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CuspAI, a company with about 20 employees, is focusing on AI-based materials research.

The company is developing a platform that serves as a kind of ‘search engine for materials’. This uses machine learning to design new materials for various applications. The first areas of application include:

  • gas separation and carbon capture: new materials could significantly improve the efficiency of CO₂ separation.
  • Semiconductor materials: As the miniaturisation of chips continues, materials research is becoming increasingly important to find new, more powerful alternatives to silicon.
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    The platform is based on generative AI models that create and simulate new molecules. In addition, CuspAI uses physics-based models to predict the properties of these molecules.

    Technological foundations and AI models

    The platform relies on various methods:

  • generative models that design new molecules and condition their properties.
  • force fields that enable physical simulations by calculating the energies and forces of atoms.
  • property predictors that bypass simulations by directly predicting material properties.
  • AI-powered search agents that efficiently filter the best materials from a large set of potential combinations.
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    Welling emphasises that AI is enabling tremendous progress in materials research. Simulations that used to take weeks can be done in seconds with AI-powered models.

    Data sources and collaboration with companies

    CuspAI draws on various data sources, including:

  • Public databases such as Materials Project and Nomad.
  • Company-specific data provided through collaborations with companies.
  • In-house simulations that generate synthetic data to improve the AI models.
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    A particular challenge is combining domain-specific knowledge with AI. Welling describes how many companies have data but not the necessary machine learning experts to use it efficiently. CuspAI offers a bridge between materials science and AI.

    For the next phase, Welling is looking for excellent researchers in the field of machine learning and chemistry. The company's locations – including Cambridge, Amsterdam and Berlin – offer an attractive environment for European talent.