Perovskenes: two-dimensional perovskite-type monolayer materials predicted by first-principles calculations
Bibliographic record
Abstract
are at least meta-stable, as confirmed by cohesive energy calculations, evaluation of elastic constants, and simulation of phonon dispersion modes. With this information, we proceeded to investigate the electronic, optical, and thermoelectric properties of these perovskenes. To gain insight into their promising applications, we investigated the electronic and optical properties of these 2D materials and found that they are wide bandgap semiconductors with significant absorption and reflection in the ultraviolet (UV) region of the electromagnetic field, suggesting them as promising materials for use in UV shielding applications. In addition, evaluating their thermoelectric factors revealed that these materials become better conductors of electricity and heat as the temperature rises. They can, hence, convert temperature gradients into electrical energy and transport electrical charges, which is beneficial for efficient power generation in thermoelectric devices. This work opens a new window for designing a novel family of 2D perovskite type materials termed perovskenes. The vast variety of different perovskite compounds and their variety of applications suggest deeper studies on the perovskenes materials for use in innovative technologies.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".