Fraunhofer IPA: Researching the key components for tomorrow’s energy storage systems with quantum computers

In this project, the Fraunhofer Institute for Manufacturing Engineering and Automation IPA is working on two complementary areas in a subcontract. The work aims to understand the practical requirements of quantum hardware for modeling realistic materials and predicting performance for energy storage and conversion applications.

On the one hand, the researchers are using Density Matrix Embedding Theory (DMET) to derive accurate Hamiltonian models that capture the highly correlated electronic behavior in redox materials. These models form the basis for state-of-the-art quantum and tensor network simulations.

On the other hand, they evaluate the extent to which quantum algorithms can be used to calculate the ground state energy of these complex systems. By contributing its expertise as a subcontractor of Tensor AI Solutions, Fraunhofer IPA, together with the Fraunhofer Institute for Industrial Engineering IAO as flaQship (Fraunhofer Lab for Application-Oriented Quantum Computing Stuttgart-Heilbronn), is helping to build a bridge between quantum computing and materials science and pave the way for more efficient, sustainable energy solutions.

Fraunhofer lab flaQship supports the project with quantum-based material simulation

The high-tech company Tensor AI Solutions was commissioned by the German Aerospace Center (DLR) for the QCMineral | QUADRANT project as part of the DLR Quantum Computing Initiative (DLR QCI). The aim of the research and development project is to simulate redox materials in order to generate and store energy efficiently. Tensor AI Solutions is contributing its expertise in tensor network-based AI and quantum simulation and is coordinating the project on the industrial side. The project is being implemented with the involvement of Fraunhofer IAO and Fraunhofer IPA, which are contributing their expertise in material simulation and quantum computing as subcontractors. On the client side, the project is being carried out at the DLR Institute of Materials Physics in Space and the DLR Institute of Future Fuels.

QCMineral is a project of the DLR Quantum Computing Initiative and is made possible with funding from the Federal Ministry of Research, Technology and Space (BMFTR). Redox materials play a central role in the efficient conversion and storage of energy in thermochemical cycles. The specific material design determines how efficiently heat – for example from concentrated solar radiation or industrial waste heat – can be converted into chemical energy. The evaluation and optimization of these materials requires high-precision calculations of quantum mechanical effects, which are only possible to a limited extent with existing simulation methods such as density functional theory.

Quantum computing as a central simulation method

The use of advanced simulation methods, including the use of quantum computers and tensor networks, 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.

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Further links

👉 www.ipa.fraunhofer.de  

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