Application of quantum simulations in hydrogen research
Quantum simulation of materials is one of the most important applications of quantum computers in the near future, as it makes comparatively moderate demands on the size and precision of the hardware. The AQUAS project implements and validates software tools for the quantum mechanical simulation of relevant materials for hydrogen production and efficiency enhancement of already operational catalysts. The focus is on algorithms that can already be used on current, relatively error-prone hardware.
Challenge and innovation
Fuel cells and electrolysers are becoming increasingly important for Germany as an industrial location, in particular due to the political goal of the energy transition. To achieve the necessary increases in efficiency, the electrochemical interface processes need to be investigated in greater detail. Quantum-chemical numerical calculations of atomic and molecular bonds are suitable tools for this. The bonds are mediated by electrons, which can exist in many different quantum states. However, the exponential number of possible quantum states can only be approximated on classical computers and requires a combination of different simulation techniques, which in turn limits the predictive power. The design of new catalysts and electrode structures is therefore only possible in constant comparison with complex experiments. Since quantum simulations with quantum computers, on the other hand, scale linearly with the system size, they can enable simulations that were previously unmanageable.
Due to this exponentially better scaling, in which the number of necessary Qubits grows linearly with the number of quantum states, simulation on quantum computers can bring considerable advantages in the simulation of electro-chemical interface effects, e.g. in oxygen catalysis. Currently, however, the gain in computing power through quantum computers is still limited to a few applications. Hybrid algorithms, in which classical computers and quantum computers are closely interlinked to simulate the catalysts, promise to combine the best of both worlds. This is done on the one hand by using variational quantum algorithms, but in particular also by methods that perform a so-called embedding and divide the material problem into subproblems, part of which must be solved on the quantum computer. Furthermore, these hybrid quantum simulations are to be supplemented by the use of quantum machine learning (QML) methods. The AQUAS project aims to implement all these methods in software tools for a more accurate description of electrolysis materials.
HQS Quantum Simulations GmbH (project coordination), DLR Institut für Softwaretechnologie, DLR Institut für Technische Thermodynamik, Universität Ulm, Fraunhofer IPA
January 2022 – December 2024
Total costs: € 3.5 million
Funding volume: € 2.7 million