Quantum computing for materials research

In our research projects, we address the key challenges involved in making quantum computing usable for materials research

Quantum computing has great potential for materials research, especially in the simulation of complex quantum mechanical systems such as molecules or solids. In our research projects, we address the key challenges involved in making quantum computing usable for materials research.

• Error rates and decoherence: Current quantum computers (especially NISQ devices – Noisy Intermediate-Scale Quantum) still have high error rates. Quantum bits (qubits) are very susceptible to interference from the environment, which limits their useful life (coherence time).
• Limited number of qubits: Many relevant materials systems require hundreds of thousands to millions of qubits for realistic modeling. Current quantum computers usually only have a few dozen to a few hundred qubits.
• Efficient algorithms: Many quantum chemical problems require special algorithms (e.g., Variational Quantum Eigensolver – VQE) that must be tailored to current hardware. Many of these algorithms are not yet mature or scale poorly with system size.
• Error correction and mitigation: Complete error correction is currently not feasible because it requires enormous additional qubit resources. Initial techniques for errormitigation exist, but these are not yet sufficient for precise simulations.
• Hybrid approaches: Combining classical and quantum mechanical computing methods (e.g., in VQE) is complex and requires a great deal of expertise. Optimization processes are often slow or prone to local minima.
• Mapping real-world materials problems: Converting actual materials into a form that a quantum computer can process (e.g., second quantization, Hamiltonians) is not trivial. Many systems contain strongly correlated electrons or complex interactions that are difficult to model.

To tackle these challenges together with you, we calculate the properties of your materials systems and develop the appropriate simulation methods for them. Our aim is to create a sound understanding of mechanisms with a reasonable amount of computing power. This opens up new possibilities for you in terms of materials design.

Pairing classic computers with Quantum hardware

In principle, a quantum computer, due to its mode of operation, offers ideal prerequisites for mapping quantum chemical processes in complex functional materials. However, the currently available hardware is still inferior to the mathematically ideal performance of a quantum computer. In particular, the decoherence of the system, i.e. the loss of quantum properties due to interference during the calculation time, is a serious problem. This severely limits the universal applicability of a quantum computer at present. The technology is developing rapidly, however, so that in a few years' time, much more powerful and fault-tolerant systems will be available.

We are researching how best to use the quantum hardware available today to address material modeling issues in the most effective manner and are developing specific expertise for hybrid simulation methods. In these hybrid methods those aspects that can be reliably calculated on conventional computers are treated with established methods of density functional theory.

The part of the problem, which classically is the most demanding to solve in terms of computational resources, is mapped to an effective auxiliary model and calculated using the quantum computer. An iteration loop between the two computer systems then provides the overall solution (Figure 1). The aim of our research work is to develop these type of effective models that can be implemented on today's quantum computers.

Our findings form a basis for future software with transferable quantum algorithms.

Materials simulation for batteries and fuel cells

The successful expansion of electromobility requires small and lightweight energy storage systems with high energy densities and performance as well as efficient energy converters. The material and structure of the electrodes determine the electrical function of batteries and fuel cells and ultimately their service life.

In the joint project "Quantum computer material design for electrochemical energy storage and conversion with innovative simulation techniques" (QuESt), we are working with project partners at the German Aerospace Center (DLR) to test new approaches to material design. Using the IBM quantum computer, we are investigating the interactions between atoms and electrons of battery electrodes and in fuel cell catalysts. Such functional materials usually contain chemical elements with strongly correlated electrons, in particular transition metals. Their physically correct description requires numerically complex procedures. These provide an optimal testbed for the development of the hybrid simulation methods described above, using currently available quantum hardware. Within the scope of QuESt, we are investigating in particular the phase, defect and reaction properties of oxide compounds containing manganese, iron, cobalt and nickel with perovskite crystal structure types.

Alternative technology for quantum registers

The IBM quantum computers use superconductor-based circuits as elementary qubits. Shielding these as well as possible against external interference requires a great deal of technological effort. The quantum processor chip is therefore cooled to temperatures close to absolute zero and shielded against electric and magnetic fields. An alternative approach to the realization of qubits, technologically still in its infancy, involves the use of certain isolated crystal defects in solids. The most promising candidate for this is the nitrogen-vacancy center (NV center) in the diamond crystal, which exhibits its quantum properties even at room temperature for an astonishingly long time.

In the joint project "Modeling and simulation of qubit registers from chains of NV centers on dislocations in diamond" (SiQuRe), we are working together with partners at the Albert-Ludwigs-University of Freiburg and the University of Ulm on the modeling and simulation of solid-state defect-based qubit registers. The research project deals with models and computer simulation methods concerning theoretical quantum physics and deals with the question to what extent qubits addressable NV centers in diamond are periodically arranged along linear structural defects and can be used for the construction of future quantum computers.

Reference Projects

Materials Design for Electrochemical Energy Storage and Conversion Devices Using Innovative Simulation Techniques: QuESt and QuESt+

In the QuESt and QuESt+ projects, Fraunhofer IWM, in collaboration with the German Aerospace Center (DLR) and the Helmholtz Institute Ulm, is developing quantum computing algorithms specifically tailored to the behavior of electrons and ions at interfaces in batteries, fuel cells, and electrolyzers - that is, processes whose precise simulation using classical methods continues to face fundamental limitations.

