Electrochemical Properties of Biobased Carbon Aerogels Decorated with Graphene Dots Synthesized from Biochar
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Carbon aerogels prepared from low-cost renewable resources are promising electrode materials for future energy storage applications. However, their electrochemical properties must be significantly improved to match the commercially used high-carbon petroleum products. This paper presents a facile method for the green synthesis of carbon aerogels (CAs) from lignocellulosic materials and graphene dots (GDs) from commercially available biochar. The produced carbon aerogels exhibited a hierarchical porous structure, which facilitates energy storage by forming an electrical double-layer capacitance. Surprisingly, the electrochemical analyses of the GD-doped carbon aerogels revealed that in comparison to pristine carbon aerogels, the surface doping of GDs enhanced the electrochemical performance of carbon aerogels, which can be attributed to the combined effect from both double-layer capacitance and pseudocapacitance. Herein, we designed and demonstrated the efficacy of a supercapacitor device using our green carbon electrode as a sustainable option. These green carbon aerogels have opened a window for their practical use in designing sustainable energy storage devices.
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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".