Bibliographic record
Abstract
The dynamics of copper and zinc biosorption by Sargassum fluitans was analyzed under variable column operating conditions including different column lengths (15 and 45 cm), metal-feed solution concentrations (1 and 6 meq L(-1)), metal-sorbent affinities (2.01 and 0.45), and interstitial velocities (12 and 4 cm min(-1)). The experimental breakthrough curves obtained under these varying conditions were also simulated using a mathematical model taking into account the mass transfer as well as the axial dispersion phenomena. The column performance was evaluated using two performance indicators: the service time (t(s)) and the unused portion of the column as reflected in the area under the breakthrough curve (A(c)). Sensitivity analysis results indicated that the feed stream concentration, mass transfer coefficient, column length, and interstitial velocity had the most important effect on the column performance. Applying chromatography theories, the optimization of the biosorption process for productivity and sorption performance, in terms of operating conditions (interstitial velocity) and design parameters (column length), was outlined. The corresponding optimum curve relating the interstitial velocity and the column length resulted with the pressure drop limitations recognized. As an example, a laboratory column 100 cm long will necessitate an interstitial velocity of 19 cm min(-1) to yield the best sorption results.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".