Faster and smarter chemical R&D with accurate physical property predictions

ended

Accurate knowledge of properties of chemical compounds is essential for all chemical research. Without it, cutting-edge research becomes very expensive or impossible, and costly decisions to buy unnecessarily large or powerful equipment may be made. 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”. In a completely new approach, Hafnium Labs has developed a software tool that systematically analyses the best computer models and experimental data to provide predictions that are >10 times more accurate than current state-of-the-art models. This will allow scientists to short-circuit months of experimentation, to optimize processes and to investigate more molecules that could have breakthrough properties. Q-props has been successfully used in three contracted projects with large customers and Hafnium Labs has five letters of support and verbal expressions of interest from over 20 other global oil & gas, chemicals and pharma companies. Hafnium Lab's strategic goal is to become the market leader for property predictions across all stages of chemical R&D, all industries, and ranging from large corporations to SME's and research institutions. The financial goal is to reach sales of €50m and EBITDA of €16m in 2025. Hafnium Labs has a TRL6 prototype operating in its own cloud, but to address customers' need for confidentiality in their R&D work and enable revenue scale-up, the first objective of the Phase 2 project is to modify the prototype so that it can run on customers' own clouds. The second objective is to optimize and simplify how customers work with their own valuable data in Q-props and the third objective is to ensure that the software can be used by all chemical scientists and engineers, including those who lack specialist knowledge of chemical modelling.