The problem with thermoelectrics today

The problem with thermoelectrics today

The problem with thermoelectrics today

They're toxic, inefficient, costly and rely on rare earth metals.

They're toxic, inefficient, costly and rely on rare earth metals.

A new generation
of materials with AI

A new generation
of materials with AI

A new generation of materials
with AI

Mater-AI is producing materials more efficient than the industry gold standard, optimised for electrical
and thermal conductance.

Mater-AI is producing materials more efficient than the industry gold standard, optimised for electrical and thermal conductance.

Mater-AI is producing materials more efficient than the industry gold standard, optimised for electrical
and thermal conductance.

438× faster than conventional R&D

438× faster than
conventional R&D

438× faster than conventional R&D

Thermoelectric materials with superior efficiency and no toxic elements have the potential to transform power generation and solid-state cooling across automotive, industrial systems, and IoT applications.

Thermoelectric materials with superior efficiency and no toxic elements have the potential to transform power generation and solid-state cooling across automotive, industrial systems, and IoT applications.

World-class lab partners

Mater-AI synthesise and test our AI-designed materials with University of Cambridge, Henry Royce Institute,
Imperial College London.

World-class lab partners

We synthesise and test our AI-designed materials with University of Cambridge, Henry Royce Institute, Imperial College London.

World-class lab partners

We synthesise and test our AI-designed materials with University of Cambridge, Henry Royce Institute, Imperial College London.

We bring AI-discovered thermoelectrics materials into the real world for power generation and solid-state cooling. By significantly improving efficiency, we’re not only replacing legacy systems but also enabling entirely new applications.

Let's build a better material future.

Let's build a better material future.

Let's build a better material future.

Whether you're a collaborator, investor, or visionary partner,

lets shape the future together.

Whether you're a collaborator, investor, or visionary partner,
lets shape the future together.

Whether you're a collaborator, investor, or visionary partner, lets shape the

future together.

Contact Us

Contact Us

Contact Us

Meet the founding team

Meet the
founding team

Dr. Nickel Blankevoort

Co-Founder, CEO

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PhD Quantum Nanotechnology &

Thermoelectrics, Metrology Engineer


Uni. of Warwick, Entrepreneur First, ASML

Chelsea Williams

Co-Founder, CTO

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PhD cand. in Quantum Computing, AI,

Physics, Quant. Analyst


Uni. of Exeter, Uni. of Cambridge, NWM

Gatleen Bhambra

Co-Founder, COO

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Product, Commercial, Operations,
MSc Int. Business Management

Jacquard, Revolut, Gate One Consulting

Dr. Jack Broad

Founding AI Scientist

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PhD in App. Mathematics,
Post-doc ML for Materials Discovery


Uni. of Nottingham, Berkeley National Lab

We're backed by world-class investors

We're backed by
world-class investors

Keep up to date with the latest research

Addressing the Readout Problem in Quantum Differential Equation Algorithms with Quantum Scientific Machine Learning

30 Jun 2025

Chelsea A. Williams, Annie E. Paine, Antonio A. Gentile, Daniel Berger, Oleksandr Kyriienko

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Quantum Iterative Methods for Solving Differential Equations with Application to Computational Fluid Dynamics

12 Apr 2024

Chelsea A. Williams, Antonio A. Gentile, Vincent E. Elfving, Daniel Berger, Oleksandr Kyriienko

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Exploring the Impact of the HOMO–LUMO Gap on Molecular Thermoelectric Properties: A Comparative Study of Conjugated Aromatic, Quinoidal, and Donor–Acceptor Core Systems

05 Feb 2024

Nickel Blankevoort, Pablo Bastante, Ross J. Davidson, Rebecca J. Salthouse, Abdalghani H. S. Daaoub, Pilar CeaSantiago, Martin Solans, Andrei S. Batsanov, Sara Sangtarash, Martin R. Bryce*, Nicolas Agrait*, Hatef Sadeghi*

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Scaling of Quantum Interference from Single Molecules to Molecular Cages and their Monolayers

07 Nov 2022

Xiaohui Xu, Juejun Wang, Nickel Blankevoort, Abdalghani Daaoub, Sara Sangtarash, Jie Shi, Chao Fang, Saisai Yuan, Lichuan Chen, Junyang Liu, Yang Yang, Hatef Sadeghi, Wenjing Hong

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Parallel Implementation of Nonadditive Gaussian Process Potentials for Monte Carlo Simulations

Jack Broad,* Richard J. Wheatley, and Richard S. Graham

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