Sustainable AI: How ExoMatter Is Revolutionizing Material Discovery

Trial and error is a thing of the past: Thanks to artificial intelligence, carefully selecting raw materials saves a tremendous amount of resources and time in product development.

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Traditional research often relies on “trial and error” when trying to find the right material for a specific application. AI is now replacing such inefficient processes: Artificial intelligence can quickly identify the most cost-effective, sustainable, and suitable materials for any application.

The solution lies in the digitization of materials science. A pioneer in this field is the Munich-based startup ExoMatter.

ExoMatter helps Audi, Infineon, and others with material development

ExoMatter was founded in 2022 as a spin-off of the German Aerospace Center (DLR) and grew out of the renowned UnternehmerTUM program. With a team of 11 employees, the B2B company supports some of Germany’s leading industrial giants—including Audi, Infineon, and Airbus—in their fundamental materials development.

At the heart of ExoMatter is the use of powerful AI tools and data mining capabilities—that is, the extraction of useful data and the identification of patterns in large datasets. Instead of tying up time and resources in countless physical experiments, the platform draws on a wide range of scientific data sources or directly integrates customers’ proprietary data. This data is enriched and analyzed by AI to uncover complex relationships that would otherwise require years of manual research by a human.

The platform offers researchers and developers precise tools to significantly shorten the process of searching for the ideal material.

• Flexible Search: Users can either search specifically for a known formula—in which case the system automatically corrects any errors—or search for a specific composition by selecting chemical elements from the periodic table.
• Smart Filtering: With six specific filters for material properties—including carbon footprint, cost, and literature references—results can be narrowed down precisely.
• The ExoMatter Score: To facilitate decision-making, the “ExoMatter Score” evaluates material candidates based on how well they match the specific search criteria.

Ecological Efficiency and Sustainable AI

A common argument against AI applications is the energy consumption associated with the required computing power. ExoMatter clearly counters this argument. As a Software-as-a-Service company, the Munich-based firm relies on existing cloud infrastructures and does not need its own energy-intensive data centers.

The environmental benefits are exponential: While the damage caused by computing power is linear and limited, the benefits derived from the identified materials far outweigh it.

A concrete example from the year 2026 underscores this: The Dutch direct-air-capture company “Carbyon” turned to ExoMatter to find more efficient materials. The AI identified solutions with energy requirements 6–7 times lower than the specified maximum. The savings achieved by using these materials in subsequent mass production exceed the computational energy expended on the search by orders of magnitude.

Artificial intelligence can make materials development more sustainable

ExoMatter thus demonstrates how specialized physical simulations and large language models (LLMs) can revolutionize industrial research. By digitizing the laborious search for new materials—for example, for higher-performance batteries—they pave the way for a more efficient and sustainable future.

Cover photo: CC Luiza Braun, Unsplash; edited by Tina Teucher Team

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Tina Teucher is a speaker and moderator specializing in sustainable business. In her keynote speeches, she inspires audiences with her insights into the intersection of artificial intelligence, the circular economy, and megatrends, and highlights the opportunities presented by an ecological transformation. As a co-founder of startups such as the digital company Future Cooperative (product: Future Maps), Tina Teucher also brings her practical business management experience to the stage.

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