Mater-AI raises £1.5M to turn waste heat into electricity
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Mater-AI raises £1.5 million to turn waste heat into electricity

The UK startup uses AI to discover novel materials that convert heat into electricity and cooling.

12/3/2025
Othmane Taki
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UK-based startup Mater-AI has successfully raised £1.5 million in a pre-seed funding round to advance its innovative materials discovery platform. The company utilizes artificial intelligence to design novel thermoelectric materials capable of converting waste heat into usable electricity. This breakthrough technology aims to address a significant and long-standing challenge in global energy efficiency, where over 70% of energy is currently lost as heat.


Addressing a Decades-Old Energy Challenge

The vast majority of global energy, valued at over $152 billion annually, is dissipated as waste heat across sectors from data centers to heavy industry. This represents a substantial economic and environmental inefficiency that has persisted for decades. The last significant advancement in thermoelectric materials was bismuth telluride in the 1950s, a semiconductor that has since seen limited improvement.

An AI-Powered Discovery Engine

Mater-AI has developed a proprietary platform that combines AI and physics-based modeling to accelerate the design of new materials from decades to weeks. This system can generate and evaluate 100 potential material structures every hour, a stark contrast to traditional research methods. The platform optimizes for key properties like thermal and electrical conductivity to achieve higher efficiency, lower cost, and greater scalability.

The technology is an evolution of research conducted by co-founder and CEO Dr. Nickel Blankevoort, who discovered just three new structures in a year using conventional techniques during his PhD. Founded by Dr. Blankevoort, Gatleen Bhambra (COO), and Chelsea Williams (CTO), the company aims to create a new generation of materials for energy recovery. Their approach turns a historical limitation into a powerful opportunity for system-level change.

Strategic Vision and Market Opportunity

The company is initially targeting high-value applications in the defence, automotive, and industrial Internet of Things (IoT) sectors. Enhanced material performance in these areas could unlock between £3.4 billion and £4.6 billion in new market value. These industries require durable, maintenance-free power sources that can operate effectively in remote or extreme environments.

COO Gatleen Bhambra envisions a future with a fundamentally different energy architecture where waste is transformed into a resource. “Imagine data centres generating their own power from waste heat, electric vehicles that travel further by recapturing their thermal energy,” she stated. This mission underpins the company's goal to create a world where infrastructure and devices can power themselves.

Investor Confidence and Future Roadmap

The funding round was led by Twin Path Ventures and saw participation from Mishcon de Reya, One Planet Capital, XTX Ventures, and the Conception X Angel Syndicate. This strong investor backing will fuel accelerated research, team growth, and laboratory validation of its AI-discovered materials. The company has already forged partnerships with the University of Cambridge, Imperial College London, and the Henry Royce Institute.

Nick Slater, Partner at Twin Path Ventures, highlighted the technology's foundational potential to accelerate a sustainable energy future. “Mater AI is addressing a fundamental bottleneck in the energy transition: the discovery of next-generation thermoelectric materials,” he commented. Over the next 18 months, the company will iterate between lab results and its AI models to refine and validate a commercially viable material.


Mater-AI's successful funding round marks a pivotal moment in the quest for greater energy efficiency through advanced materials. By leveraging AI to overcome decades-old scientific hurdles, the company is well-positioned to make a significant impact on sustainability and industrial innovation. Its progress from computational design to real-world application will be a key development to watch in the deep-tech landscape.