2D-3D electron transfer functions and stability of sustainable graphitic biocarbon for bipolar plate application
Bibliographic record
Abstract
Biocarbon being a highly demanding renewable source of carbon is important for many applications such as soil enrichment, electronic applications, etc. In this research, sustainable waste biomass-to-energy materials conversion, kinetic, thermodynamic and electronic properties of carbonized forest biomaterials were investigated to evaluate their high-potential in bipolar plate for fuel cell application. In thermogravimetric analysis, the lignin biocarbon showed the least activation energy of 95 KJ/mol compared to 127 and 145 KJ/mol for hardwood and softwood biocarbons respectively. The crystallographic nature of carbonized ligneous and cellulosic biomaterials was also investigated, showing its intrinsic properties and exotic functionality through semi-metallic properties determined from density function theory, transmission electron microscopy and UV–Vis absorption. Finally, the electrochemical properties of bio-carbon composites were examined to prove stability and corrosion resistance comparable to metallic plates. Biocarbon composites showed high polarization resistance up to 5.96 kΩ-cm 2 with non-reactive properties, favorable to use in bipolar plates as an alternative to metallic plate which is expensive and prone to corrosion. Overall, sustainable biocarbon shows its ability as a high-performance functional material alternative to expensive nanofillers as well as to enhance the attributes of the bipolar plate composite by increasing connectivity between primary filler and insulating resin.
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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) | 0.002 | 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".