Quantum simulation of nitrogen catalysts, energy storage materials, and CO2 capture. How quantum computers will be used to tackle climate change.
🌍 The climate crisis needs new tools
Climate change is perhaps the greatest challenge of the 21st century. Despite decades of research, classical computational models fail to accurately simulate the complex chemical reactions that occur at the molecular level — precisely where the solutions for cleaner energy, more efficient fertilizers, and effective CO₂ capture are hidden.
Quantum computers promise to change this dynamic. Richard Feynman proposed in 1982 that nature, which operates quantum mechanically, could be effectively simulated only by machines that use the same quantum laws. Today, this idea is becoming reality. In June 2023, IBM announced that a quantum computer produced better results than a conventional supercomputer for a physics problem, publishing the findings in Nature.
⚗️ Nitrogen's triple bond — the Achilles' heel of industry
The Haber-Bosch process, discovered in the early 20th century by Fritz Haber and Carl Bosch (Nobel Prize in Chemistry 1918 and 1931 respectively), forms the basis of global ammonia production. The reaction N₂ + 3H₂ → 2NH₃ requires temperatures of 400–550°C and pressures of 150–250 bar, primarily because the triple bond of nitrogen (N≡N) is exceptionally strong.
The result? Ammonia production consumes 1–2% of global energy and is responsible for approximately 3% of CO₂ emissions. Vaclav Smil called the process the “detonator of the population explosion” — nearly 50% of the nitrogen in human tissues originates from it.
The critical step that determines the reaction rate is the dissociation of the nitrogen molecule on the surface of the iron catalyst, at the so-called C7 sites of the Fe(111) surface. Classical computers struggle to simulate this catalysis process with full accuracy, because the electrons in transition metals exhibit strong quantum correlations.
Quantum computers could simulate catalysis mechanisms at the atomic level, paving the way for new catalysts that would operate at lower temperatures and pressures. Wikipedia already notes that quantum simulation of the Haber-Bosch process is expected to be one of the first practical applications of quantum computers.
🔬 Quantum chemistry — simulating molecules differently
Quantum chemistry is a branch of physical chemistry that applies quantum mechanics to chemical systems. From Walter Heitler and Fritz London (1927), who first applied quantum laws to the hydrogen molecule, to modern methods like Density Functional Theory (DFT) and Coupled Cluster, computational chemistry has made tremendous progress.
However, there is a fundamental scaling problem: computation time increases exponentially with the number of electrons. Even DFT, which scales “only” as n³, cannot handle complex molecules with chemical-quality accuracy. A catalyst molecule with 50–100 heavy atoms requires trillions of calculations on a classical computer.
The Variational Quantum Eigensolver (VQE) and Quantum Phase Estimation are algorithms specifically designed for quantum computers that can find the ground state energy of a molecule much more efficiently. This means that catalysts, battery electrolytes, and CO₂ capture materials could theoretically be designed on a computer before being built in the laboratory.
🔋 Next-generation batteries and energy storage
The transition to renewable energy sources critically depends on storage. Solar and wind energy are produced irregularly — they need batteries that store vast amounts of energy efficiently and economically.
Lithium-ion batteries dominate today but have physical limits in energy density. The search for new solid-state electrolytes, lithium-sulfur cathodes, and silicon anodes requires understanding quantum interactions at the atomic scale. Classical computers can only simulate simplified models of these systems.
Quantum computers could fully simulate the electrochemical reactions inside a battery, helping design materials with higher energy density, longer lifespan, and lower cost. Optimization of an electrolyte at the quantum level could reduce energy losses by 20–30%.
🏭 Carbon dioxide capture and storage
Carbon Capture and Storage (CCS) technology is considered essential for achieving net-zero emissions targets. Materials such as Metal-Organic Frameworks (MOFs) and zeolites can capture CO₂ from industrial emissions or even directly from atmospheric air.
However, the design space for these materials is enormous — there are millions of possible combinations of metals, organic linkers, and structures. Quantum simulation can accurately predict how a CO₂ molecule interacts with the active sites of a MOF, enabling targeted design of materials with optimal selectivity and capture capacity.
In a recent publication (2024) in the Journal of the American Chemical Society, researchers presented a flexible phosphonate-based MOF that achieves enhanced cooperative ammonia capture, demonstrating that molecular design leads to significant performance improvements.
📊 Climate models and quantum optimization
Beyond chemistry, quantum computers can improve climate models. Today’s General Circulation Models (GCMs) use grids of tens of kilometers — too coarse to capture local phenomena such as cloud formation, ocean currents, or vegetation. Quantum computing could dramatically increase the resolution of these models.
Additionally, quantum optimization algorithms (Quantum Annealing, QAOA) can be applied to electrical energy network problems, optimizing renewable energy distribution, minimizing losses, and incorporating storage in real time. John Preskill, in a 2018 publication in Quantum Journal, described this era as NISQ (Noisy Intermediate-Scale Quantum) — a transitional phase where even imperfect quantum computers can deliver practical results.
🚀 Where we stand today and what awaits us
Today’s quantum computers are still in their early stages. Decoherence — the loss of quantum information due to interaction with the environment — remains the greatest challenge. Qubits must be cooled to 20 millikelvin — colder than outer space — to function.
However, progress is rapid. In December 2023, a Harvard team published in Nature the first logical quantum processor based on reconfigurable atom arrays, supported by DARPA. Microsoft is investing in topological qubits, while companies like IBM, Google, and QuEra compete for quantum advantage in practical problems.
Quantum simulation of catalysts is expected as one of the first applications to demonstrate practical value. If a quantum computer can design a nitrogen catalyst that operates at room temperature, the energy savings would be enormous — we’re talking about reducing billions of tons of CO₂ annually.
"Nature isn't classical, dammit, and if you want to make a simulation of nature, you'd better make it quantum mechanical, and by golly it's a wonderful problem, because it doesn't look so easy."
Richard Feynman, 1982The challenge remains enormous, but the combination of quantum computing, artificial intelligence, and materials science creates a triangle of innovation that could transform our energy infrastructure. Climate change may ultimately find its adversary in a machine that operates precisely by the same laws that govern nature.