Xanadu Awarded $2.0M ARPA-E Grant for Quantum Battery Research

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Insider Brief

  • Xanadu Quantum Technologies has been awarded approximately $2.0 million in funding from Advanced Research Projects Agency-Energy to develop quantum computing tools for battery materials research.
  • The project is part of the QC3 program and will focus on developing quantum algorithms to simulate defect formation processes in battery materials.
  • Xanadu will collaborate with researchers from the University of Chicago to improve simulation efficiency with a goal of achieving up to a 100× runtime reduction compared to current classical methods.

PRESS RELEASE — Xanadu Quantum Technologies Inc. (“Xanadu”), a leading photonic quantum computing company, announced today that it has been selected to receive $2,027,507 in funding from the U.S. Department of Energy Advanced Research Projects Agency-Energy (ARPA-E). The funding is part of the Quantum Computing for Computational Chemistry (QC3) program that seeks to develop and apply quantum algorithms to accelerate simulations of chemistry and materials science to advance commercial energy applications ranging from superconducting power lines, advanced batteries, engineered rare earth magnets, and breakthrough catalytic systems.

“Xanadu is proud to have been selected by ARPA-E to develop a quantum simulation platform for next-generation batteries,” said Christian Weedbrook, Founder and Chief Executive Officer of Xanadu. “This award builds on our strong track record of working with government partners to address important, real-world challenges. As we get closer to our combination with Crane Harbor Acquisition Corp. (NASDAQ: CHAC), we’re encouraged by the momentum we’re seeing with government partners. This ARPA-E selection is one of several opportunities we’re pursuing across both the United States and Canada, including a pipeline of potential awards that are significantly larger in scale. We look forward to sharing additional funding updates in the near term.”

Led by Xanadu, in partnership with the University of Chicago, the three year project will focus on developing quantum algorithms to study key processes of defect formations in battery materials. These simulations will yield critical data essential for accelerating the development of batteries with higher energy densities and extended longevity.

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An ambitious goal of the project is to achieve a 100x reduction in runtime for these simulations compared to state-of-the-art classical methods, while maintaining high accuracy. To achieve this, Xanadu will develop specialized X-ray absorption spectroscopy and reaction rate algorithms, while University of Chicago material science experts will provide precise molecular structures and embedding models for simulations.

The potential impact of this research is significant. Beyond fast-tracking the development of practical high-energy-density batteries, the tools developed through this program will be designed for direct transferability to other high-value sectors essential to energy modernization, such as advancements in chemistry to support the nuclear sector, and key challenges in the production of ammonia and petrochemicals.

This partnership helps to position quantum computing as a cornerstone of materials innovation, demonstrating that fault-tolerant quantum platforms can solve the fundamental computational bottlenecks currently impeding novel energy technologies. Ultimately, this work aims to create a definitive roadmap for how quantum computing will underpin the future of global energy storage and industrial R\&D for decades to come.

For additional information about Xanadu and this project, please visit xanadu.ai

Mohib Ur Rehman

Mohib has been tech-savvy since his teens, always tearing things apart to see how they worked. His curiosity for cybersecurity and privacy evolved from tinkering with code and hardware to writing about the hidden layers of digital life. Now, he brings that same analytical curiosity to quantum technologies, exploring how they will shape the next frontier of computing.

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