A plot showing surface tension as function of pH showed quite similar relative changes in pH 5-9. Johlin measured using sessile bubble method with different timing (hours) to expect equilibrium.

However, the pattern isn’t the same as Sugden’ result that was imposed over the same plot.

abstract here

A regularity has been found: a larger hydrophilic head gives rise to a lower interfacial tension. A relationship was found between the size of the hydrophilic head of lipid and the isoelectric point pH value. With larger hydrophilic heads, the isoelectric point appears at lower pH.

abstract:
Vol7_suppl_05_39.pdf

obtained by the sessile bubble method of measuring surface tensions

J. Biol. Chem.-1930-Johlin-319-25.pdf

Many experimental studies have been undertaken to measure interfacial tensions (IFT’s) as a function of pH, salinity, temperature, and divalent ion concentrations.
The molecular approach involves a statistical mechanical calculation of the intermolecular forces operating at the interfaces between two phases.

abstract here

This citing is probably too old (1983)

A theoretical equation is derived to describe the dependence of the interfacial tension of a lipid bilayer on the pH of the aqueous solution. Interfacial tension measurements of an egg phosphatidylcholine bilayer were carried out. The experimental results agreed with those derived from the theoretical equation obtained close to the isoelectric point within a range of three pH units. A maximum corresponding to the isoelectric point appears both in the theoretical equation and in the experiment.

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The interfacial tension (IFT) of hydrocarbon fluids is commonly predicted by either the parachor method or the scaling law. The methods require equilibrium liquid and vapor phase composition and density. An equation of state would normally be required if experimental values are not available. However, the computation of density for simple hydrocarbons and reservoir fluids, despite the important advances achieved by cubic equations of state, still remains a weak link in these types of calculations. Thus, there exists a need to investigate the qualitative and quantitative effects, of such inaccuracies in the density, on IFT predictions. Moreover, the study presented in this work would be useful in reservoir engineering and enhanced oil recovery calculations. The results presented in this work indicate that the methods are highly sensitive to the inaccuracies in the density of both the liquid and the vapor phases. An error of around 10% in the liquid or the vapor density can result in an error of up to 200% in the estimated IFT. Two binary and one ternary mixture for which measured data on IFT, composition and density is reported in the literature form the basis of this study.

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Using (1) solubility, (2) molecular weight, and (3) density, a three-layer feed-forward neural network was constructed and tested to predict the IFT at the crystal/solution interface. The concentration of solute in liquid phase, (1) concentration of solute in solid phase, (4) temperature, (3) density and (2) molecular weight of crystal were used as inputs to predict the interfacial tension at the crystal/liquid interface (σ_SL). The network was trained using the solubility information for 28 systems to predict the σ_SL value and was validated with 29 new systems. Despite the limited number of data used for training, the neural network was capable of predicting σ_SL successfully for the new inputs, which are kept unaware during the training process. The σ_SL value that is predicted by the artificial neural network during the training and testing process was compared with σ_SL predicted from the widely used empirical expression. For most of the systems, ANN better predicts IFT.

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This article summarized measurement method for IFT instrumentation equipment.

classification of IFT measurement method

m2.pdf

centrifugal-IFT equilibrium

Interfacial tension of any liquid that gives a shape very close to a cylinder at the equilibrium point, can be estimated using Vonnegut’s expression:

ω : angular velocity; (radians per second, degrees per second, revolutions per second)

Δρ : difference between two fluid: the less-dense and the dense