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Discovered Materials raises $9m to hunt for cooler chip materials

Discovered Materials has raised $9 million in seed funding to use AI agents to find new materials for more efficient computer chips. The startup says it has already found several materials matching the properties of those used by major chipmakers.

  • Discovered Materials closed a $9 million seed round led by Lightspeed India Partners, with investment from Peak XV Partners and angel investors.
  • The startup uses AI agents and physics models to generate and verify thousands of potential semiconductor materials daily.
  • The company plans to patent valuable materials for use in GPUs and license them to chipmakers.

Discovered Materials has raised $9 million in seed funding to use AI agents to find new materials for building more efficient computer chips. The round was led by Lightspeed India Partners, with participation from Peak XV Partners and angel investors including Paul Graham, Gokul Rajaram, and Thariq Shihipar.

The startup, founded by Advaith Sridhar and Akash Ramdas, uses Anthropic models in a custom harness to generate material leads. Foundational physics models trained by the company then run simulations to verify whether the candidates are of interest. Sridhar said the system allows thousands of guesses a day, compared with around 20 during Ramdas's PhD.

Discovered Materials has released examples of hundreds of new materials and a benchmark designed to track how frontier models handle the challenge. The company says it has already discovered several materials that match the properties of existing materials used by major chipmakers, but cannot share more details.

Hemant Mohapatra, the Lightspeed partner who led the round, described the work as "playing whack-a-mole with atomic structures," noting that a material is only useful if all its properties converge. He said filtering and synthesising candidates is the bottleneck, rather than finding them.

Sridhar said the company will attempt to patent the use of valuable materials in GPUs or the manufacturing process, licensing them to chipmakers. He hopes to have new materials worth patenting within the next year.

Why this matters: Chips running AI workloads generate significant heat, contributing to high electricity consumption in data centres. Finding more efficient materials could reduce this demand.

What this means for you: More efficient chip materials could eventually lead to cooler-running devices and lower energy use in data centres.

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