Thermal analysis of St. John's Wort wastes and biochars: A study of combustion characteristics and kinetics
Bibliographic record
Abstract
St. John's wort, extensively utilized in industries such as food, medicine, and cosmetics, generates substantial biomass waste. Utilizing these wastes is crucial to reducing environmental harm and making an economic contribution. This study aimed to determine the potential of St. John's wort wastes and biochar forms produced from these wastes to be used as solid fuel. In this context, the combustion behavior of the biomass and biochar were determined by thermogravimetric analysis method. Additionally, the Kissenger-Akahira-Sunosa and Flynn-Wall-Ozawa techniques were used to compute the combustion activation energies of these samples. According to the analysis, biomass combustion commenced at approximately 250°C and occurred in two stages, whereas biochar combustion initiated at around 400°C and proceeded in a single stage. Furthermore, over 90% of the mass from both samples was observed to decompose during combustion, with average combustion activation energies ranging between 70.08 and 203.86 kJ/mol for biomass and biochar, respectively. These findings suggest that biomass exhibits more readily combustible characteristics compared to biochar but is less energy efficient. In conclusion, optimizing the biochar production process could enhance its energy efficiency and potentially narrow the performance gap between biomass and biochar. Additionally, further research into alternative methods or additives to improve the energy efficiency of biomass combustion is warranted.
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 | 0.001 |
| 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".