Quantum computers can simulate better materials for batteries that are safer, more energy-dense and easier to recycle.
Ford researchers have published a new preprint study in ArXiv in which they modeled crucial materials for electric vehicle (EV) batteries using a quantum computer.
While the results reveal nothing new about lithium-ion batteries, they demonstrate how more powerful quantum computers could be used to accurately simulate complex chemical reactions in the future.
Better battery materials may be found using quantum computers
To discover and test better battery materials with the help of computers, researchers must break the process into several separate calculations: one set for all the relevant properties of each molecule, another for how those properties are affected by the smallest changes of the environment, such as temperature fluctuations, and one for all the possible ways in which any two molecules can interact together.
Even something that seems simple like bonding two hydrogen molecules requires incredibly deep calculations.
But developing materials using computers has a huge advantage: researchers don’t have to literally test every possible experiment, which can be incredibly time-consuming.
Tools like artificial intelligence and machine learning have been able to speed up the research process to develop new materials, but quantum computing offers the potential to make it even faster. For electric vehicles, finding better materials could lead to more durable, faster charging and more powerful batteries, he writes Popular Science.
Why are quantum computers used?
Traditional computers use binary bits (which can be zero or one) to perform all calculations. While they are capable of incredible things, there are some problems, such as highly accurate molecular modeling, that they simply do not have the power to handle, and because of the types of calculations involved, they may never be able to.
Once researchers model more than a few atoms, the calculations become too large and too time-consuming, so scientists must rely on approximations that reduce the accuracy of the simulation.
Instead of ordinary bits, quantum computers use qubits that can be zero, one, or both at the same time. Qubits can also be entangled, rotated and manipulated in other quantum ways to carry more information. This gives quantum computers the power to solve problems that are impossible for traditional computers, such as precisely modeling molecular reactions.
In addition, molecules are quantum in nature and therefore more accurately “model” on qubits, which are represented as waves.
Ford’s attempt to find better battery materials
Unfortunately, many of these things are still theoretical. Quantum computers are not powerful enough or reliable enough to be commercially viable on a large scale. There is also a lack of knowledge, since quantum computers work in a completely different way than traditional computers, researchers are still learning how to best use them.
This is where Ford’s research comes in. Ford researchers are interested in making better battery materials that are safer, denser and easier to recycle. To do this, they need to understand the chemical properties of potential new materials, such as charge and discharge mechanisms, as well as electrochemical and thermal stability.
The team wanted to calculate the ground energy (or normal atomic energy state) of LiCoO2, a material that could be used in lithium-ion batteries. The researchers did this by using an algorithm called the variational quantum eigensolver (VQE) to simulate the Li2Co2O4 and Co2O4 gas-phase models (basically the simplest form of chemical reaction possible) that represent the charging and discharging of the battery.
VQE uses a hybrid quantum-classical approach where the quantum computer (in this case, 20 qubits in an IBM state vector simulator) is used to solve the parts of the molecular simulation that bring the greatest benefits. Traditional computers handle the rest of the calculations.
Because this was a proof of concept for quantum computing, the team tested three approaches with VQE, which they named UCCSD, UCCGSD, and k-UpCCGSD. In addition to comparing the quantitative results, they compared the quantum resources required to perform the calculations accurately with classical approaches based on the wave function.
The researchers found that k-UpCCGSD produced results similar to UCCSD at a lower cost, and that the results from the VQE methods were similar to those obtained from the classical CCSD and CASCI methods.
A step forward for electric vehicles
Although there is still much work to be done, the researchers concluded that computational chemistry performed on soon-to-be-available quantum computers will have “a vital role in finding potential materials that can improve battery performance and robustness.”
Although they used a 20-qubit simulator, they suggest that a 400-qubit quantum computer (soon to be available) would be needed to fully model the Li2Co2O4 and Co2O4 system they studied.
All of this work is part of Ford’s bid to become a dominant electric vehicle maker. Trucks like the F-150 Lightning push the limits of current battery technology, so further advances, perhaps aided by quantum chemistry, will become increasingly necessary as the world moves away from gas-powered cars.
And Ford isn’t the only player considering using quantum computers to develop new batteries. IBM is working with Mercedes and Mitsubishi on using quantum computers to reinvent the EV battery.