First-Principles Investigation on the Adsorption and Diffusion of Oxygen at the B2(110)–O(001) Interface in Ti2AlNb Alloys
Bibliographic record
Abstract
The adsorption and diffusion of oxygen at the B2(110)[1¯11]||O(001)[11¯0] interface in Ti2AlNb alloys were investigated via first-principles calculations. Only a 2.6% interfacial mismatch indicates that B2(110)–O(001) is basically a stable coherent interface. The calculated adsorption energies and diffusion energy barriers show that oxygen prefers to occupy the Ti-rich interstitial sites, and once trapped, it hardly diffuses to other interstitial sites, thus promoting the preferential formation of Ti oxides. Under the premise of a Ti-rich environment, a Nb-rich environment is more favorable for oxygen adsorption than an Al-rich environment. The electronic structures suggest that O 2p orbitals mainly occupy the energy region below −5 eV, bonding with its coordinated atoms of Ti, Al, and Nb. However, Al 3p and Nb 4d orbitals near the Fermi level couple with sparsely distributed O 2p orbitals, forming anti-bonding, which is not conducive to oxygen adsorption. Because Nb 4d electrons are more localized than Al 3p electrons are, Nb–O anti-bonding is weaker. O–Ti has almost no contribution to anti-bonding, suggesting good bonding between them. This is consistent with the experimental observations that TiO2 is the main oxidation product.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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 | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".