Project introduction

Accurate knowledge of properties of chemical compounds is essential for all chemical research. Without it, cutting-edge research becomes very expensive or impossible.

However, experts estimate that we have experimental physical property data for less than 0.2% of relevant chemical systems — and most is for petrochemicals. There is almost no data for biochemicals, carbon capture molecules, electrolytes, or other chemistries that we need for the green transition.

Experimentation is accurate but slow and very expensive. On the other hand, all computer models for chemical properties are inaccurate, because chemical interactions are too multi-layered and complex for us to model, even with the much-vaunted “power of AI”.

Choosing the right model for your chemistry, fitting it correctly to the experimental data, and ensuring that the data is actually sufficient and reliable is difficult, even for a physical property expert.

That is why Hafnium Labs has developed Q-props, a pioneering software that sets a modern gold standard for obtaining reliable physical properties for any chemistry. Q-props uses all available data and models to always give the best possible property prediction and information on how reliable each prediction is.

Before the Horizon 2020 project was launched, Q-props was running internally on Hafnium Labs’ cloud servers. The main objective of the project was to enable customers to run Q-props on their cloud and in their process simulators. The second objective was to optimize and simplify how customers work with their own valuable data in Q-props, while the third objective was to ensure that the software can be used by all chemical scientists and engineers, including those who lack specialist knowledge of chemical modelling. 

What have we achieved so far and where are we now?

The project has ended successfully.

In the first project period, the major focus was on developing a version of Q-props that could be deployed on customer side and, thus, run in full confidentiality. Further, Q-props was optimized to make it more robust and enhance security when accessing and updating the tool.

In the second project period, the major focus was on executing demonstration projects with industrial partners to show the potential of using Q-props to solve a wide range of problems encountered in the chemical and energy industries, and improving Q-props in several aspects.

This work has included developing different means for easy data integration and developing Q-props interfaces for specific use cases.

Commercially, Q-props has evolved from a single product with a somewhat complex deployment to a suite of tools with each their unique value proposition and simple deployment: