Are you developing new chemical compounds, designing formulations, or aiming to improve or manage a chemical process?
In each of these examples, you will need to optimise the impact of multiple parameters. And you will be doing this based on data from experiment or production that you are constantly seeking to understand and improve. The Alchemite software can help. Find out how you can apply it to guide your experimental programs, getting better results in less time, and to get vital insights into what is driving the performance of your products or processes, ensuring quality and enabling effective innovation.
Alchemite was used to predict the physical properties of alkanes, combining sparse experimental data with results from molecular dynamics simulations. It accelerated the identification of optimal hydrocarbons, out-performing alternative physico-chemical and thermodynamic methods.
Alchemite helps to guide testing and find optimal formulations for products such as paints, inks, coatings, foods, flavours, and fragrances. Find out more about the Domino Printing Sciences ink case study.
Alchemite for Chemicals
With the Alchemite software, chemists, chemical engineers, and data scientists can apply powerful deep learning methods to get more from their data. You could use Alchemite to:
- Validate and clean your data from experiment or production
- Design better experiments – decide what to measure next for maximum insight at least cost
- Quickly generate models that tell you what is driving the performance of your product or process
- Run virtual experiments to on candidate chemicals
- Optimise process parameters
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