Quantum computing just might save the planet
(McKinsey) Quantum computing could revolutionize the fight against climate change, transforming the economics of decarbonization and becoming a major factor in limiting global warming to the target temperature of 1.5°C according to this recent report from McKinsey. IQT-News summarizes the five areas designate in the Climate Report as key for decarbonization that can pave the way to a net-zero economy.
The use cases are summarize below. Quantum-enabled technologies may make it possible to eliminate more than 7 gigatons of CO2 equivalent (CO2e) from the atmosphere a year, compared with the current trajectory.
Batteries are a critical element of achieving zero-carbon electrification. They are required to reduce CO2 emissions from transportation and to obtain grid-scale energy storage for intermittent energy sources such as solar cells or wind.
Recent research 3 has shown that quantum computing will be able to simulate the chemistry of batteries in ways that can’t be achieved now. As a result, we could create batteries with 50 percent higher energy density for use in heavy-goods electric vehicles, which could substantially bring forward their economic use.
Adapting industrial operations
Many parts of the industry produce emissions that are either extremely expensive or logistically challenging to abate.
Cement is a case in point. During calcination in the kiln for the process of making clinker, a powder used to make cement, CO2 is released from raw materials. This process accounts for approximately two-thirds of cement emissions.
Alternative cement-binding materials (or “clinkers”) can eliminate these emissions, but there’s currently no mature alternative clinker that can significantly reduce emissions at an affordable cost.
There are many possible permutations for such a product, but testing by trial and error is time-consuming and costly. Quantum computing can help to simulate theoretical material combinations to find one that overcomes today’s challenges—durability, availability of raw materials and efflorescence (in the case of alkali-activated binders). This would have an estimated additional impact of 1 gigaton a year by 2035.
Decarbonizing power and fuel: Solar cells
Solar cells will be one of the key electricity-generation sources in a net-zero economy. But even though they are getting cheaper, they still are far from their theoretical maximum efficiency. Today’s solar cells rely on crystalline silicon and have an efficiency on the order of 20 percent. Solar cells based on perovskite crystal structures, which have a theoretical efficiency of up to 40 percent, could be a better alternative.
Quantum computing could help tackle these challenges by allowing for precise simulation of perovskite structures in all combinations using different base atoms and doping, thereby identifying higher efficiency, higher durability, and nontoxic solutions.
Hydrogen is widely considered to be a viable replacement for fossil fuels in many parts of the economy.
Before the 2022 gas price spikes, green hydrogen was about 60 percent more expensive than natural gas. But improving electrolysis could significantly decrease the cost of hydrogen.
Quantum computing can help model the energy state of pulse electrolysis to optimize catalyst usage, which would increase efficiency of hydrogen. Quantum computing could also model the chemical composition of catalysts and membranes to ensure the most efficient interactions. And it could push the efficiency of the electrolysis process up to 100 percent and reduce the cost of hydrogen by 35 percent. If combined with cheaper solar cells discovered by quantum computing (discussed above), the cost of hydrogen could be reduced by 60 percent.
Ammonia is best known as a fertilizer, but could also be used as fuel, potentially making it one of the best decarbonization solutions for the world’s ships. Today, it represents 2 percent of total global final energy consumption.
For the moment, ammonia is made through the energy-intensive Haber-Bosch process using natural gas.
nnovation has reached a stage where it might be possible to replicate nitrogen fixation artificially, but only if we can overcome challenges such as enzyme stability, oxygen sensitivity, and low rates of ammonia production by nitrogenase. The concpt works in the lab but not at scale.
Quantum computing can help simulate the process of enhancing the stability of the enzyme, protecting it from oxygen and improving the rate of ammonia production by nitrogenase. That would result in a 67 percent cost reduction over today’s green ammonia produced through electrolysis, which would make green ammonia even cheaper than traditionally produced ammonia. Such a cost reduction could not only lessen the CO2 impacts of the production of ammonia for agricultural use but could also bring forward the breakeven for ammonia in shipping—where it is expected to be a major decarbonization option—forward by ten years.
Ramping up carbon capture and carbon sequestration activity
Carbon capture is required to achieve net zero. Both types of carbon capture—point source and direct—could be aided by quantum computing;
1) Point-source capture
Point-source carbon capture allows CO2 to be captured directly from industrial sources such as a cement or steel blast furnace. But the vast majority of CO2 capture is too expensive to be viable for now, mainly because it is energy intense.
One possible solution: novel solvents, such as water-lean and multiphase solvents, which could offer lower-energy requirements, but it is difficult to predict the properties of the potential material at a molecular level.Quantum computing promises to enable more accurate modeling of molecular structure to design new, effective solvents for a range of CO2 sources, which could reduce the cost of the process by 30 to 50 percent.
2) Direct-air capture
Direct-air capture, which involves sucking CO2 from the air, is a way to address carbon removals. While the Intergovernmental Panel on Climate Change says this approach is required to achieve net zero, it is very expensive (ranging from $250 to $600 per ton a day today) and even more energy intensive than point-source capture.
Adsorbents are best suited for effective direct-air capture and novel approaches, such as metal organic frameworks, or MOFs, have the potential to greatly reduce the energy requirements and the capital cost of the infrastructure. MOFs act like a giant sponge—as little as a gram can have a surface area larger than a football field.
Quantum computing can help advance research on novel adsorbents such as MOFs and resolve challenges 4 arising from sensitivity to oxidation, water, and degradation caused by CO2.
Reforming food and forestry
Twenty percent of annual greenhouse-gas emissions come from agriculture—and methane emitted by cattle and dairy is the primary contributor (7.9 gigatons of CO2e, based on 20-year global-warming potential).
Research has established that low-methane feed additives could effectively stop up to 90 percent of methane emissions. Yet applying those additives for free-range livestock is particularly difficult.
An alternative solution is an antimethane vaccine that produces methanogen-targeting antibodies. This method has had some success in lab conditions, but in a cow’s gut—churning with gastric juices and food—the antibodies struggle to latch on to the right microbes. Quantum computing could accelerate the research to find the right antibodies by precise molecule simulation instead of a costly and long trial-and-error method.
Additional use cases
There are many more ways that quantum computing could be applied to the fight against climate change. Future possibilities include identification of new thermal-storage materials, high-temperature superconductors as a future base for lower losses in grids, or simulations to support nuclear fusion. Use cases aren’t limited to climate mitigation, but can also apply to adaptation, for example, improvements in weather prediction to give greater warning of major climatic events.
Sandra K. Helsel, Ph.D. has been researching and reporting on frontier technologies since 1990. She has her Ph.D. from the University of Arizona.