Metal to semiconductor switching in the AgTe monolayer <i>via</i> decoration with alkali metal and alkaline earth metal atoms: a first-principles perspective
Bibliographic record
Abstract
In this work, employing first-principles calculations, we systematically investigate the atomic structure and electronic and optical properties of the AgTe monolayer, as well as the impact of alkali metal (Li, Na, K) and alkaline earth metal (Be, Mg, Ca) atoms decoration. The AgTe monolayer exhibits metallic characteristics. When Li, Na, K, and Mg atoms are decorated on the AgTe monolayer, the decorated AgTe monolayers are dynamically stable. In contrast, with Be and Ca atoms, the decorated structures are found to be dynamically unstable. Interestingly, the decoration of Li, Na, and K atoms into the AgTe monolayer can open the band gaps in the decorated Li-, Na- and K-AgTe monolayers around the Fermi level, leading to the actualization of metal-to-semiconductor transitions. In contrast, the decorated Mg-AgTe monolayer maintains its metallic characteristic. The highest electron and hole mobilities are achieved in the Na-AgTe monolayer among the decorated structures, suggesting the applicability of this structure in photovoltaic applications. The optical study shows that Li-, Na- and K-decorated AgTe monolayers have improved light absorption in the visible light region. Consequently, our findings shed light on the decoration of these 2D material monolayers and can potentially enhance and motivate studies in producing these monolayers for current nanodevices and future 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".