Equilibrium and thermodynamic study of trichloroethylene adsorption on activated carbon in a fluidized bed and its thermal regeneration
Bibliographic record
Abstract
Abstract Volatile organic compounds (VOC), used as solvents in industries, are major sources of air pollution. Trichloroethylene (TCE) is a chlorinated VOC widely used in industries. TCE vapours are toxic in nature and adversely affect human health and the surrounding environment when exposed over the threshold limit value for a long duration. Adsorption of TCE vapours using activated carbon as an adsorbent in a fluidized bed and its thermal regeneration is a viable, effective, and economic technology for its separation from air. However, before designing such a system, the equilibrium and thermodynamic study of the adsorption of TCE vapour on activated carbon is important. In this study, the dynamic adsorption of TCE vapour was carried out in a fluidized bed using nitrogen as the carrier gas. The effect of operating conditions, including particle size of activated carbon (212–710 μm), flowrate of nitrogen (carrier gas), adsorption temperature (303–353 K), and the concentration of TCE vapour in nitrogen at the inlet (25–85 mg/L) on the adsorption capacity of TCE on the fluidized bed of activated carbon, was examined. The experimental results obtained were analyzed using the Langmuir and Freundlich adsorption isotherms. The thermodynamic study showed that the adsorption of TCE was spontaneous, exothermic, and physical in nature. The effect of regeneration temperature and purge gas flowrate on the renewal of used activated carbon was also studied.
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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".