Efficiency of band edge optical transitions of 2D monolayer materials: A high-throughput computational study (workflows)
Bibliographic record
Abstract
This archive contains supporting information for the manuscript "Efficiency of Band-Edge Optical Transitions in 2D Monolayer Materials: A High-Throughput Computational Study." The files provided enable full reproduction of the results presented in the paper. All calculations were performed using VASP version 6.4.0, except for the GW-BSE calculations, which were carried out with VASP version 6.5.0. In addition, the archive includes a CSV file summarizing key results for the top-performing direct band gap monolayer materials. The file contains the polarization-averaged momentum matrix elements $|p|^2$ at 300 K (see Eq. 3 in https://doi.org/10.48550/arXiv.2409.18287), along with information such as $k$-point coordinates, PBE+SOC band gaps, space group, energy above the convex hull, and database identifiers (DOI, COD, and C2DB).
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.046 | 0.008 |
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".