Removal of manganese from water by electrocoagulation: Adsorption, kinetics and thermodynamic studies
Bibliographic record
Abstract
Abstract The present study provides an electrocoagulation process for the removal of manganese (Mn) from water using magnesium as anode and galvanised iron as cathode. The various operating parameters like effect of initial pH, current density, electrode configuration, inter‐electrode distance, coexisting ions and temperature on the removal efficiency of Mn were studied. The results showed that the maximum removal efficiency of 97.2% at a pH of 7.0 was achieved at a current density 0.05 A/dm2 with an energy consumption of 1.151 kWhr/m3. Thermodynamic parameters, including the Gibbs free energy, enthalpy and entropy, indicated that the Mn adsorption of water on magnesium hydroxides was feasible, spontaneous and endothermic. The experimental data were fitted with several adsorption isotherm models to describe the electrocoagulation process. The adsorption of Mn preferably fitting the Langmuir adsorption isotherm suggests monolayer coverage of adsorbed molecules. In addition, the adsorption kinetic studies showed that the electrocoagulation process was best described using the second‐order kinetic model at the various current densities. © 2012 Canadian Society for Chemical Engineering
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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 | 0.000 |
| 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) | 0.000 | 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".