“…There are limitations to the vOCG method when used for the prediction of interfacial energies. Several specific concerns raised are that the base components are systematically greater than the acid components, that experimentally determined surface energy components may depend on the set of fluids chosen for experiments, and that the values of the components may sometimes take negative values. , In response to the first concern, the relative magnitudes of the acid and base terms are set by the choice of the components of water, which are typically equal to each other but may be chosen to make typical acid and base values for other fluids comparable as shown by Della Volpe and Siboni. , The second concern may be addressed by choosing appropriate test fluids when characterizing the surface energy components, or by choosing many fluids. , The final concern is assuaged by noting that negative surface energy component values reported are often of a lesser magnitude than the error of the measurement. , Even with the concerns addressed, there may still be significant error in prediction of interfacial energy over a broad range of fluids as pointed out by Kwok and Lee. − In addition, in the specific case of LIS, a subset of prior work has used ionic liquids as lubricants; unfortunately, not only are there very limited data on the acid–base components of these liquids, − but the vOCG method would have trouble even with suitable data for pure ionic liquids due to the extent to which ionic liquids and water are mutually soluble, with water changing surface tension by nearly 50% in the presence of certain ionic liquids; therefore, ionic liquids are not considered in this analysis. , With these criticisms in mind, there is a wealth of literature on interfacial energy prediction, − including data for the vOCG LW, acid, and base components for over 150 fluids and solids compiled in the Supporting Information along with measurements taken in this study, and the consensus is that the vOCG method is the most versatile choice for a broad range of fluids. ,,,,, Indeed, as demonstrated below, its predictive power is not only suitable for LIS, but it also offers additional insights that previously proposed design guidelines have not been able to properly capture.…”