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.