Modeling Exsolution of Pt from ATiO<sub>3</sub> Perovskites (A = Ca/Sr/Ba) Using First-Principles Methods
Bibliographic record
Abstract
Exsolution of transition metals from host perovskites has emerged as a unique synthesis method for designing catalysts for energy applications. Here, using accurate first-principles density functional theory, coupled with an ab initio steered molecular dynamics and umbrella sampling framework, we rationalize both the energetics as well as the dynamics of the exsolution process of a quintessential system: Pt-doped ATiO 3 (A = Ca/Sr/Ba) perovskites and identify the major driving forces for Pt exsolution. From the developed ab initio thermodynamic framework, we find that Pt exsolution from ATiO 3 (A = Ca/Sr/Ba) perovskites has a distinct host-perovskite facet dependence and likely proceeds through sub-surface vacancy formation followed by diffusion of the doped Pt to the surface of the host perovskite. The molecular dynamics simulations reveal that the exsolution process has a clear temperature and host-perovskite dependence, establishing that only specific dopant-host perovskite combinations at favorable thermophysical conditions result in the catalyst with the novel properties. This opens new paths for the predictive synthesis of intelligent catalysts.
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".