Materials and Energy
Design permanent magnet compositions and crystal structures for high energy products without critical rare-earth dependencies.

The Challenge
Electric-vehicle motors, wind-turbine generators, and industrial drives all depend on high-performance permanent magnets. NdFeB and SmCo deliver exceptional energy products but rely on rare-earth elements exposed to supply-chain concentration, price volatility, and geopolitical risk. Developing rare-earth-free or rare-earth-reduced magnets with competitive performance is one of the decade's most pressing materials challenges. The design space for new magnetic phases is enormous: combinations of transition metals, metalloids, and light elements across various crystal structures create billions of potential candidates, and the physics linking composition and structure to magnetic performance involves complex exchange interactions, magnetocrystalline anisotropy, and domain structure that defy simple screening rules.
Current magnet discovery relies on DFT calculations of magnetic moments and anisotropy energies for proposed crystal structures, combinatorial thin-film synthesis of narrow composition ranges, or ML models trained on magnetic-property databases. DFT is accurate but expensive and evaluates only the structures someone has already proposed. Combinatorial synthesis produces thin-film samples whose magnetic properties may not transfer to bulk magnets. ML models interpolate within known families but lack the structural constraints to generate valid candidates in novel chemical spaces; they may predict high magnetic moments for compositions that cannot form stable crystals.
The MatterSpace Approach
MatterSpace Lattice co-optimizes composition, crystal structure, and magnetic properties under constraints that enforce structural validity and supply-chain requirements. Users specify minimum energy-product targets, maximum rare-earth content (including zero for fully rare-earth-free magnets), operating-temperature requirements, and coercivity targets. Lattice generates novel magnetic phases satisfying all constraints, coupling magnetic-property prediction with structural stability so that candidates with favorable exchange interactions and anisotropy also possess synthesizable crystal structures.
The Magnetic Materials domain pack encodes exchange coupling, magnetocrystalline anisotropy, domain-wall energetics, and structure-property relationships for hard magnetic phases. Users specify magnet requirements (minimum BHmax, Curie-temperature floor, maximum rare-earth fraction, coercivity targets). Lattice produces candidate crystal structures with predicted saturation magnetization, anisotropy fields, and energy products. Validation includes thermodynamic stability, Curie-temperature verification, and phase-competition analysis. Output candidates include crystallographic data, predicted magnetic properties, and recommended synthesis approaches.
Specify what the output must satisfy. MatterSpace constructs candidates that meet all constraints simultaneously.
Every output satisfies physical laws, stability criteria, and domain constraints — no post-hoc filtering needed.
Powered by MatterSpace, the Universal Generation Engine for Science and Engineering and a goal-driven inverse generation engine, with physics-aware priors and adaptive dynamics control.
Generation Output
Key Differentiators
Crystal-structure validity and magnetic performance are jointly guaranteed. Lattice avoids the common failure mode of computationally predicted magnets that turn out to be thermodynamically unstable or unsynthesizable. It explores beyond known magnetic structural prototypes, generating candidates with novel crystal chemistries unreachable through analogy-based search. Rare-earth-free generation is a first-class capability: Lattice produces transition-metal, metalloid, and light-element combinations that achieve competitive energy products without supply-chain risk. Temperature-dependent property prediction ensures candidates perform across the full operating range, not just at room temperature.
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Whether you are exploring magnets and magnetic materials for the first time or scaling an existing research programme, MatterSpace generates novel candidates that satisfy your constraints by construction.
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