In kf-CV, the experimental impedance, 𝒁 exp , is initially partitioned into k subsamples or "folds" of equal size. The 𝑝-th partition (𝑝 = 1, 2, …, k) 𝒁 𝑝,test is treated as the test set, while the rest of 𝒁 exp is used to estimate the DRT vector, 𝒙 𝑝 (𝜆), by solving an optimization problem formally equivalent to (2). Then, using 𝒙 𝑝 (𝜆) and 𝒁 𝑝,test , the square residuals between predicted and test impedance are computed (see (S9) in Section S1.2). Finally, the kf-CV score, kf(𝜆), is obtained as the average of these residuals . We emphasize that, as 𝑘 increases, so does the computational time. In this article, we chose 𝑘 = 5 .