Design of Moisture-Enabled Electric Generators Utilizing sp- and sp<sup>2</sup>-Hybridized Two-Dimensional Carbon Materials: A Minireview and Perspectives
Bibliographic record
Abstract
A moisture-enabled electric generator (MEG), as an emerging green energy collection technique, utilizes nanomaterials, such as the most typical two-dimensional (2D) carbon-based materials, to interact with ubiquitous environmental humidity, directly generating electricity. In a 2D carbon-based MEG, functionalized graphene and graphdiyne (GDY) stand out due to their perfect hexagonal symmetry and unique combination of semiconductor behavior, characterized by hybridization of sp and sp 2 carbon atoms. Researchers are particularly interested in the potential of these materials as moisture-absorbing agents to enhance MEG efficiency and regulate electricity generation performance. This minireview summarizes the impact of factors such as morphology control of carbon-based materials, like graphene and GDY, methods of moisture supply, and electrode design on MEG performance. Subsequently, it discusses MEG applications in fields such as sensing, energy supply, and wearable electronics. Finally, it analyzes the challenges facing MEG development and outlines prospects.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 0.001 |
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".