Submonolayer growth of BaTiO3 thin film via pulsed laser deposition: A kinetic Monte Carlo simulation
Bibliographic record
Abstract
Distinguishing with the traditional solid-on-solid model, the adatom bonding is specially considered to describe the atom combined according to the perovskite structure, and the pulsed laser deposition growth of the perovskite thin film on the surface of square lattice substrate of homoepitaxial system is considered as three stochastic incidents such as the deposition, diffusion, and bonding of adatoms. We proposed an energy-dependent kinetic Monte Carlo approach to simulate BaTiO3 thin film growth via pulsed laser deposition within the submonolayer regime, in which the coverage θ is less than 1. In the simulation, first- and second-nearest-neighbor interactions are taken into account by the Born–Mayer–Huggins potential. Varying the values of the laser repetition rate and pulse duration, the relative curves of the island density and island size versus coverage were obtained. The simulation results show that the island density increases, while the island size decreases with the pulse frequency. When the pulse repetition rate is less than 1 kHz, there is no obvious variation for the curves of the island density and island size versus coverage. However, when the pulse repetition rate is larger than 1 kHz, the island density does not change for θ<0.1, and with the pulse duration, the island density increases while the island size decreases for θ>0.1. They are in good agreement with the previous experimental observations. It provides an understanding of the evolution of the morphology of the BaTiO3 thin film in submonolayer growth and a basic exploration of the epitaxial growth process of ionic oxides with perovskite-type structures.
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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 | 0.001 |
| 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 | 0.000 |
| Research integrity | 0.002 | 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".