Surface complexation modelling of heavy metal adsorption onto natural clay minerals
Bibliographic record
Abstract
Adsorption of metals onto soil clay fractions is one of the most important chemical processes for heavy metal cations occurring in soil or sediment environment. Traditional Langmuir or Freundlich isotherm approaches do not indicate the adsorption mechanism. Surface Complexation Models (SCM's) describe the adsorption process by treating the sorbent surface as composed of various functional groups and have been successfully applied to oxide minerals. However, results from the application of SCM's for constant charged phyllosilicate clay minerals have not obtained universal consensus due to their complicated structures and surface charge features. The major objective of this thesis is to establish a simple surface complexation adsorption model for heavy metal cations onto natural clay minerals. Three representative clay minerals (kaolinite, illite and montmorillonite) and five soil clay minerals from Canada and China were investigated. The adsorption of five heavy metal cations, Cd(II), Cu(II), Ni(II), Pb(II) and Zn(II), onto the clay minerals were studied by batch adsorption experiments as a function of pH and ionic strength. Results suggested there were two dominant processes involved in the adsorption of the metals: (1) at lower pH values, the adsorption occurred on permanently charged surface sites through outer-sphere ion-exchange reactions; (2) at higher pH values, the adsorption occurred on variable charged mineral edges through specific inner-sphere surface complexation reactions. Changes in ionic strength showed a dramatic effect on the first process but had little effect on the second process. The Constant Capacitance Model was used to describe the electrostatic properties on the variable charged edge sites. A surface adsorption model combining both ion-exchange reactions with surface complexation reactions at the variable charged edge sites could successfully predict the adsorption behaviour of the five metals in various ionic strengths for both pure clay minerals and extracted soil clay minerals. The model scheme could be applied to all the studied clay minerals; however the model parameters, such as the adsorption constants and site densities, were different for case to case because of the wide range of structures and surface charge properties of natural clay minerals from various sources.
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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 | 0.000 | 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".