the SG with the highest utility value in the Pareto front. Denoted as σ selected , this SG coverage is 0.131 and shows a ∆d C-O max mean of 0.132 Å. The target distribution in σ selected is shown in blue in Fig. ). This SG is more focused on the outstanding situation compared to the SG that maximizes the quality function. From the 24 offered candidate descriptive parameters, SGD identifies four parameters as key to describe the capability of the surface sites in SAAs to strongly elongate CO 2 bonds: the electron affinity of the adsorption site (EA site ), the Pauling electronegativity of the adsorption site (PE site ), the generalized coordination number of the adsorption site (gen-CN), and the radius of the SA dorbital (r d-SA ). The rules associated with the SG σ selected are the following: