How Quantum Computers Can Make Batteries Better

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How Quantum Computers Can Make Batteries Better
Hyundai partners with IonQ to optimize lithium-air batteries
CHARLES Q. CHOI
20 JAN 2022

Tesla Cybertruck How Quantum Computers Can Make Batteries Better ll-out-showing-a-rendering-of-a-molecular-compound

HYUNDAI
IONQ QUANTUM COMPUTING BATTERIES LITHIUM-AIR BATTERIES HYUNDAI ELECTRIC VEHICLES


Hyundai is now partnering with startup IonQ to see how quantum computers can design advanced batteries for electric vehicles, with the aim of creating the largest battery-chemistry model yet to be run on a quantum computer, the companies announced yesterday.

A quantum computer with high enough complexity—for instance, enough components known as quantum bits or “qubits”—could theoretically achieve a quantum advantage where it can find the answers to problems no classical computer could ever solve. In theory, a quantum computer with 300 qubits fully devoted to computing could perform more calculations in an instant than there are atoms in the visible universe.

The nearest-term app for quantum computers may be chemistry—for instance, simulating molecules to see which ones might prove useful drugs. “Quantum computers are naturally suited for modeling molecular behavior because both are systems governed by quantum mechanics,” says Peter Chapman, CEO and president of Maryland-based IonQ. Since quantum computers can model chemistry more accurately than classical computing, “it becomes possible to ensure that one is extracting maximum efficiency and eliminating sources of potential waste.”

Now IonQ aims to use quantum computing to analyze and simulate the structure and energy of lithium compounds for Hyundai’s batteries, including lithium oxide in lithium-air batteries. “Lithium-air batteries have a higher energy density than lithium-sulfur batteries and thus have more potential power and capability,” Chapman says.

In the new partnership, IonQ will develop new variational quantum eigensolver algorithms optimized for investigating lithium chemistry. These kinds of algorithms are often used in quantum chemistry to, for instance, model a molecule’s ground state, the one in which it has the least amount of energy. Variational quantum eigensolvers are actually hybrid algorithms, where classical computers do much of the work while quantum processors solve the part of the problem that would prove difficult for conventional machines to handle.

IonQ will join the classical and quantum computers in this work over the cloud. This includes IonQ’s latest quantum computer, “which recently outperformed all other devices tested in a series of benchmarking tests run by industry consortium QED-C and which is currently in private beta,” Chapman says.

Tesla Cybertruck How Quantum Computers Can Make Batteries Better a-gold-colored-rectangular-chi

IonQ's glass chip can hold 64 ions in four groups for a total of 32 usable qubits. WALKER STEERE/IONQ


Whereas Google, IBM, Amazon and others often use qubits based on superconducting loops, IonQ uses qubits based on electromagnetically trapped ions. Superconducting loops are compatible with conventional microchip technology, but trapped ions may offer advantages such as resistance to errors.

The partnership aims to create the most advanced battery chemistry model yet developed on quantum computers, measured by the number of qubits and quantum gates, the quantum computing version of the logic gates that conventional computers use to perform computations.

“The team plans to harness at least 12 qubits and over 100 gate operations for the project,” Chapman says. In comparison, a Daimler-IBM partnership using quantum computing to develop next-generation lithium-sulfur batteries used only four qubits, and no other commercial projects have published results yet, he notes.

Carmakers are increasingly looking into quantum computing “because it is naturally applied to a revolution taking place across the industry—the development of electric vehicles,” Chapman says. “There is enormous incentive to make a better, less expensive battery, and so it makes sense that forward-thinking companies like Hyundai are putting quantum in their tool kit.”

The companies noted this work aims to improve the cost, durability, capacity, safety, and charging behavior of lithium batteries, which are often the most expensive components of electric vehicles. “Electric vehicles are an important part of the global movement toward reducing our collective carbon footprint,” Chapman says. “It’s very meaningful to be partnering with Hyundai to advance science that will help make them more commonplace.”

Beyond chemical analysis for battery materials, quantum computing could also help explore fuel-cell technologies and material durability, Chapman notes. In addition, “quantum machine learning applications could be used to improve training time for autonomous vehicles and solve simple problems in predictive maintenance, warehousing, and more,” he says.

“Longer-term, more complex optimization problems such as multichannel logistics and routing are on automakers’ R&D slates,” Chapman adds. “For instance, Volkswagen has been exploring quantum computing in a variety of applications for several years, first looking at how best to optimize the routing of buses and vans in traffic using quantum hardware and quantum-inspired techniques. More recently, they’ve been looking at optimizing the distribution network of charging stations.”


