Strain-induced enhancement of surface self-diffusion on strontium titanate (001) surfaces
Bibliographic record
Abstract
Abstract We present a numerical investigation of self-diffusion on strontium titanate TiO2-terminated (001) surfaces via density functional theory. Our calculations first indicate that Ti has the highest diffusion barrier with approximately 2.20 eV, thus representing the rate-limiting step for surface self-diffusion. Furthermore, the higher energy barriers of O and Ti in comparison to O2 and TiO2 indicate electronic activity with the surface atoms. Under the consideration of equi-biaxial strain as it would be encountered in e.g. heteroepitaxial thin films, the diffusion barriers for surface self-diffusion decrease for both compressive and tensile strains between −6% and 2%. For larger strains, we observe plastic deformations. This possibility to lower the energy barrier paves the way for accelerated and possible new mechanisms of surface diffusion and reconstruction of strontium titanate structures in a wide range of applications.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| 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".