Two-Dimensional δ-Be<sub>2</sub>C with Hepta-Coordinated Carbons: A Highly Stable Direct-Band-Gap Semiconductor Predicted by First-Principles Calculations
Bibliographic record
Abstract
The theoretical design of novel materials exposes new properties and applications and, in many cases, yields deeper insights and offers promising targets for experimental exploration. Inspired by the successful synthesis of an atomically well-defined borophene polymorph beyond the single-atomic-layer (SL) limit, in this work, by conducting extensive density functional theory (DFT) computations, a novel two-dimensional (2D) inorganic material, 2D δ-Be 2 C, is discovered. In a unit cell of the proposed 2D δ-Be 2 C monolayer, there are six atoms: four berylliums and two carbons. In this 2D monolayer structure, each carbon atom binds to seven beryllium atoms, while each beryllium binds to three carbons forming a double-layer 2D structure. Based on our calculations, the predicted 2D δ-Be 2 C shows good energetic, dynamic, thermal, and mechanical stability. 2D δ-Be 2 C is much lower in energy than all other reported 2D Be 2 C structures. Moreover, it shows better formation energy than all Be x C y monolayer structures, which suggests its high potential for being synthesized experimentally. Based on our calculations, 2D δ-Be 2 C is a semiconductor with a strain-tunable moderate Γ-point direct band gap of about 2.12 eV calculated with a hybrid functional. Furthermore, this material has good absorption properties for visible light. As a direct-band-gap semiconductor with tunable electrical and optical properties, 2D δ-Be 2 C is promising for use in electronics applications, especially in hydrogen production by water splitting and for optical sensors. Moreover, the interesting results of this study suggest deeper investigation to find new 2D materials in double-layer structures as a possible way to reach stable 2D binary materials in the laboratory as has been successfully conducted in double-layer borophene synthesis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".