Implementing multi-fidelity optimization with the mixture training provides us with an opportunity to test whether we can better constrain the training data without implementing regularization, since our set of mixture data is much larger, containing 195 physical property measurements. We ran an optimization with N=20 initial points, as well as one with 𝑁 = 10 initial points, to determine what level of initial information was required to produce a successful optimization.