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SDLabs

An AI and machine learning software platform to accelerate materials R&D and innovation

October 2022

SDLabs

An AI and machine learning software platform to accelerate materials R&D and innovation

  • World Alliance Member
  • Featured Solution
  • Labelled Solution
Label Date October 28, 2022
From Switzerland
Maturity stage TRL 7 - Prototype testing in the real world

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

Activity Region

  • Headquarters
  • Activity

Company Profile

Atinary Technologies

Machine learning startup making R&D and discovery of advanced materials and molecules 10x faster, better and greener.

Headquarters 1066 Épalinges, Switzerland
Type Startup or self-employed
View company profile Solution website

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The information set out above, is solely for the purposes of information and the Solar Impulse Foundation does not provide any guarantee as to its authenticity, completeness or accuracy. This information does not constitute investment advice or a recommendation to buy into, transact or to enter into any agreement with any of the parties or persons mentioned above. Potential investors or interested parties are solely responsible for their investment or business decisions and for performing any due diligence required by the circumstances. The innovator Atinary Technologies has asserted ownership of the intellectual property rights for images, videos, and content showcased above, affirming full and unrestricted usage rights, and has provided explicit permission for the Solar Impulse Foundation to publish such information designated as "public" in the application form.