The Limitations of Looking Only at Foam Height
A published protocol for systematic, rigorous characterization of foamability and foam stability.
Foams are often studied by pouring externally generated foam into a column and visually observing changes in foam height over time. While this allows for a rough directional comparison — foam A appears more stable than foam B — it does not tell you why the foam reaches its maximum height and volume, nor does it give you any insight into foam stability, its mechanisms, or destabilizing pathways.
If the foams you are comparing also differ in initial bubble size or liquid fraction, then even that rough directional comparison may be misleading — the differences you observe during decay may reflect those structural differences rather than any difference in the formulation.
This is a well-known problem in foam science, but a clear, practical framework for addressing it has been difficult to find — until a group at the University of Stuttgart published a paper that lays one out explicitly.
In 2013, Julia Boos, Wiebke Drenckhan, and Cosima Stubenrauch published a study in the Journal of Surfactants and Detergents that proposes a systematic protocol for studying aqueous foams. The paper is built around a deceptively simple question: what are the important parameters you need to control and measure if you want to characterize foams properly? Their answer, worked out through careful experimentation with well-defined nonionic surfactant systems, provides a practical roadmap that any scientist working with foams can apply.
The Protocol
The authors propose a three-step approach.
First, choose foam generation conditions that produce foams with the same — or at least very similar — initial structure. This means measuring the initial liquid fraction and the average bubble size of the freshly generated foam, not just the foam volume. If two foams start with different bubble size distributions or different liquid content, every subsequent measurement is confounded by that difference. The authors demonstrate this by systematically varying gas flow rate and filter porosity, showing how each parameter affects the initial foam structure, and identifying conditions under which meaningful comparisons can be made.
Second, monitor the time evolution of bubble size and bubble size distribution. This is where the real diagnostic power emerges. A foam that is simply draining will show a stable bubble size distribution — the bubbles are not changing, only the liquid between them is moving. A foam that is undergoing coalescence will show an abrupt appearance of larger bubbles as films rupture and adjacent bubbles merge. A foam experiencing Ostwald ripening will show a gradual, uniform shift toward larger bubble sizes. These are different physical processes with different causes, and distinguishing between them requires tracking what the bubbles are actually doing — not just what the foam volume is doing.
Third, monitor the time evolution of foam volume and liquid fraction simultaneously. Foam volume tells you the net result of everything happening inside the foam. Liquid fraction — measured independently through conductivity — tells you how much liquid remains in the film network. Together, they begin to separate drainage from structural collapse. If foam volume is stable but liquid fraction is decreasing, the foam is draining. If both are decreasing together, something more than drainage is at work.
What the Simultaneous Measurements Revealed
The authors applied this protocol to three surfactant systems: two pure nonionic surfactants (β-C12G2 and C12E6) and their 1:1 mixture, all at the same concentration. By carefully controlling foam generation conditions, they produced foams with nearly identical initial bubble sizes and liquid fractions — establishing the baseline needed for a fair comparison.
What happened next was strikingly different for each system, and the differences could only be understood because all three measurement types — foam volume, liquid fraction, and bubble size — were running simultaneously.
One surfactant produced a foam that drained normally without any change in bubble size or foam volume over the entire observation period. The liquid fraction decreased as gravity pulled liquid downward through the film network, but the foam structure itself remained intact. This is a foam where drainage is the only active mechanism — the surfactant layer is rigid enough to prevent film rupture.
The second surfactant told a completely different story. Bubble sizes changed rapidly within the first two minutes, the bubble size distribution broadened dramatically, and the foam volume collapsed. The authors were even able to capture the moment of coalescence directly — two adjacent bubbles visible in one frame merging into a single larger bubble one second later. This is a foam where coalescence, not just drainage, is driving the instability. And crucially, the drainage data alone could not have told you that. Foam volume was decreasing and liquid fraction was decreasing, but without the bubble size data confirming coalescence, the mechanism would have remained ambiguous.
The mixture of the two surfactants revealed something more nuanced still. On short timescales, it behaved like the more stable surfactant — draining at a similar rate with similar initial structure. On intermediate timescales, coalescence appeared, resembling the behavior of the less stable surfactant. The authors were able to assign the two different destabilization mechanisms to the two different surfactant components in the mixture — a conclusion that would have been impossible without tracking all three parameters over time.
Why This Matters to Your Foam Work
The power of this paper is not in the specific surfactant systems the authors chose — it is in the methodology. The protocol they propose applies to any foam study where the goal is to understand why a foam behaves the way it does, not just to observe that it does.
Most traditional foam tests measure one thing: foam height or foam volume as a function of time. The work by Boos clearly demonstrates that this is not enough. Two foams can lose volume at the same rate for entirely different reasons — one through drainage, the other through coalescence — and the formulation response to each is different. A drainage problem is addressed through film viscosity and thickness. A coalescence problem is addressed through interfacial elasticity and surface coverage. If you cannot distinguish between the two, you cannot optimize intelligently.
The simultaneous measurement of foam volume, liquid fraction (via conductivity), and bubble size distribution is what makes this distinction possible. It is the approach the authors used throughout this study, and it is the measurement philosophy that the FOAMSCAN is built around.
The full paper includes detailed experimental methodology, bubble size distribution data at multiple time points, drainage curves with power-law analysis, and a clear summary of the proposed protocol. It is a valuable reference for any scientist designing foam characterization experiments.
This article is part of the TECLIS America technical resource library. For information about the FOAMSCAN foam analyzer and its simultaneous optical and conductivity measurement capabilities, visit the FOAMSCAN product page.