Synthesis and characterization of novel nitrogen doped biocarbons from distillers dried grains with solubles (DDGS) for supercapacitor applications
Bibliographic record
Abstract
Nitrogen doped biocarbon materials were effectively synthesised from distiller's dried grains with solubles (DDGS) using urea as the nitrogen source. The use of urea in the pre-treatment of DDGS on the fixation of elemental nitrogen in the biocarbon materials was investigated. Urea addition increases the nitrogen content in the obtained biocarbon, which is found to have 9.28 ± 0.67% for the DDGS:Urea weight ratio of 1:3. Physicochemical properties of the intrinsic and nitrogen doped biocarbon material were investigated by employing Raman and BET surface area analysis. Nitrogen rich biocarbon obtained using the DDGS:Urea weight ratio of 1:3 was taken for the fabrication of an electrochemical double layer capacitor. The fabricated symmetric supercapacitor with 2-electrode configuration showed the specific capacitance of 49.7 F·g−1 and 100.7 F·g−1 respectively for the intrinsic and nitrogen doped carbon materials at a current density of 0.5 A·g−1.
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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) | 0.000 | 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 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".