## DLVO

### Quick Start

We have some sort of particle or emulsion or colloid that we hope will remain stable in its liquid environment. All particles have a self-attraction we can do almost nothing about. So to keep the system stable we have to find some repellent forces, which in practice mean charges, in aqueous systems, or steric forces. DLVO theory lets us calculate this balance. Unfortunately it features lots of parameters and relatively complex equations. Fortunately, with the app the equations are handled for you, and, to get a good feel for the key ideas, you need to play only with:

- The radius, r, of your particle
- φ, the Zeta potential (the charge on the particle) and the molar concentration of ions in the solution
- the length, δ, of your stabilizer and the Flory-Huggins χ parameter of the stabilizer in the solvent.

Play with those key values, looking at V_{t} which is the total (hopefully) repulsive (positive) energy keeping your system stable.

### DLVO

_{1}

_{2}

_{12}*10

^{-20}

DLVO (Derjaguin and Landau, Verwey and Overbeek) theory is obligatory for everyone wanting some insights into stability of nanoparticles, emulsions and colloids. The fact that it often requires input values (and there are lots of them!) that are unknown to the users, and the fact that other factors can completely overwhelm DLVO effects is an unfortunate truth. But all the same, any formulation team should share the common language of DLVO and should make at least some attempt to place their formulations within the context. The model here takes the minimum number of relevant inputs and plots the three key effects plus the resulting balance. Any standard text on DLVO (even Wikipedia) will provide much more detail. The model used here is based on one created by Dr Robert Lee of Particle Sciences and his assistance is warmly acknowledged. A companion model explores the meaning of Zeta potential

This is all very fine for theoreticians, but how does one get hold of all those input values when you just know that you have some particles you want to disperse? The first advice is "Don't Panic". Now think things through one at a time.

- You know the radius of your particle, you know T, you know the Density of your liquid (1 is good enough for most purposes) and its Molar Volume is simply MWt/Density (so MWt is close enough).
- You can look up Dielectric Constants (and Molar Volumes) here .
- The A
_{12}Hamaker constants don't vary all that much, so 1 is good enough, but you can look up some values here . - We're almost there. Your particle is either neutral (Zeta=0) or strongly charged (Zeta=+50 or -50) or has a modest charge somewhere in between.
- Your dispersant is either a small molecule (δ=0.5nm), an oligomer (δ=1nm) or a polymer (δ=10nm). It is either absorbed to a small (Γ=0.5) or large amount (Γ=2).
- And finally your dispersant is either highly compatible with the solvent (Χ=<0.1) or highly incompatible with the solvent (Χ>0.5).

Once you get used to making rough estimates of the parameters using such thinking, you can quickly work out for your specific system which (if any) parameters need to be defined more carefully. You might also work out that other effects (solubility via HSP thinking, bridging or depletion flocculation, Smoluchowski exceptions) are more important, making DLVO largely irrelevant.

A specific application of DLVO is discussed in the Polymers section of Practical Surfactants. To stabilise an emulsion a polymeric surfactant can be very effective provided:

- It can reach the surface fast enough during creation of the emulsion
- The polymer is a di-block with strong attachment of the hydrophobic part to the oil
- The other part of the di-block is highly water soluble so Χ is low
- The length of the water soluble chain is high - so δ=5-10nm
- The coverage (Γ) is high

### The Stability Ratio, W

Particles, in the absence of a barrier, will come into contact with each other at a rate that depends on the diffusion coefficients of the particles. Given a barrier they will come together more slowly. The ratio of the barrier-free and barrier values is W, the Stability Ratio. A high value of W (typically 5000 or more) indicates that the barrier is adequate for stability over "normal" timescales.

There are many contested ways to calculate W, involving ever more esoteric numerical tricks such as Bessel functions and exponential integrals. A paper, Hiroyuki Ohshima, *Approximate analytic expression for the stability ratio of colloidal dispersions*, Colloid Polym Sci (2014) 292:2269–2274, has a super-accurate calculation that has defeated me. However, the paper includes a simpler approximation (though not as simple as the Fuchs approximation that neglects van der Waals attractions!) that differs only in regions of zero practical interest. So that's what I've implemented.

The method *only* takes into account the Hamaker and Debye terms, Steric is not included (and is so large anyway that we don't need W). Like so much of DLVO theory, when you implement it, the results are somewhat disappointing - W rises to huge values (I simply stop displaying them and say "Large - Stable") once the zeta potential gets into the conventional range of ~25-30mV, confirming the rule of thumb that that's the range required for stability. However, that rule assumes that your Hamaker constant is the typical small value. Once A12 gets large then the rule of thumb breaks down and W is more important.

### Coulombic Stabilization

There is continuing controversy about charge stabilization in low dielectric constant solvents. If we assume that somehow particles can aquire a zeta potential, then the effect of it extends over a long range because we don't have the electrical double layer effects behind the standard V_{D} calculations. If you turn on the Coulombic option (and have a low dielectric constant) then you will see some funny V_{D} curves that are especially significant for larger particles.

The calculations are based on a paper from Ian D. Morrison, *Criterion for Electrostatic Stability of Dispersions at Low Ionic Strength*, Langmuir 1991, 7, 1920-1922. They include a calculation of W, the Stability Ratio (rate constant for diffusion-controlled coagulation/second-order coagulation rate constant), where a large value (say 5000) means that the particles are stable against coagulation.

I welcome feedback on this new (Nov 2019) feature in the app, given its controversial nature.