Polaron closes £6m round to predict manufacturability using microscopy-trained AI
This article covers Polaron, a materials startup spun out of Imperial College London, which has closed a £6m growth funding round led by Racine2. The funding will be used to expand engineering capacity and accelerate rollout of its generative design tools to meet demand from manufacturing customers in the automotive, energy and advanced materials sectors.
Polaron, a materials startup spun out of Imperial College London, has closed a growth funding round of £6 million led by Racine2. The money will be used to expand engineering capacity, accelerate rollout of its generative design tools and meet demand from manufacturing customers in automotive, energy and other sectors — a funding event that highlights renewed investor interest in applying AI to real-world materials and manufacturing problems.
Why it matters
Manufacturing of advanced materials has long been hampered by a gap between how materials are processed and how they perform in products. Polaron aims to shorten that cycle by linking production choices directly to measurable performance, which can speed development and reduce costly trial and error.
The company says its tools are already in use at global manufacturers, including electric vehicle makers responsible for more than a third of world EV production, and cites a use case where battery electrode design driven by its platform delivered energy density improvements of more than 10 percent. If reproducible at scale, gains like that can have meaningful impact on EV range and energy storage economics.
Inside the product
Polaron trains machine learning models on real microscopy images and matched measured properties to interpret microstructure and predict material behaviour. The platform is presented as an "intelligence layer" that helps engineers translate microstructural features into actionable process changes, reducing weeks or months of manual analysis to minutes.
Its roadmap includes generative design capabilities that propose process or structural changes to hit target properties, and integrations targeted at industries where microstructure matters most: automotive components, battery electrodes and other advanced materials applications. The company says development grew out of seven years of research at Imperial College London that combined AI and materials science.
Who are the investors?
The round was led by Racine2, described in the announcement as an impact-focused fund associated with Serena and Makesense. Co-investors include Speedinvest and Futurepresent, alongside angel investment from senior figures in the industrial AI ecosystem.
The investors framed their support around Polaron's route to industrial maturity: grounding AI models in microscopy and production constraints rather than purely atomistic discovery.
In the announcement, Alix Trébaol, Investor at Serena, said:
In materials, AI is commoditising atomistic discovery. The winners will be the ones who can predict real-world industrial manufacturability. No one but Polaron knows how to do this today.
In the announcement, Florian Obst, Investor at Speedinvest, said:
What impressed us about Polaron is its focus on the point where materials innovation often breaks down: translating scientific insight into manufacturable reality. By grounding AI in real microstructural data and industrial constraints, Polaron is building a platform that can accelerate how advanced materials move from research into production.
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Founder perspective
Polaron was founded by researchers from Imperial College London after seven years of lab and modelling work. The team plans to use the new funding to grow its engineering team, expand deployment of its generative design tools and support an expanding customer base across automotive and energy supply chains.
In the announcement, Isaac Squires, Co-founder & CEO at Polaron, said:
For 150 years, industry has used machines to shape materials. Now, we are teaching machines to understand them. Polaron is building an intelligence layer powered by the world’s materials data for faster discovery, better design and a new generation of advanced materials.
The bigger picture
This raise sits at the intersection of university spinouts and industrial AI applied to hardware-heavy sectors. It reflects growing interest from materials investors in companies that can bridge lab-scale discovery and manufacturable solutions. As manufacturers pursue electrification and lighter, higher-performing components, tools that help predict manufacturability and optimise microstructure could attract more funding and commercial partnerships across the UK and Europe.
Polaron’s trajectory — an Imperial spinout commercialising seven years of research, signed pilots with large manufacturers and a £6 million growth round — is one of several recent examples of deep-tech startups looking to move materials science from research into production.
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