Quantum analysis of lithium ion materials boosts EV batteries
PsiQuantum has teamed up with Mercedes-Benz to find out how quantum computers can be used to speed up the development of more effective batteries for electric vehicles
PsiQuantum is the world’s best funded quantum startup and is building a fault-tolerant photonic quantum computer. It is working with a range of companies, including car makers, on how this can help develop new technology. Several European projects are looking at developing similar systems, including a new €50m project for a room temperature photonic quantum computer in Germany (see links below).
The new analysis by PsiQuantum and Mercedes shows how electrolyte molecules in Lithium-ion batteries (LiB) can be simulated on such a machine, giving a route to developing new materials for more efficient batteries.
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Development of new Li-ion batteries currently involves a significant amount of trial and error. Some developers such as Inobat have used machine learning and AI to accelerate the process. However, conventional supercomputers struggle to simulate the crucially important quantum behaviour of the molecules and reactions in question. Quantum computers could overcome this constraint.
Quantum analysis
PsiQuantum investigated quantum algorithms for simulating effects of the common electrolyte additive, fluoroethylene carbonate. The analysis of these electrolyte simulations uncovered new optimizations, only apparent at the scale of fault-tolerant quantum computation, which reduced the resource overhead of the application to be more manageable.
The team also demonstrated the utility of a method specific to photonic quantum computing known as interleaving which allows the time and memory resources of a quantum computer to be traded off. This marks a significant move towards the goal of efficient chemistry simulations on a quantum computer.
The team found that the problem would require a quantum computer with 16,382 logical qubits able to execute a circuit containing 232 billion T-gates. This is impractical on today’s quantum ocmputers with around 100 qubits.
However, compiling the application to a specific hardware architecture, its photonic Fusion Based Quantum Computing (FBQC) reduced this analysis to under a day.
In this architecture the fundamental hardware units are so-called Resource State Generators (RSGs) that produce small collections of entangled photons on demand. The work with Mercedes Benz found that, without further optimization, an FBQC machine could simulate the effect of fluoroethylene carbonate on battery performance in under a day.
The study also demonstrated how interleaving can trade off runtime and hardware resource requirements. Interleaving reuses single pieces of hardware multiple times, storing photons output from the hardware in optical fibre until needed. By increasing algorithm runtime to 2.5 weeks, interleaving allows fluoroethylene carbonate to be simulated with 20x fewer hardware resources.
This will enable breakthroughs in Li-ion battery design for car makers by running the optimized algorithm on PsiQuantum’s utility scale quantum computing architecture.
“Better batteries are vital for our continued transition away from fossil fuels towards more sustainable forms of transport and energy storage,” said Pete Shadbolt, chief scientific officer at PsiQuantum. “We’ve been able to optimize and enhance how a quantum computer can improve the molecular design of batteries by carefully considering how fault-tolerant machines of the future will operate. In light of greater recognition that error correction will be required to run useful quantum algorithms, customers are coming to us to understand fault-tolerant programming and resource requirements when assessing potential applications.”
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