Quantum computing has the potential to fundamentally reshape chemical R&D. High-precision quantum molecular simulations will enable researchers to model complex molecules and reactions with unprecedented accuracy, speeding up the design of novel materials, advanced formulations, and high-performance catalysts according to consultants at McKinsey.
Describing quantum computing as a “powerful new tool to address the chemical industry’s most pressing challenges,” McKinsey Technology’s analysis said the total potential of quantum computing applications in chemical could be between $200 billion to $500 billion by 2035. This value would be derived from cost reductions, faster R&D, and new product and revenue streams. Areas where McKinsey believes quantum computing holds particular promise include: design of next-generation biocides for sustainable agriculture; developing high-energy-density battery materials for electric vehicles; and inventing peptides that can breakdown microplastics.
As well as R&D, quantum computing is set to positively impact manufacturing and sustainability. “By modelling chemical reactions and process dynamics with greater accuracy, quantum computing can help increase yields, improve energy outputs and reduce material waste,” the consultants said.
The commentary cites work carried out by BASF which it says is “exploring quantum applications across its operations.” Back in 2023 BASF announced a collaboration with SEEQC, a US-based quantum computing company, to investigate the application of quantum computing in chemical reactions. The research focused on looking at the potential of quantum in homogenous catalysis. BASF also established a collaboration with Germany-based Kipu Quantum in 2024, to study the potential of its novel quantum algorithms for BASF’s logistics optimisation.
Other notable quantum computing collaborations in the chemical sector, highlighted by McKinsey include: BP working with ORCA Computing to apply hybrid quantum classical machine learning to generative modelling of molecular conformations, and Mitsubishi Chemical Group working with PsiQuantum to simulate excited states of photochromic molecules used for energy-efficient data storage and solar energy storage.
Collaborations such as these, says McKinsey, show that while still in their early stages, quantum applications in the chemicals industry are advancing rapidly. “Leading chemical companies and their downstream customers, such as automotive companies, are actively investing in quantum computing and exploring its potential,” the commentary notes.
In the near-term, hybrid approaches that combine classical high performance computing, artificial intelligence/machine learning, and quantum tools will likely deliver the greatest value. R&D workflows will increasingly become hybrid. “Classical computing will continue to handle equilibrium and large-scale simulations, while quantum computing will focus on non-equilibrium dynamics, reaction kinetics, and catalytic behaviours that currently defy accurate modelling,” McKinsey says.
Key steps to preparing to engage with quantum computing include: establishing quantum ready IT infrastructure, including access to cloud-based quantum computing platforms; developing proprietary algorithms tailored to high-impact use cases; and recruitment and upskilling talent in quantum information science, algorithm development and hybrid computing.
McKinsey says: "Quantum computing is not a silver bullet, but it is a foundational shift in what is computationally possible. For chemicals companies, the implications are vast: accelerated discovery, leaner production, and the ability to solve previously intractable problems. By starting now, industry leaders can stay ahead of the curve and help shape the next era of innovation in chemistry."
Further reading
- What’s driving R&D? AI, sustainability and connectivity
- Carbon capture: Using machine learning to cross the 'Valley of Death'
- 10 innovations that could transform chemistry
- ‘AI scientist’ helps researchers find new drug treatment combinations with GPT-4
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