All in all, “I hope this partnership makes clear that quantum is not some far-off concept with no present practical application,” Chapman says. “If you choose the right partner and pick the right problems, there is impactful work that can be done right now.”

https://spectrum.ieee.org/lithium-air-battery-quantum-computing


New partnership aims to improve the durability, capacity and safety of the car company's batteries.

Tesla Cybertruck How Quantum Computers Can Make Batteries Better image009

Quantum computing company IonQ is working with Hyundai Motors to develop safer and more efficient batteries for electric cars.
Image: IonQ

IonQ and Hyundai Motors announced a new partnership designed to use the power of quantum computing to build better electric car batteries. The companies expect the research to benefit Hyundai's automotive lithium batteries by making improvements to the charge and discharge cycles of the devices as well as their durability, capacity and safety.

The team will develop new variational quantum eigensolver (VQE) algorithms to study lithium compounds and their chemical reactions. The IonQ/Hyundai project plans to run a battery chemistry model to simulate 14 electrons of dilithium oxide.

A VQE algorithm runs partly on a classical computer and partly on a quantum computer. As the IBM Q team explained: "A classical computer varies some experimental parameters that control the preparation of a quantum state, and then a quantum computer prepares that state and calculates its properties."

The project team will have access to all quantum computers commercially available at IonQ, including the latest system which is currently in private beta. This version of the hardware recently outperformed all other devices tested in a series benchmarking tests run by industry consortium QED-C, according to Peter Chapman, president and CEO of IonQ.


"In terms of recent technological milestones, the system uses the advanced double-individual gate laser system, where each ion is being hit by two individual laser beams," he said.

TaeWon Lim, executive vice president and head of the Fundamental Material Research Center at Hyundai Motor Group, said in a press release that the company is stepping into the quantum era and developing more effective battery power.

"This creative collaboration with IonQ is expected to provide innovation in the development of basic materials in virtual space for various parts of the future mobility," he said.

Chapman said in a press release that quantum chemistry solutions can address climate change.
"Battery efficiency is one of the most promising emerging areas where quantum computing can make a difference," he said.

SEE: Quantum startups Pasqal and Qu&Co merge and promise 1,000 qubits by 2023

Chapman sees many use cases for quantum computing in the auto industry as Hyundai and others shift their focus from being car manufacturers to being transport and mobility providers.

"Volkswagen, Daimler, Bosch, BMW, and more have already invested in research across a variety of application areas," he said. "Volkswagen has been exploring quantum computing in a variety of applications for several years, first looking at how best to optimize the routing of buses and vans in traffic using quantum hardware and quantum-inspired techniques, and more recently, they're looking at optimizing the distribution network of charging stations."

The research from the battery project also could be used to improve fuel cell technologies and material durability, Chapman said, as well as optimization challenges.

"Quantum machine learning applications could be used to improve training time for autonomous vehicles, and solve simple problems in predictive maintenance, warehousing and more," he said. "Longer-term, more complex optimization problems such as multichannel logistics and routing are on automakers' R&D slates."

This quantum partnership supports Hyundai's Strategy 2025 goals, which are designed to increase sales of electric vehicles and address climate change. The plan has four focus areas: electric vehicles, urban air mobility, autonomous driving technology and hydrogen fuel cells. The Strategy 2025 goals include selling an all-electric lineup by 2040 and developing a hydrogen fuel cell ecosystem.

Hyundai started selling electric vehicles in 2008 and brings expertise in lithium batteries to the new partnership, while IonQ brings quantum skills and hardware. IonQ has worked with other partners to apply quantum computing to chemistry problems. In March 2021, IonQ described research with Dow and 1QBit to simulate complex molecules and chemical compounds. The researchers used the principle of problem decomposition to "reduce the number of qubits required to simulate the electronic structure of a large model chemical system."

This means fewer qubits–up to a factor of 10–are needed to achieve the same level of accuracy compared with solving the problem without breaking it down into smaller parts. The paper, "Optimizing Electronic Structure Simulations on a Trapped-ion Quantum Computer using Problem Decomposition," was published in February 2021.

IonQ uses a trapped-ion design in its quantum machines. IonQ's quantum systems are available through direct API access, Amazon Braket, Microsoft Azure and Google Cloud.


https://www.techrepublic.com/articl...istry-to-work-on-improving-lithium-batteries/
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IonQ : Improving Battery Chemistry with Quantum Computing01/21/2022 | 12:53pm EST

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.

https://www.marketscreener.com/quot...ry-Chemistry-with-Quantum-Computing-37611235/
 

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Fusion reactors have already been invented. Big oil bought out the patent and is sitting on it.

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