Structural determination and physical properties of 4d transitional metal diborides by first-principles calculations
Bibliographic record
Abstract
The structural determination, thermodynamic, mechanical, dynamic and electronic properties of 4d transitional metal diborides MB2( M = Y – Ag ) are systematically investigated by first-principles within the density functional theory (DFT). For each diboride, five structures are considered, i.e. AlB2-, ReB2-, OsB2-, MoB2- and WB2-type structures. The calculated lattice parameters are in good agreement with the previously theoretical and experimental studies. The formation enthalpy increases from YB2to AgB2in AlB2-type structure (similar to MoB2- and WB2-type). While the formation enthalpy decreases from YB2to MoB2, reached minimum value to TcB2, and then increases gradually in ReB2-type structure (similar to OsB2-type), which is consistent with the results of the calculated density of states. The structural stability of these materials relates mainly on electronegative of metals, boron structure and bond characters. Among the considered structures, TcB2– ReB2( TcB2– ReB2represents TcB2in ReB2-type structure, the same hereinafter) has the largest shear modulus (248 GPa), and is the hardest compound. The number of electrons transferred from metals to boron atoms and the calculated densities of states (DOS) indicate that each diboride is a complex mixture of metallic, ionic and covalent characteristics. Trends are discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".