Qarakal Quantum And Quantum Elements Receive BIRD Foundation Grant For Quantum Computing Innovation With a $2.4 Million Budget

Insider Brief

• Quantum Elements and Qarakal Quantum were selected by the BIRD Foundation for a $2.4 million project to develop a quantum simulation platform for chemical reactions on material surfaces.
• The collaboration will combine Qarakal’s superconducting quantum hardware with Quantum Elements’ digital-twin software and error-management tools to jointly optimize hardware and chemistry workflows.
• The companies aim to build a validated prototype, benchmark chemistry models and quantum algorithms to investigate how quantum computing could complement existing catalyst simulation methods.

PRESS RELEASE — Quantum Elements and Qarakal Quantum today announced they have been selected by the Israel-U.S. Binational Industrial Research and Development (BIRD) Foundation to jointly develop a quantum simulation platform for understanding and designing the chemical reactions that occur on material surfaces.

The project, one of seven approved by the BIRD Foundation, has a budget of $2.4 million.

The project will combine Qarakal Quantum’s modular superconducting quantum hardware and hardware-software co-design approach with Quantum Elements’ software for advancing fault-tolerant quantum computing, using AI-driven co-design, error suppression, error correction and decoders. 

Together, the companies will work toward a validated prototype capable of taking industrially relevant catalyst problems and turning them into quantum-ready computational workflows. Heterogeneous catalysis is essential to industries ranging from energy and chemicals to advanced materials, with catalytic processes involved in the manufacture of an estimated 80–90% of chemical products. The scale of these industries is significant — according to a MarketLine study, the global chemical processing industry generates between $5 and $6 trillion annually. Reactions occurring on the surface of catalysts play a central role in processes such as clean hydrogen production, CO₂ conversion, nitrogen-fixation chemistry, hydrocarbon processing, and the performance and degradation of advanced coatings.

Today, these systems are studied extensively using high-performance computing and methods such as density functional theory. These techniques are powerful, but problems involving strong electronic correlation, surface defects, transition-metal active sites, and complex bond-breaking pathways can necessitate significant computational approximation. The Qarakal–Quantum Elements project will investigate how quantum computing can complement existing tools.

“Our architecture is modular by design and tailorable for real-world workloads — that’s what makes this collaboration work,” said Dr. Nissan Maskil, CEO and co-founder of Qarakal Quantum. “Quantum Elements’ digital twins can model each module in detail, so we can make smart design decisions before we optimize the hardware. As our systems scale, their tools scale with them. Catalyst chemistry gives us meaningful problems to solve, and an opportunity to help industry with advanced reactions that are very hard to simulate today.”

Rather than treating quantum chemistry as an algorithm that runs independently of the underlying machine, the project will jointly optimize multiple layers of the computing stack. Quantum Elements’ digital-twin technology will model the behavior and noise environment of Qarakal’s superconducting system, supporting decisions around compilation, calibration, pulse-level execution, error suppression, and algorithm design before limited quantum hardware time is used.

“Useful quantum applications cannot be developed in isolation from the hardware that has to run them,” said Izhar Medalsy, Co-Founder and CEO of Quantum Elements. “Catalyst discovery gives us an opportunity to apply our quantum digital-twins and physics AI capabilities across the full path from physical device behavior to an industrial chemistry workflow.”

The collaboration is designed to produce benchmark chemistry models and quantum algorithms with demonstrations and API outputs intended for chemists and materials engineers. The companies ultimately envision the work supporting a broader quantum-enabled simulation platform for industrial catalyst and materials development. 

Potential future users include catalyst manufacturers, specialty-materials companies, chemical suppliers and industrial R&D organizations that already rely on computational screening, HPC and laboratory experimentation.