Mechanical, Chemical, and Physical Properties of Wood and Perennial Grass Biochars for Possible Composite Application
Bibliographic record
Abstract
Miscanthus, switchgrass, and softwood chip biochars, produced by slow pyrolysis, were characterized to evaluate their properties in light of potential alternative and novel applications. This work investigated specific physical and chemical properties of biochars that have not been previously reported. Atomic force microscopy (AFM), moisture absorption, and electrical and thermal analysis were conducted to demonstrate the mechanical, physical, and chemical properties of biochars. In addition, elemental analysis, specific surface area, Fourier transform infrared in the attenuated total reflectance (FTIR-ATR), and X-ray diffraction were performed. The state-of-art quantitative nano-mechanical measurement yielded a modulus of elasticity of approximately 10 GPa for the wood chip biochar, while the grass-based samples exhibited a comparatively lower modulus of approximately 5 GPa. In addition, the pore blocking phenomenon by water molecules was identified as a cause for atypical behavior of the biochars’ moisture absorptions, resulting in wood chip biochar having the lowest equilibrium moisture content of 6.2 wt.%. Results from electrical and thermal conductivity measurements demonstrated relatively lower values in comparison to carbonized biomass.
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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".