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What came first, the science of quantum computing or its purpose? There is a case for the latter. Physicists have been working on ways to take advantage of qubits, the quantum version of binary bits, for years, but the technologies to date have been largely purpose-built, aimed at solving specific types of problems.
One of the labs I’m involved with is doing basic research on quantum computing while partnering with various academic groups where quantum computing is expected to make a difference, such as in compressed sensing and drug discovery. However, work is proceeding apace on other fronts—for example, at the intersection of transportation and manufacturing. Two years ago, McKinsey & Company Research suggests that one-tenth of all quantum computing use cases under exploration could benefit the automotive industry. A subset of these cases concerns the batteries that will power future electric vehicles (EVs).
EV battery background
Here’s the larger issue: While the cost of EV battery packs has dropped significantly over the past dozen years, batteries based on lithium-ion technology still make up a significant portion of an EV’s huge total cost. High purchase prices will prevent greater adoption and delay the expected reduction in carbon footprint.
Above the cost structure, there is performance. Consumers want EVs that drive reliably, go long distances without recharging, impose minimal environmental burden and are safe to drive. Let’s spell out what those requirements mean to product developers and engineers. Reliability and distance are battery life span, energy density, charge time, equilibrium voltage, temperature and discharge rate, among other factors. Green means being recyclable, avoiding pollutants and reducing waste. The safety of a battery is ultimately related to the thermal stability of its chemical components.
Ultimately, solving complex problems requires trade-offs. Consider Tesla, which last year decided to change battery types in its standard-range cars. The company dropped in favor of lithium-nickel-cobalt-aluminum (NCA). Lithium-Iron-Phosphate (LFP), which is less expensive and safer, although not as energy-dense or resistant to low temperatures. These compounds are attached to the positive electrode or cathode of the battery. Automakers are betting that quantum computing will help them identify the optimal battery chemistry.
Carmakers and Quantum
Since 2017, Volkswagen has been working on quantum computing, first with Canadian firm D-Wave and later with Google. In 2018, they reported using quantum computing to simulate molecules, e.g Lithium-Hydrogen and Carbon Chains, aiming to develop a “tailor-made battery”. Mercedes-Benz parent Daimler AG taps IBM’s Quantum team for work Lithium-sulfur 2020 and recently reportedly working with IBM to accelerate development time through better understanding Lithium-ion Chemistry.
Toyota is working with Tokyo-based Kunasys on quantum techniques to improve modeling of an EV battery component Electronic structure. For its part, Hyundai has partnered with Maryland-based IonQ to study its battery compounds, including Lithium oxide. Founded in 2015, IonQ began trading in 2021 as “the world’s first public pure-play quantum computing company”. Unlike Google, IBM and others, which use superconducting loops to create qubits, IonQ uses trapped ions.
Another startup, Canadian company Xanadu, published an article recently the nature Regarding achieving quantum advantages (ie, proving that their results are beyond that of a classical computer), also target batteries. In a paper co-authored with several academics and Volkswagen researchers, Xanadu scientists introduced “Quantum algorithms for calculating equilibrium cell voltage, ionic mobility and thermal stability.” Their goal is to mimic another cathode material, Dilithium-iron-silicate.
Like the coherent Ising machine (CIM) with which one of my company’s labs is engaged, the Xanadu approach to quantum computing is photonics-based.
Pre-universal approach
There are many other automotive-related problems, besides batteries, that quantum computing is poised to tackle—and industry leaders would do well to keep a close eye on developments in this space. BMW recently announced a winner The quantum computing challenge Involves automated driving, material deformation, equipment configuration and quality analysis.
At the same time, existing technologies are still capable of solving a large number of the industry’s current computational needs. The UK-based Faraday Institution uses a digital supercomputer (named Michael) researching lithium-ion batteries, next-generation lithium-ion cathode materials, and what lies beyond. It would be a mistake to dismiss today’s supercomputers, as hybrid architectures hold great promise for combining quantum and classical capabilities.
Still, since we’re several years away from a “universal” quantum device that can solve any number of problems, discussions of quantum computing will likely stay close to the specific problem it seeks to solve, whether it’s related to EV batteries or some other. . Applications and Industry.
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