In the first project, QuESt, it was demonstrated that electrochemical processes can be modeled predictably on IBM quantum computers at both the atomic and macroscopic levels, particularly by embedding quantum algorithms as solvers in Dynamical Mean-Field Theory (DMFT) calculations for strongly correlated electron systems in solid-state electrodes.

The follow-up project, QuESt+, further developed these approaches: error mitigation strategies for current NISQ hardware were systematically investigated and implemented, the algorithmic description was extended to electrochemical reactions in electrolytes, and the solution of partial differential equations for the macroscopic modeling of electrochemical processes was transferred to the quantum computer.

The added value lies in accelerated simulation-based materials design for electrochemical energy storage and conversion devices, through more precise predictions of electron and ion transport and better estimation of degradation mechanisms. 

Project profile: QuESt: IBM quantum computers – materials design for electrochemical energy storage and conversion devices using innovative simulation techniques – Fraunhofer IWM

Project profile: QuESt+: IBM quantum computers – Materials design for electrochemical energy storage and conversion devices using innovative simulation techniques – Fraunhofer IWM

Publications

Variational quantum-algorithm based self-consistent calculations for the two-site DMFT model on noisy quantum computing hardware,  J. Ehrlich, D. F. Urban, and C. Elsässer, J. Phys.: Condens. Matter 37, 225901 (2025) Link

Baden-Württemberg Quantum Computing Competence Center 2024 and 2025

As part of the Baden-Württemberg Competence Center for Quantum Computing, Fraunhofer IWM is working to develop quantum algorithms for materials science problems (KQCBW24). At its core, the focus is on materials where classical methods such as density functional theory reach their fundamental limits: strongly correlated electron systems, such as those found in fuel cell electrodes, magnetic storage architectures, catalysts and battery materials. To address this, hybrid workflows have been developed that embed quantum algorithms as solvers within existing DFT+DMFT simulation chains on classical HPC systems.

In the follow-up project KQCBW25, this scope is being expanded: In addition to electronic structure, the project now also addresses partial differential equations, such as crack propagation in solids, charging and discharging processes in batteries, and fluid dynamics - in each case with resource estimates and systematic comparisons to classical FEM/FDM methods. In addition, Fraunhofer IWM contributes its expertise in the atomistic modeling of qubit materials by quantifying the influence of crystal defects on NV color centers in diamond.

What both projects have in common is the commitment not to promise a quantum advantage, but to test for it on a materials-system-specific basis. 

Project profile: Baden-Württemberg Quantum Computing Competence Center - Fraunhofer IWM

Project profile: Baden-Württemberg Quantum Computing Competence Center 2025 to 2027 - Fraunhofer IWM

Quantum Algorithm Development, Benchmarking, and Resource Estimation for Materials Simulation with User Benefits on NISQ Quantum Computers, QUBE

The development of new energy storage and conversion devices requires a deep understanding of the electronic properties of the functional materials used. Many of these materials, particularly transition-metal oxides with a perovskite structure (e.g., ternary ferrates and cobaltates), exhibit strongly correlated electronic states, the quantitative simulation of which reaches fundamental limits using established classical methods such as density functional theory (DFT). Even advanced embedding methods such as Dynamical Mean Field Theory (DMFT) require significant approximations and immense computational effort on classical high-performance computers, which limits the accuracy of predictions and thus the speed of materials development. The QUBE joint research project is developing hybrid quantum-classical simulation methods that shift the most numerically demanding part of DMFT - the calculation of the Green'schen function for the correlated subproblem - to a quantum computer, thereby achieving a quantum advantage for materials simulation.

Project profile: Quantum Algorithm Development, Benchmarking and Resource Estimation for Materials Simulation with User Benefits on Noisy Intermediate-Scale Quantum (NISQ) Quantum Computers - Fraunhofer IWM

Quantum Computing for the Simulation of UV-Induced Polymer Degradation, QPolyDeg

One of the greatest challenges in the use of polymers is aging caused by UV radiation: it leads to embrittlement, discoloration, and the loss of mechanical properties, resulting in high costs due to materials failure, maintenance, and premature replacement. A deep understanding of the molecular degradation mechanisms is key to developing longer-lasting and more sustainable plastic products - but the underlying quantum chemical processes cannot be adequately modeled using classical simulation methods. This is where the QPolyDeg joint research project comes in: It - for the first time - harnesses the power of quantum computing to simulate UV-induced polymer degradation at the fundamental quantum-mechanical level.

Through the development of novel, non-variational quantum algorithms, the project aims to calculate energy spectra of fermionic systems that are virtually inaccessible to classical computers. The results will enable a profound understanding of aging processes and open new avenues for the targeted development of longer-lasting polymer materials.

Project profile: Quantum Computing for the Simulation of Ultraviolet (UV)-Induced Polymer Degradation - Fraunhofer IWM

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