Effects of chain configuration and stoichiometry on the behavior of boron carbide from first-principle calculations
Bibliographic record
Abstract
Boron carbide is an advanced ceramic known for its high hardness, chemical and thermal stability, and wear resistance, making it ideal for refractory applications such as thermal barrier coatings, aerospace components, neutron absorbers, and semiconductor electronics. Despite these applications, the relationship between atomic configuration and properties of boron carbide at higher temperatures remains largely unexplored. This study investigates the effects of stoichiometry and chain arrangement in boron carbide structures on their elastic and thermal properties at elevated temperatures. Fifteen different structures with varying carbon concentrations and chain arrangements are considered. A quasi-harmonic approach, consisting of static density functional theory and phonon calculations, was used to explore these properties up to 2000 K. Increasing carbon concentration generally enhances structural stability. Specifically, B 11 C p (CBC) is the most stable, while B 12 (BCB) is the least stable. Carbon placement in icosahedra at the polar site within structures results in greater stability. Temperature-dependent elastic constants were predicted up to 2000 K, showing a significant reduction in values for all C i j s except C 44 , which remains nearly constant, highlighting boron carbide’s anisotropic behavior. Structures with a C-B-C chain arrangement exhibit better resistance to compression and shear deformation. The thermal expansion coefficient trends for stable structures are predicted. The results show that structures with a C-B-C chain arrangement have lower thermal expansion coefficients and better thermal stability compared to those with a C-C-B chain. This research enhances our understanding of boron carbide’s behavior at elevated temperatures. These insights are crucial for optimizing manufacturing processes and designing high-performance components.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".