AI startup Discovered Materials has secured $9 million to develop faster methods for discovering new semiconductor materials, aiming to address thermal management challenges in chip design and improve device performance.
Discovered Materials, an AI startup focused on semiconductor materials, has raised $9 million in seed funding led by Lightspeed India Partners, according to The Hindu BusinessLine. The round also drew backing from Y Combinator, Peak XV Partners and angel investors including Paul Graham, Gokul Rajaram and Anthropic’s Thariq Shihipar. The company said it will use the money to grow its team, expand its laboratory and scale the research agents it is building for materials discovery.
The startup’s pitch is straightforward but technically ambitious: use AI agents to narrow the long search for new chip materials, which can otherwise take years of laboratory work. Y Combinator says Discovered Materials is aiming to compress that process into months, with AI systems that identify and test candidate materials more quickly than conventional methods. The company has also said its systems produced new thermal materials in three months that matched the performance of products developed over much longer periods by major chemical groups.
The business is entering a field where materials performance is becoming central to chip design. As computing loads rise, chipmakers face tighter constraints on power use and heat management. Co-founder Akash Ramdas told The Hindu BusinessLine that “New materials are how we close that gap”, referring to the widening divide between raw computing power and energy efficiency. The company’s work is directed at that bottleneck, especially in thermal materials, where even modest improvements can affect device performance and reliability.
Discovered Materials was founded by IIT-Madras alumni Advaith Sridhar and Ramdas. Ramdas has a PhD in materials science from Stanford University and says he has spent 11 years researching materials for semiconductor chips, while Sridhar studied AI at Carnegie Mellon University and previously worked on AI models and agents at Persona AI and Luma Labs. The company has also published hundreds of AI-identified materials and introduced Material Discovery Bench, a benchmark designed to test AI agents on real semiconductor materials problems.
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