By Carolyn Mathas

The automotive industry is lining up to become a very strong and early adopter of quantum technology for a variety of reasons. Quantum computers are specifically adept at optimization and simulation. For automotive, this involves solving complex challenges in material design, battery technology simulation and eliminating as much costly and time-consuming real-time testing and prototyping as possible.

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

Ford and Battery Chemistry

Ford quantum researchers, for example, recently released the results of a new study with Quantinuum modeled EV battery materials using quantum computers, demonstrating that valuable chemical simulations will be possible on future, more powerful systems. Ford’s team of researchers tested simulations of lithium-ion battery chemistry using Quantinuum’s InQuanto together 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 however, sensitive to heat and are inherently flammable. Improvements in energy density, power density, lifecycle, safety, cost, and recyclability are all on the drawing board. That’s where quantum computational chemistry comes in. The study found that, “Computational chemistry can provide insights about the charge/discharge mechanisms, electrochemical and thermal stability, structural phase transition, and surface behavior, and it plays a vital role to find potential materials that can enhance the battery performance and robustness.”

In researching lithium-ion battery chemistry using quantum computers, the 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 the quantum computation, with the remaining calculations directed to a classical computer.

BMW and Hydrogen Fuel Cells

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


The InQuanto platform enables 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 that have not worked with quantum systems can access the easy-to-use interface. They can run their simulations of scaled molecular and material problems on quantum hardware, including the IBM series of superconducting circuit devices, and Quantinuum’s H Series of ion-trap devices, Powered by Honeywell, plus a range of other hardware devices and emulators.

inQuanto 2.0 was just released to provide a more versatile, extensible, and more applicable platform for those new to the use of quantum computers, InQuanto is built around the latest quantum algorithms, advanced subroutines, and chemistry-specific noise-mitigation techniques. The new version enhances 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