N-, B-, P-, Al-, As-, and Ga-graphdiyne/graphyne lattices: first-principles investigation of mechanical, optical and electronic properties
Bibliographic record
Abstract
Graphdiyne and graphyne are carbon-based two-dimensional (2D) porous atomic lattices with outstanding physics and excellent application prospects for advanced technologies, like nanoelectronics and energy storage systems. During the last few years, B- and N-graphdiyne nanomembranes were experimentally realized. Motivated by the latest experimental advances, in this work, we predicted novel N-, B-, P-, Al-, As-, and Ga-graphdiyne/graphyne 2D lattices. We then conducted density functional theory simulations to obtain the energy minimized structures and explore the mechanical, thermal stability, electronic and optical characteristics of these novel porous nanosheets. The acquired theoretical results reveal that the predicted carbon-based lattices are thermally stable. It was moreover found that these novel 2D nanostructures can exhibit remarkably high tensile strengths or stretchability. The electronic structure analysis reveals a semiconducting electronic character for the predicted monolayers. Moreover, the optical results indicate that the first absorption peaks of the imaginary part of the dielectric function for these novel porous lattices along the in-plane directions are in the visible, IR and near-IR (NIR) ranges of light. This work highlights the outstanding properties of graphdiyne/graphyne lattices and recommends them as promising candidates in the design of stretchable energy storage and nanoelectronics systems.
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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 | 0.000 |
| 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".