Why the Ideal Magnet Remains Out of Reach

2026-04-29 · Source: IEEE Spectrum · Field: Science & Research — Physical Sciences & Chemistry, Mathematics & Computational Sciences, Artificial Intelligence & Machine Learning · Depth: Expert, medium

Summary

Researchers globally are urgently seeking cost-effective, powerful permanent magnets free of rare earth elements, which are critical for electric vehicles, wind turbines, and robotics, and whose supply is largely controlled by China. Despite over a decade of intensive effort, conventional high-performance computers have failed to discover viable alternatives, primarily because simulating the complex interactions of electron orbitals and spin states in hypothetical materials presents a combinatorial space of 2^40 or 2^50, making it computationally intractable. A collaboration involving Alice & Bob, Los Alamos National Laboratory, and GE Vernova, backed by US \$3.9 million from ARPA-E, is now testing the hypothesis that quantum computers can solve this problem by leveraging quantum parallelism and superposition. They anticipate needing 100 logical qubits, potentially by 2030, to accurately simulate these materials, contrasting with less successful simplified approaches like Microsoft's MatterGen.

Key takeaway

For research scientists developing advanced materials, the computational intractability of simulating complex electron interactions necessitates exploring novel approaches. You should consider how quantum computing, especially with logical qubits, could integrate into your material discovery workflows. This could help tackle problems like rare-earth-free magnet design. However, practical quantum solutions are still years away, with 100 logical qubits projected around 2030.

Key insights

Quantum computing offers a potential breakthrough for simulating complex material properties, overcoming classical computational limits.

Principles

• Permanent magnetism arises from aligned electron spins in crystalline materials.
• 4f electrons in rare earths enhance magnetic anisotropy and coercivity.
• Simulating electron interactions creates an intractable combinatorial space.

Method

A proposed method involves using quantum parallelism and superposition with 100 logical qubits to simulate complex electron orbital and spin state interactions for new magnet discovery.

In practice

• Explore quantum computing for materials science simulations.
• Integrate quantum calculations into larger ML-guided workflows.
• Focus on high coercivity and chemical stability in magnet design.

Topics

• Permanent Magnets
• Rare Earth Elements
• Quantum Computing
• Materials Science
• Computational Chemistry
• Alice & Bob

Best for: AI Scientist, Research Scientist

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Editorial summary, takeaway, and curation by AIssential. Original article published by IEEE Spectrum.