Materials or molecules are essential to every aspect of our lives, from the clothing we wear, the phones and vehicles we use, the energy that powers our lives, to what we eat and the medicines we need. The solution is a cloud-based software platform deploying our leading machine learning (ML) algorithms that make materials R&D faster, greener, and more productive. This allows companies to develop better materials and molecules faster, while minimizing their waste and carbon footprint. The solution solves optimization problems that existing methods cannot solve, increasing the probability of discovering novel breakthrough materials. The solution works with existing processes and allows R&D labs to replace the slow and expensive trial-and-error method with a data-driven method, where the platform and algorithms orchestrate and guide the experiments. Companies can deploy leading ML algorithms with no coding and no ML-expertise required.

The Environmental Benefits

• •Atinary solutions are 10x faster and lead to better performance than state-of-the-art methods used in industry, such as high-throughput experimentation and Design of Experiment
• •Atinary solutions can solve complex optimization problems that current methods cannot, including multi-objective optimizations with categorical variables and non-linear constraints
• •Applications include catalysis, formulation, and process optimization of materials for climate tech, health, and chemicals
• •Atinary solutions can find the optimal blend formulation of organic polymer solar cells with less than 3% of the samples needed using conventional traditional trial-and-error methods and high-throughput experimentation (HTE).
• •Atinary solutions accelerate the process by 6x and improves efficiency by 25% compared to current state-of-the-art Design of Experiment (DoE)
• •Atinary Falcon outperformed algorithms from renowned universities in the U.S. in a competition to discover optimal perovskite crystals for solar cells, with the highest success rate of all resulting in high quality perovskite crystals

The Financial Benefits

• •Reduce the number of samples and experiments needed to find optimal materials and molecules by up to 33x compared to high-throughput experimentation and up to 22x compared to Design of Experiment
• •The transfer learning algorithm accelerates materials optimization and discovery by up to 5x, leveraging prior knowledge from past experiments and use this knowledge in new applications
• •Increase the probability of discovering the advanced materials needed to develop biodegradable plastics, or better, lighter, non-toxic, non-flammable and/or easier to recycle batteries

Target client profile

• Public Authorities
• Business

Activity Region

• Headquarters
• Activity

Company Profile