Slow Pyrolysis as a Method for the Destruction of Japanese Wireweed, Sargassum muticum
Bibliographic record
Abstract
Japanese wireweed, Sargassum muticum is an invasive species to Great Britain, which might be controlled by harvesting it for energy and chemicals. Pyrolysis is the thermal decomposition of the organic components of dry biomass by heating in the absence of air. The distribution of matter between solid, liquid and syngas depends on the biomass and the pyrolysis temperature and time. Slow pyrolysis with lower temperatures (~ 400 oC) tends to produce more solid char. Pyrolysis char can be an effective soil ameliorant, a sequestration agent due to its stability or burned as a fuel. The research attempts to answer the question: Could slow pyrolysis be an energy efficient means for the destruction of Japanese wireweed and produce a potential product, biochar? A simple test rig was developed to establish the yield of biochar, biocrude and syngas from the slow pyrolysis of Sargassum muticum. An energy balance was calculated using compositional data from the analysis of the seaweed feedstock, higher heating values (HHV) from bomb-calorimetry and literature values. The energy required to heat 1 kg of dry seaweed by 400 oC for slow pyrolysis was estimated at 0.5 MJ. The HHV of syngas and biocrude produced from the pyrolysis totalled 2.9 MJ. There is, therefore, sufficient energy in the biocrude and syngas fractions produced by the pyrolysis of seaweed to power the process and produce useful biochar, but insufficient energy for drying.
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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".