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Improving Battery Chemistry with Quantum Computing

The most expensive part of an electric car is typically the battery pack. According to a 2020 study by Oliver Wyman for the Financial Times, the batteries alone make up almost 40% of the total production cost of a battery electric vehicle (BEV), which also keeps their overall costs higher: it still costs about 45% more to produce a BEV than an equivalent combustion-driven car.

Much of this cost comes from the materials used to make the batteries. Every battery has a cathode that does most of the heavy lifting when it comes to the storage and release of energy, and this cathode is made of rare metals like lithium, nickel, and cobalt that must be mined from the earth and intensively refined to high purity before they’re able to be put to use. To pack in more energy, more complex combinations incorporating even rarer metals are often used.

To help meet growing demand for electric vehicles while staying cost-efficient, nearly every automaker is investing heavily in battery chemistry research, looking for battery materials that are cheaper and more sustainable to source and produce.

Beyond cost, there are a variety of other reasons to find better battery materials. Improving the energy density—the amount of power a fully-charged battery can hold—would allow for increased range and greater flexibility as to where batteries are placed within the vehicle. Improving the number of charge and discharge cycles the batteries can go through makes for longer-lived vehicles, and allows drivers to avoid the dreaded and expensive “battery swap” that many EV early adopters are currently experiencing. Improvements are also possible in charging speed, heat production during discharge, reliability, flammability and safety, and more.

This intensive research has paid off. The total price for an electric vehicle’s battery pack has fallen by almost 90% since 2010, according to Bloomberg NEF. But prices still need to come down even further, to about $100 per kilowatt-hour, to become price-competitive with combustion cars.

Yet finding new battery chemistry—or improving the architectures we already have—is hard work. You have to understand how two molecules will interact at a very deep level: if they react, how quickly they react, what byproducts are produced, and how the reaction might be tuned with the addition of other materials like electrolytes. The oldest way of searching for potential molecules is the simplest: synthesizing compounds in a wet lab and seeing how they perform.

Physically testing molecules is, of course, both slow and expensive, so for much of their research, battery chemists now turn to computers. But classical computers are not well-suited for modeling quantum behaviors. Fully solving the Schrödinger equation for even a modestly-sized molecule like lithium dioxide is impossible, so chemists resort to computational techniques that rely on lossy (and still computationally intensive) tricks like the Born-Oppenheimer approximation. This limits the accuracy of the simulations produced, and while it helps limit the wet lab work to the most promising candidates, a great deal of the “real” understanding still happens when these compounds are actually synthesized.

So many automakers, including Daimler, Toyota and now Hyundai are turning to quantum computing as an accelerator for battery research. IonQ is partnering with Hyundai on their initiative to develop new variational quantum eigensolver (VQE) algorithms to study lithium compounds and their chemical reactions involved in battery chemistry, a key element of Hyundai’s Strategy 2025 vision to transition their organization into a smart mobility solution provider, including the sale of 560,000 EVs per year and a lineup of twelve or more battery electric vehicle models by the middle of the decade.

Quantum computing is an exciting enabler for chemistry-based problems like batteries because quantum computing was, in a sense, made to solve chemistry problems. In his now-famous 1981 talk at MIT’s 1st Conference on Physics and Computation, Richard Feynman proposed what we now call universal quantum computing specifically because it would be good at solving problems of quantum physics and therefore chemistry, explaining that an exact simulation of a quantum-mechanical phenomenon (which these chemical interactions are) can only be successfully performed with a quantum mechanical system. Or, to put it in his more colorful language, “nature isn’t classical, dammit! and if you want to make a simulation of nature, you'd better make it quantum mechanical.”

How we actually go about doing that is by using one quantum system (our quantum bits) to simulate another (battery chemistry) using quantum circuits, allowing us to use techniques such as a VQE algorithm to find something out about that system. In the case of VQE, we’re finding the system’s ground-state energy, which is the most critical piece of information for understanding how one molecule will interact with other molecules. This technique provides more accuracy than a classical approximation because it can fully solve for all atomic nuclei and electrons in the system, something that may never be possible with classical computational techniques, which do not allow for this direct mapping.

Teaming up with a partner like Hyundai is an ideal collaboration for IonQ. They bring deep expertise on these battery chemistry problems and their constituent molecules, and we bring our industry-leading hardware and long history of innovation in quantum chemistry, including demonstrating an end-to-end pipeline for simulating large molecules, and simulating water. Together, we believe we can continue to advance the state of the art, starting with molecules like lithium oxide—already a leap forward in quantum chemistry—and expanding to even larger and more complex compounds and interactions as our techniques and hardware capacity improve, potentially enabling long-sought-after breakthroughs such as solid-state and “post-lithium” battery technologies.

Ultimately, these tiny quantum simulations stand to have an impact on some of the largest problems we face. Reducing our reliance on fossil fuels for transportation is a major part of combatting man-made climate change, and it can’t be done without cost-effective, efficient electric vehicle technology. Improving their range, efficiency, charging time, and safety could hasten the switch. At IonQ our mission is to build the world’s best quantum computers to solve the world’s most complex problems, and it’s hard to think of a better example than helping make electric vehicles a primary mode of transportation across the globe.