Ford and BMW Solve Quantum Chemical Challenge with Quantinuum’s InQuanto | Daily News Byte


By Carolyn Mathas

The automotive industry is lining up to be a very strong and early adopter of quantum technology for a variety of reasons. Quantum computers are particularly adept at optimization and simulation. For automotive, this includes solving complex material design challenges, simulation of battery technology and eliminating more expensive and time-consuming real-time testing and prototyping wherever possible.

Ford and BMW have made recent announcements on how they are using the Quantinuum InQuanto computational chemistry software platform to address these challenges.

Ford and Battery Chemistry

Ford quantum researchers, for example, recently released the results of a new study that modeled Quantinuum EV battery materials using quantum computers, showing that important chemical simulations will be possible in future, more powerful systems. A team of Ford researchers tested simulations of lithium-ion battery chemistry using Quantinuum’s InQuanto with the company’s H-series ion-trap quantum hardware.

The challenge is that while lithium-ion batteries can be charged and discharged many times, they are still sensitive to heat and inherently flammable. Improvements in energy density, power density, lifecycle, safety, cost, and recyclability are on the drawing board. That’s where quantum computational chemistry comes in. The study found that, “Computational chemistry can provide insights into charge/discharge mechanisms, electrochemical and thermal stability, structural phase transitions, and surface behavior, and it plays an important role to find the potential materials that could improve battery performance and durability.”

In researching lithium-ion battery chemistry using quantum computers, scientists used an algorithm for finding the ground state of a quantum mechanical system. The hybrid quantum-classical algorithm solves the part of a molecular system that benefits most from quantum computation, with the rest of the calculations directed to a classical computer.

BMW and Hydrogen Fuel Cells

BMW announced that it is using the InQuanto platform on AWS to simulate the surface properties of a material to be used in its hydrogen fuel cell powertrains. A major challenge in developing novel fuel cell technology is the slow kinetics of the oxygen reduction reaction (ORR). Most studies involving catalytic and electrocatalytic chemical reactions such as the ORR, use the density functional theory (DFT) method of computational chemistry. DFT relies on canceling errors and has insufficient accuracy for this application. Quantum computing, however, has the potential to deliver accurate calculations of complex systems, without the compromises of DFT.


The InQuanto platform allows computational chemists to focus on their research using proven code and algorithms available from the InQuanto library, and not write a lot of code. Computational chemists who have not worked with quantum systems can access the easy-to-use interface. They can run their simulations of scaled-down molecular and material problems on quantum hardware, including IBM’s series of superconducting circuit devices, and Quantinuum’s H Series of ion-trap devices, operated by Honeywell, along with a range of other hardware devices and emulators.

inQuanto 2.0 has just been released to provide a more versatile, extensible, and adaptable platform for those new to using quantum computers, InQuanto is built on the latest quantum algorithms, advanced subroutines, and chemistry-specific noise-mitigation techniques. The new version improves efficiency with new protocol classes that speed up vector calculations by an order of magnitude, and integral operator classes that exploit symmetries and can reduce memory requirements. Learn more at Ford, BMW and InQuanto.

December 22, 2022


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