Quantum computing may be the future, but it’s increasingly becoming part of one of the world’s most pressing problems: clean energy. In energy research laboratories and advanced materials facilities, there is a subtle but significant shift underway. Researchers are increasingly relying on quantum simulation techniques as classical computing strains to keep pace in understanding the intricate properties of next-generation materials for energy.
As the energy sector accelerates efforts to create superior batteries, scalable hydrogen technologies, long-duration energy storage and high-efficiency solar materials, they are running up against a reality: many of these issues are underpinned by quantum interactions that are difficult to model with classical high-performance computing. This is creating a computational bottleneck – and quantum computing is poised to solve it.
Overcoming the Computational Limit in Energy Materials
The performance of today’s energy storage systems – including lithium-ion batteries, new solid-state systems and beyond – relies on the interactions between electrons described by quantum mechanics. Simulating these interactions is crucial to understanding performance, stability and efficiency. But classical approaches suffer from exponential scaling with the number of electrons.
This was highlighted in a groundbreaking study by researchers from ETH Zurich published in the Proceedings of the National Academy of Sciences (PNAS), which showed that even powerful supercomputers are unable to provide an efficient solution for large many-electron systems (PNAS) Elucidating reaction mechanisms on quantum computers
For new battery technologies like lithium-sulfur, sodium-ion, metal-air and solid state electrolytes, such challenges inhibit innovation. Existing modeling techniques are simply not keeping up with the world’s energy needs.
On the other hand, quantum computers are designed to simulate quantum systems – and these are a perfect match for these challenges.
Theory to Early Applications
Over the past few years, quantum chemistry has entered the early stages of application. This was marked by the creation of the Variational Quantum Eigensolver (VQE) by Alán Aspuru-Guzik and his team. This method showed that quantum computers can calculate molecular energies to an accuracy impossible with classical computers (Nature Reviews Physics) The theory of variational quantum simulation
A Pivotal Year: 2015
A number of key factors brought quantum computing to the energy industry:
- Advent of Error-Corrected Quantum Computers
Advancements in logical qubits and fault tolerance – as discussed in the IBM Quantum Roadmap – have made quantum computations more stable and useful for chemistry studies.
- Advent of Mixed Quantum-Classical Workflows
Quantum services like Azure Quantum, AWS Bracket and IBM Quantum Cloud enable the integration of quantum algorithms with existing computing workflows, making quantum computing more accessible (Azure Quantum Chemistry).
- Speeding up Clean Energy Development
The International Energy Agency (IEA Clean Energy Materials Report) has stated that world decarbonization targets are outstripping R&D efforts, making accelerated material discovery even more vital.
Quantum Simulation in Action
Quantum simulation is no longer a theoretical pursuit, but is being used in a number of areas of clean energy research and development:
- Next-Generation Batteries
Quantum algorithms are being applied to study small molecular clusters in solid-state and lithium-sulfur batteries, revealing new insights into their instability that are missed by classical simulations.
- Hydrogen Storage and Fuel Cells
Scientists are using quantum techniques to investigate the adsorption behavior of metal-organic frameworks (MOFs) – a potential avenue for hydrogen storage.
- Carbon Capture Technologies
Quantum methods are also being used to gain insights into carbon dioxide binding with next-generation sorbents – a crucial component of carbon capture technologies.
- Solar Photovoltaics
Quantum chemistry is helping to better understand perovskite and organic solar materials (Quantum insights for organic solar cells), which may result in improved efficiency and stability.
Superconductors and Grid Innovation
Pioneering quantum models are also being applied to investigate electron pairing in unconventional superconductors – something that cannot be easily studied using classical methods.
These are real advances, rather than pipe dreams.
Quantum Capabilities in a State of Play
While promising, quantum computing is still in its infancy. It’s current capabilities include:
- Accurate simulation of small molecules and fragments
- Better predictions of electron movement in systems
- Pre-synthesis screening for new materials
- Risk of instability and inefficiency
- Reducing energy materials R&D time
However, limitations remain:
- Lack of simulation of entire battery systems
- Limited ability to model large molecules
- Lack of integrated end-to-end commercial processes
Today, quantum computing is best used as a research multiplier – to supplement and not substitute for classical computing and experimentation.
A New Engine for Energy Innovation
Quantum computing is taking energy innovation to the next level. In areas ranging from batteries to hydrogen, solar, carbon capture and grid technologies, the future of innovation will rely on materials whose characteristics are fundamental to quantum mechanics.
Existing computational approaches are struggling to keep up. By contrast, preliminary findings from quantum-based simulations hold the promise of a future in which the discovery of new materials will be an accelerated, more accurate and less experimental process.
Even though the world is fixated on artificial intelligence, the combination of quantum computing and energy research may end up having a greater, longer-term impact on society.
Conclusion
The path forward for clean energy development might not only lie in the laboratory but in the quantum simulation environment executing on ever-improving hardware. The materials that will comprise the energy system of 2040, be it batteries, solar cells, or carbon capture devices, might have their origins from advancements beyond the capabilities of classical computing.
Quantum computing is coming at an opportune time. For the energy transition, it couldn’t have come soon enough.
Author Bio
Sankalp Shrivastava is an enterprise architect and technology strategist that is aimed at transforming business processes by the use of modern architecture, data-driven design and platform innovation. Having a deep experience in the SAP ecosystems, cloud technology, and large-scale enterprise transformation, he works on the intersection of business strategy and technology to help organisations build scalable, secure, and future-ready systems.
His work has focused on balancing the business goal with the intelligent technology choices that allow businesses to run more efficiently as well as adapt to the highly dynamic digital environments. He is keen on how generative AI can be used to improve operational intelligence, decision-making, and accessing new sources of business value in complex enterprise contexts.
Besides that, he discusses the emerging potential of quantum computing, especially its potential to transform in the long-term optimisation, advanced analytics, and enterprise problem-solving. He seeks to fill the gap between groundbreaking innovation and its application through his writing and research.
