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Practical Determination and Application of HSP for the Paints & Coatings Industry

Sander van Loon – Jun 12, 2018

Co-Author: Beverley Fricker

Practical Determination and Application of HSP for the Paints & Coatings IndustryThe formulation challenges in the paints and coatings industry are miscellaneous and complex. Moreover, “trial and error” continues to be a widely adopted methodology, which is time-consuming, intensive, and increases time-to-market.

Coating formulations consist of many different types of raw materials (binders, fillers, pigments, solvents, and additives) which should mix be together into one stable and homogeneous dispersion. As the diversity of raw materials available on the market is boundlessly broad, adopting a science-based approach can speed up the development process.

One such approach involves the use of Hansen Solubility Parameters (HSP), which is particularly relevant for predicting ingredients compatibility, and therefore, makes their selection easier for the formulators. This efficiently allows you to narrow down the formulation space as opposed to trial-and-error methods.

In the field of coatings, typical challenges can be tackled by using this approach; for example, HSP can predict an optimal dispersant for a specific pigment/filler (blend), resulting in lower viscosity, as well as lowering the amount of dispersant needed. An optimal dispersant will impart maximal hiding power and color intensity, excellent stability against flocculation and will prevent issues such as pigment flooding and floating.

A lower viscosity will be beneficial in many aspects:

 − Reduce VOC
 − Increase pigment content (in the case of pigment pastes) and solid content in general, and
 − Extend possibilities for rheology improvements

In addition, lower amounts of dispersants will raise the barrier performance of the coating and can also lead to more cost-efficient formulations. This is just one example among many other application possibilities of HSP which are worth considering for efficient coating developments.


Smart & Predictive Formulations via Hansen Solubility Parameters


In 1967, Charles Hansen submitted his doctoral thesis “The three-dimensional solubility parameter and solvent diffusion coefficient” which introduces the theory which has since become known as the Hansen Solubility Parameters (HSP). These parameters have removed the trial-and-error process and given practical solutions to countless problems across a wide variety of formulation-based industries (Hansen, 2017).

The term “solubility parameters” is now considered to be quite restrictive, as the use of HSP goes beyond solubility challenges: these parameters can predict the compatibility for various types of chemicals/ingredients, allowing for smart and predictive ingredient matching. Therefore, HSP should be interpreted as “Hansen Similarity Parameters”, as recognized by Dr. Hansen.

The Hansen Solubility Parameters are made up of - δD (Dispersion forces); δP (Polar forces) and δH (Hydrogen bond forces). By plotting these in a 3D space in the HSPiP software, it is easy to visualize and interpret the results. When the HSP has been practically determined, the Compatibility Radius is also provided; all solvents/ingredients within this radius are compatible with the test product. The radius is concentration dependent, the higher the concentration of the product the smaller the radius.

The software HSPiP is now led by Professor Steven Abbott with Dr. Hiroshi Yamamoto. (Abbott, 2017) (Yamamoto, 1999 - Present). VLCI is a certified center for practically determining HSP and has been doing so in close collaboration with Professor Abbott and Dr. Hansen since 2010, for all areas of the formulation world.

To learn more about the fundamentals of HSP, see Professor Steven Abbott’s Article: Science-based Formulation: The XL Power of HSP for Coatings Compatibility Issues


Practically Determining Hansen Solubility Parameters


The classic method to practically determine a product’s HSP involves the test material being added to a range of solvents that cover the HSP space. The samples are shaken and left to dissolve. The samples are then visually assessed with a qualitative rank from 1-6, where a 1 means the product is completely dissolved, a 6 means there has been no interaction between the solvent and the product and the other scores indicating various stages of dissolution.

Stages of Dissolution
Stages of Dissolution


This data is then entered into the HSPiP Software, which defines a spheroidal cluster of the solvents that dissolve the test material. This cluster is called the Hansen Solubility Sphere and its central coordinates (δD, δP and δH) define the solubility parameters of the test material. The software also performs an analysis of the “fit” of the data to the parameters it has determined, highlighting the validity of the result, which can indicate if more experimental data is needed.

HSP Sphere
HSP Sphere


This theory can be applied to a wide range of situations, including crosslinked (insoluble) polymers, additives, pigments, nanoparticles etc. The scoring is then based on criteria such as swellability or resistance to sedimentation, VLCI offers the following test methods and HSP workflows for a range of materials and is able to develop bespoke tests for challenging molecules:

Method Suitable for
Dissolution Method Simple solutes, mixtures, additives
Quantitative Swell Test Crosslinked and insoluble polymers
Sedimentation Method Insoluble particles, e.g. pigments
Liquids Method Low molar volume liquids, e.g. solvents

Polymers, surfactants, solvents, insoluble pigments, films, complete formulations and much more can be practically determined!


 » Continue reading to explore how to interpret the results out of HSP obtained from raw materials and thus, learn to implement them in your coating formulation.


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