A ternary Fe-Mn-B-C alloy system with variable Fe/Mn ratios, partial substitution of boron by carbon, and exploration of alternative body-centered tetragonal, orthorhombic, and related lower-symmetry space groups, where light elements occupy interstitial sites, can achieve a Curie temperature above 500 K, magnetic density exceeding 0.1 μB/atom, moderate complexity (≤20 atoms/unit cell), and improved thermodynamic and dynamic stability with formation energy e_hull ≤ 0.15 eV/atom. Structural and compositional tuning, including targeted light-element substitution and symmetry-lowering distortions, is necessary to enhance magnetic anisotropy energy and dynamic stability for permanent magnet applications.
Property | Value |
---|---|
composition | MnFe4Co2(BC)2 |
space group | 1 |
score | 0.714 |
generation method | multiple_mutations |
number of trials | 3 |
Property | Value |
---|---|
curie_temperature | 458.7 |
magnetic_density | 0.115878 |
cost | 9.38 |
e_hull | 0.35086 |
dynamic_stability | True |
- The material achieves good magnetic density and dynamic stability, which are essential for practical magnetic applications. - The Curie temperature is near but below the target, suggesting potential for improvement. - The relatively high energy above hull indicates the composition or structure may need optimization to improve thermodynamic stability. - Cost is not a limiting factor here. - The combination of elements (Mn, Fe, Co, B, C) can yield promising magnetic properties but may require further tuning to meet all targets.
Phase diagram of MnFe4Co2(BC)2; e_above_hull: 0.350860 eV/atom; predicted_stable: False
**1. Initial Material Generation**
Generated 3 initial material candidates using AI-driven hypothesis generation. Started with 1 from-scratch generations.
*Reasoning:* System begins with broad exploration to establish baseline materials and understand the chemical space, building up a database of candidates for future mutation operations.
**2. Performance Optimization Convergence**
Achieved 27.1% improvement from initial score (0.562) to final best (0.714). Best material discovered at iteration 2.
*Reasoning:* The evolutionary process successfully optimized target properties through iterative refinement, with the AI learning to generate progressively better materials by leveraging successful mutation patterns and chemical insights.
**3. Chemical Space Diversification**
Explored 5 different elements across 3 unique compositions, systematically mapping the rare-earth-free magnetic material space.
*Reasoning:* Comprehensive exploration of chemical diversity ensures the discovery process doesn't get trapped in local optima and identifies the most promising regions of chemical space for permanent magnet applications.
iteration | composition | sg | method | score |
---|---|---|---|---|
0 | Fe4Mn3B4 | 6 | from_scratch | 0.562079 |
1 | Mn3Fe4(BC)2 | 1 | multiple_mutations | 0.580194 |
2 | MnFe4Co2(BC)2 | 1 | multiple_mutations | 0.71441 |