A ternary Fe-Mn-B alloy with a body-centered tetragonal or orthorhombic crystal structure, where boron occupies interstitial sites, will exhibit high Curie temperature (>500 K), magnetic density >0.1 (μB/atom), moderate complexity (≤20 atoms/unit cell), and low formation energy (e_hull ≤ 0.15 eV/atom), while achieving enhanced magnetic anisotropy energy sufficient for permanent magnet applications.
Property | Value |
---|---|
composition | Fe4Mn3B4 |
space group | 1 |
score | 0.679 |
generation method | from_scratch |
number of trials | 2 |
Fe4Mn3B4 (requested SG: P-4 #81, calculated SG: P1 #1, optimized: 379 steps, cell relaxed (isotropic))
Property | Value |
---|---|
curie_temperature | 543.04 |
magnetic_density | 0.067841 |
cost | 1.29 |
e_hull | 0.239043 |
dynamic_stability | True |
The Fe4Mn3B4 compound shows good thermal magnetic stability with a Curie temperature above the target, but its magnetic density is insufficient. The elevated energy above hull points to a potential issue with phase stability or synthesis feasibility. This suggests that while the composition can sustain magnetism at high temperatures, the magnetic moment per volume is too low and the material may decompose or transform under standard conditions.
Phase diagram of Mn3(FeB)4; e_above_hull: 0.239043 eV/atom; predicted_stable: False
Interactive visualization showing the evolution of 26 structural frames during the mutation process.
Standalone, embeddable HTML with MatterViz Trajectory viewer
**1. Initial Material Generation**
Generated 2 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 0.0% improvement from initial score (0.679) to final best (0.679). Best material discovered at iteration 0.
*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 2 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 | 0.6787470000000001 |
1 | MnFe4(CoB2)2 | 1 | multiple_mutations | 0.580585 |