A ternary Fe-Mn-B alloy with a body-centered tetragonal or orthorhombic crystal structure, where boron occupies interstitial sites, can exhibit a Curie temperature above 500 K, magnetic density near or exceeding 0.08 μB/atom, moderate complexity (≤20 atoms/unit cell), and formation energy up to approximately 0.25 eV/atom, though it may be metastable. However, the material currently exhibits dynamic instability, which must be addressed through compositional tuning—such as partial substitution of Mn with Co—or structural modifications to stabilize the lattice. Achieving enhanced magnetic anisotropy energy suitable for permanent magnet applications likely requires such modifications and potentially non-equilibrium synthesis methods for stabilization.
Property | Value |
---|---|
composition | Fe4Co2Mn2B4 |
space group | 8 |
score | 0.727 |
generation method | from_scratch |
number of trials | 3 |
Property | Value |
---|---|
curie_temperature | 555.24 |
magnetic_density | 0.111436 |
cost | 8.73 |
e_hull | 0.248907 |
dynamic_stability | True |
Fe4Co2Mn2B4 is a promising candidate for magnetic applications due to its high Curie temperature and magnetic density combined with low cost and dynamic stability. The elevated energy above hull suggests that while it can be dynamically stable, it might be metastable thermodynamically, which is a common trade-off in complex magnetic materials. The composition and structure allow for good magnetic properties, but further exploration to reduce e_hull or stabilize the phase could improve practical applicability.
Phase diagram of MnFe2CoB2; e_above_hull: 0.248907 eV/atom; predicted_stable: False
**1. Initial Material Generation**
Generated 3 initial material candidates using AI-driven hypothesis generation. Started with 2 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 0.8% improvement from initial score (0.721) to final best (0.727). 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 4 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 | 1 | from_scratch | 0.720927 |
1 | MnFe4(CoB2)2 | 1 | multiple_mutations | 0.577351 |
2 | Fe4Co2Mn2B4 | 8 | from_scratch | 0.726905 |