Surface modification of XSe (X = Cu and Ag) monolayers by grope 1 elements: A metal to semiconductor transition by a first-principles perspective
Bibliographic record
Abstract
Two-dimensional (2D) materials can be effectively functionalized by chemically modified using doping. Very recently, a flat AgSe monolayer was successfully prepared through direct selenization of the Ag(111) surface. Besides, the results indicate that the AgSe monolayer like CuSe, has a honeycomb lattice. Motivated by the experimental outcomes, in this work, employing first-principles calculations, we systematically investigate the electronic and optical properties of AgSe and CuSe monolayers, as well as the impact of alkali metals (Li, Na and K). Without functionalization, both the CuSe and AgSe monolayers exhibit metallic characteristics. The Li (Na)-CuSe and Na (K)-AgSe systems are dynamically stable while, the K- and Li-CuSe and Li-AgSe are dynamically unstable. Interestingly, the functionalized CuSe system with Li and Na atom as well as AgSe with K and Na atom, can open the band gaps, leading to the actualization of metal to semiconductor transitions. Our results show that, the electronic characteristics of the Na-CuSe/AgSe system can be modulated by adjusting the adsorption heights, which gives rise to the change in the electronic properties and the band gap may be controlled. Furthermore, from the optical properties we can find that the K-AgSe system is the best candidate monolayer to absorb infrared radiation and visible light. Consequently, our findings shed light on the functionalization of 2D materials based CuSe and AgSe monolayers and can potentially enhance and motivate studies in producing these monolayers for current nanodevices and future applications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".