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Tensor AI supports QCMineral | QUADRANT in the quantum-assisted development of metal oxides with redox function

15. January 2026
Tensor AI has been awarded the contract in the QUADRANT tender for research and development in our materials research project QCMineral.

Together with the DLR research team, and with Fraunhofer IAO and Fraunhofer IPA as subcontractors, the quantum start-up is developing hybrid quantum-classical simulation methods for us for the precise ab initio simulation of perovskite redox materials. Promising industrial applications include energy storage and the synthesis of solar fuels.

Time-consuming development work

Traditional material development is a laborious and time-consuming task in which hundreds of material samples are produced, analysed and usually discarded. Computer-aided material development promises to greatly accelerate this process, as the properties of new materials can be precisely calculated in advance before they have to be laboriously produced and analysed in the laboratory. However, density functional theory (DFT) does not provide the required chemical accuracy for correlated materials such as redox oxides. This is where quantum computers with their innovative algorithms promise a breakthrough.

In the QCMineral project, the DLR Institute of Future Fuels and the DLR Institute of Frontier Materials are investigating this potential on Earth and in space by developing special redox materials for energy storage and the thermochemical production of liquid fuels and hydrogen from water, carbon dioxide and solar energy. New materials designed with the help of quantum computers could, for example, drastically increase the efficiency of fuel production or the energy densities of new energy storage systems: a prerequisite for the industrial and social utilisation of these pioneering energy technologies.

In addition to redox materials, QCMineral is also working on innovative glass applications and was looking for companies for the development, implementation and evaluation of atomistic material simulations of glassy and glass-ceramic SiO2-based functional materials using quantum computers. The public tender for this has been finalised.

Intensive technology transfer

The DLR Institute of Future Fuels has been working for decades on the production of fuels from sunlight, air and water. In some projects, progress can be directly reflected in QCMineral.

SolarGrAm – Solar Green Ammonia Production: develops a database for redox materials for air separation (separation of nitrogen and oxygen, another application of solar-thermal redox cycles). The high-purity nitrogen is required for ammonia synthesis.

Sun-to-LIQUID II – Develops reactors with 3D-printed redox materials for the production of liquid fuels. The next stage on the way to industrial application. Target 15% efficiency.

SOLHYKO – Reactor optimisation, demonstration operation, technology comparison for solar thermochemical processes for the production of hydrogen and synthesis gas and further processing into liquid fuels.

Porotherm-Solar – Open-pored monolithic perovskite structures as hybrid thermal storage units for concentrated solar energy. Materials and components for storage systems for solar-thermal power plants (for night-time operation).

HERCULES – High-Temperature Thermochemical Heat Storage Powered by Renewable Electricity for Industrial Heating Applications. Surplus green electricity from power peaks is stored as heat in metal oxides for later use in industrial processes. Heat can be stored better than electrical energy.

KISMOR – Continuously operated solar monolithic receiver reactor. Reactor development for solar-thermal cycle processes with redox materials; based on Sun-to LIQUID.

ABraytCSPfuture – AirR-Braytoh Cycle Concentrated Solar Power Future Plants via Redox Oxides-Based Structured Thermochemical Heat Exchangers/Thermal Boosters. Heat storage for controllable solar thermal power plants to bridge clouds and night. The chemical energy stored in the hot redox material serves as a booster in addition to the sensible heat because it is only released when required by reaction with atmospheric oxygen and compensates for the temperature loss during storage.

SolarFuels – Synthetic fuels from sunlight. Construction of an industrial pilot plant for the production of synthetic fuels using solar reforming and a German value chain for the overall technology

The application of advanced simulation methods, including tensor networks, and the use of quantum computers can provide a decisive advantage in the research of new materials. Tensor networks enable structured, controllable and transparent data processing and thus make an important contribution to comprehensible simulations and explainable AI in a highly complex physical-chemical field of application.

Thanks to their flexibility, tensor networks can be used on both conventional high-performance computers and future quantum hardware. They therefore form a central bridge for hybrid computing, in which calculations can be scaled specifically between classical and quantum-based hardware in order to optimally balance accuracy, efficiency and resources.

Tensor AI Solutions

Tensor AI Solutions is a high-tech AI company focussing on explainable artificial intelligence. The company develops cross-hardware solutions for safety-critical applications, including in the defence, robotics and manufacturing sectors. The specially developed AI technology based on tensor networks enables transparent, controllable and energy-efficient AI systems without a black box.

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