Copper Adsorption with Pb and Cd in Sand-Bentonite Liners under Various pHs. Part II. Effect on Adsorption Sites
Bibliographic record
Abstract
The project examined the effect of Pb and Cd on Cu adsorption using sand liners containing 0, 5, and 10% sodium bentonite and exposed to metal solutions at three pH levels (3.7, 5.5, and 7.5). Aliquots of 2 g of liner material were exposed in duplicate, for 14 days, to solutions containing Cu alone or Cu with either Pb or Cd. Selective sequential extraction (SSE) was used to quantity the Cu adsorbed by each liner particle adsorption site (exchangeable, carbonate and hydroxide, oxides and residual). The results indicated that two main factors affected liner material behavior in adsorbing Cu, besides Cd and Pb competition: pH either above or below 6.5; liner cation exchange capacity (CEC) greater or equal and greater than the solution cation equivalence. In general, the liner carbonate and hydroxide fractions precipitated the greatest amount of Cu, under all environmental conditions while the exchangeable, oxide and residual adsorbed more or less the same amount. Lead, and to a lesser extent Cd, significantly increase the mobility of Cu, by competing especially for the exchangeable sites. While Cd also competed against Cu for oxide adsorption, Pb competes for calcium and hydroxide precipitation. Lead, and to a lesser extent Cd, competed especially for the exchangeable site where the adsorption is more dynamic, and less for the more permanent adsorption sites, involving precipitation, and electrostatic bonding.
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) | 0.001 | 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".