On average, we observed that the FIA-2 and FCA-0.5 functions explore the smallest fraction of the parameter space before identifying a satisfactory material, at 3.9 ± 0.3% and 4.1 ± 0.9%, respectively. The FCA-0.5 also measures the smallest percentage of infeasible measurements during its campaigns, at 74.8 ± 4.0%. While measuring 3/4 infeasible measurements is indeed a high constraint violation rate, we expect random sampling to measure unstable HOIPs at a rate of roughly 92%. Also noteworthy is that the naïve-ignore strategy, which turns off the feasibility classifier contribution in Eq. 6, measures unstable HOIPs at a rate of almost 87%. Therefore, by using our GP feasibility classifier and an appropriate feasibility-aware acquisition function (such as FCA-0.5 ) we are able to reduce the rate at which the constraint function is violated by about 14% compared to baseline.