where YSImix is a 16 × 1 column vector that contains the measured YSI for each mixture, x is a 16 × 6 matrix that contains the actual mole fraction of each component in each mixture, and YSIcomp is a 6 × 1 column vector that contains the YSI of each component. Again, we regard YSImix as a known from the measurements (see SI N), x as a known from the mixture preparation (see SI B), and YSIcomp as an unknown. The YSIopt obtained by solving Eq. ( ) with linear regression are listed in to the predicted YSImix using the linear blending rule, Eq. ( ), and the YSIopt (horizontal axis). The agreement is very good, which shows that the functional form of the linear blending rule can fit the measured data.