Utilization of Arecanut «(Areca catechu)» husk for gasification
Bibliographic record
Abstract
Gasification of areca husk was studied in this research.The husk is an agricultural by-product of Arecanut (Areca catechu) that could be a potential energy source for the processing of the nut.The problem of slagging during arecanut gasification was investigated using a throat-less, lab-scale downdraft gasifier.The effect of air flow rates from 0.001 to 0.006 m 3 /s on slag formation was studied.With increase of air flow rate, the clinker formation was found to increase (r 2 = 0.7191).Subsequent studies consisted of washing the husk to remove external contaminants picked up during sun drying of the husk on ground.Husk samples were washed using water and were gasified to study the slag formation.Statistical analysis of clinker formation between washed and unwashed samples showed that the variation was significant.Ash and clinkers constituents were analyzed and their composition showed typical elements and oxides enhancing deposition problems.The alkali index calculated from ash composition indicates that slagging is practically certain to occur during thermochemical conversions of areca husk.
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 | 0.000 | 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".