Maturity of Hansen Solubility Parameters (HSP) Usage in Different Applications
Last update on Nov 30, 2020
Science-based Formulation
HSP holds the promise to speed-up formulation development in every application where ingredient compatibility is a must. Based on science, you can avoid unfocused trials and directly work with combinations that have a chance to give a result.
For the past 3-4 years, HSP has gained renewed traction due to an overall focus on bringing more science and calculation power (sometimes artificial intelligence but not only) into formulations.
Yet, even if, in theory, it can work everywhere; in practice, you need the right data and you need to know where you can best leverage this predictive tool.
Hansen Solubility Parameters (HSP) have been around for more than 50 years and have found their initial playing field mostly in the field of solvents, solvent blends and polymer-solvent compatibility. Beyond these native applications, there are many fields on the rise, with varying maturity levels.
Here is a mapping of the tool maturity per application to help you see if you can gain a competitive advantage straight away or in the near future. (It may be worth for you to invest in the generation of the right HSP data!) This mapping is based on the best of our knowledge today. Please help us enrich it by sharing your views. Answer the quick 5 questions to express your opinion and experience on HSP.
Before we continue with the maturity mapping, let us remind you that you can track what is happening in this field by subscribing to weekly updates on Science-based Formulation Channel!
Also, if you are new to this field or need a refresher, we recommend you to first watch first the following Tutorial series by SpecialChem's Partner VLCI!
Let's look at the different applications across different formulation domains, the anticipated impact of HSP, the adoption rate of HSP and the data availability.
HSP holds the promise to speed-up formulation development in every application where ingredient compatibility is a must. Based on science, you can avoid unfocused trials and directly work with combinations that have a chance to give a result. For the past 3-4 years, HSP has gained renewed traction due to an overall focus on bringing more science and calculation power (sometimes artificial intelligence but not only) into formulations.
Yet, even if, in theory, it can work everywhere; in practice, you need the right data and you need to know where you can best leverage this predictive tool.
Hansen Solubility Parameters (HSP) have been around for more than 50 years and have found their initial playing field mostly in the field of solvents, solvent blends and polymer-solvent compatibility. Beyond these native applications, there are many fields on the rise, with varying maturity levels.
Here is a mapping of the tool maturity per application to help you see if you can gain a competitive advantage straight away or in the near future. (It may be worth for you to invest in the generation of the right HSP data!) This mapping is based on the best of our knowledge today. Please help us enrich it by sharing your views. Answer the quick 5 questions to express your opinion and experience on HSP.
Before we continue with the maturity mapping, let us remind you that you can track what is happening in this field by subscribing to weekly updates on Science-based Formulation Channel!
Also, if you are new to this field or need a refresher, we recommend you to first watch first the following Tutorial series by SpecialChem's Partner VLCI!
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Let's look at the different applications across different formulation domains, the anticipated impact of HSP, the adoption rate of HSP and the data availability.
Mapping the Use of HSP for Every Application
There are many applications for HSP in formulations (HSP of skin in cosmetics, oil field extraction chemicals, barrier effects in plastics, fragrances, polymer blend, etc.). Here we focused on a selected number of cases that seemed to be of particular interest to SpecialChem's community.
| Domain | Adoption Rate of HSP & Data Availabilty | Used in Cases | |
| Pigments-dispersants | Coatings |
| Find the most efficient dispersant that will minimize pigment usage. |
| Solvent replacement | Coatings, Adhesives |
| Identify most probable solvent or solvent blend with more desirable tox and ecotox profile. |
| Binder-solvents | Coatings, Adhesives |
| Optimize film forming properties of solvent-borne coatings. |
| WB binders-coalescent | Coatings, Adhesives |
| Optimize film forming properties of waterborne coatings. |
| Diluents / monomers | Reactive systems (UV Cure, 2K Systems, Reactive Adhesives) |
| Increase compatibility between monomers, oligomers and crosslinkers. |
| Active-emollient/oil | Cosmetics |
| Increase activity of the ingredient in the formulation, reduce dosage. Creatively formulate with natural oils adapted to active ingredient. |
| Surfactant-oil | Cosmetics |
| Compatibility of bio-based surfactants and natural oils to create distinctive natural formulations. |
| UV Filters / oil | Cosmetics |
| Maximize compatibility of UV Filter and solubilizer to minimize concentration of under scrutiny organic UV filters. |
| Plasticizers / Binders / Polymers | PVC compounds, Adhesives, Inks |
| When new polymers are being introduced, such as PLA, HSP are used to select compatible plasticizers. |
| Resins / Tackifiers | Adhesives |
| Use to measure compatibility of block-copoylmers and tackifiers. For example, in Pressure sensitive adhesives. |
We are seeing more and more traction about HSP driven by several factors:
- Desire of formulators to do less trial/test/error related to compatibility and stability. Using more predictive calculation power they aim to reduce the number of tests actually performed and gain speed in formulation development.
- Major trend with large formulators to both centralize and digitize product and formulation data. This is part of digital transformation of companies who want more and more reliability and traceability. This topic goes beyond HSP and covers data sheets, product information, formulation documentation, transformation modelization, using calculation models to predict properties based on chemical structure…
- Raw materials who want to speed up adoption of their new chemistries, making HSP of their products and relevant co-ingredients available. This data could be more usable than generic starting formulations.




