The initial case study assumes that the system operates at\(T=T_{\text{ref}}=40\ \), which results in seven parameters requiring estimation (i.e.,\(\ \mathbf{\theta}=\left[k_{1f},\ K_{\text{eq}},\ k_{2},\ k_{3},\ k_{4},k_{5},\ k_{6}\right]^{T}\)). These seven parameters lead to seven columns in the scaled sensitivity matrix \(\mathbf{Z}\). Decision variables for the new experiments are initial concentrations for the reactants \(SM1,\ \ D\), and \(SM2\)(i.e.,\(\mathbf{d}=\left[C_{\text{SM}1_{0}},C_{D_{0}},C_{\text{SM}2_{0}}\right]^{T}\)). Lower and upper bounds for these decision variables are provided in Table 7. Note that, the four approaches (i.e., LO-LO, Bayes-LO, LO-Bayes and Bayes-Bayes) that are compared in this initial case study also considered in an expanded case study (reported in the Supplementary Information) where temperature is an additional decision variable (\(35\leq T\leq\ 45\)). Considering \(T\) as an additional decision variable results in a model with 14 parameters.