Thermal and mechanical characteristics of local firewood species and resulting charcoal produced by slow pyrolysis
Bibliographic record
Abstract
Abstract The main source of fuel for domestic cooking applications in Sub-Saharan Africa is either locally available firewood species or charcoal produced by slow pyrolysis of these species. However, very few studies exist that characterize and quantify physical properties, burning rates, peak temperatures, and calorific values of typical firewood species and resulting charcoal fuels produced by slow pyrolysis. This study evaluated the mechanical and thermal properties of firewood and charcoal from five tree species namely:Dichrostachys cinerea,Morus Lactea,Piliostigma thonningii,Combretum molle, andAlbizia grandibracteata. Characterization was done by scanning electron microscopy, thermogravimetric analysis, bomb calorimetry, Fourier transform infrared spectroscopy, bulk density measurements, and durability, water boiling and absorption tests. SEM images showed the development of macropores on charcoal after slow pyrolysis. Peak temperatures during firewood and charcoal combustion ranged between 515.5–621.8 °C and 741.6–785.9 °C, respectively. Maximum flame temperatures ranged between 786.9–870.8 °C for firewood and 634.4–737.3 °C for charcoal. Bulk densities and calorific values of charcoal species were higher than those for firewood species. Drop strengths for firewood were all 100% while for charcoal were between 93.7 and 100%. Water boiling tests indicated that firewood fuel performed better that charcoal fuel for low amounts of water due to higher maximum flame temperatures obtained during combustion of firewood.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".