Kinetics and isotherm studies for the adsorption of boron from water using titanium dioxide
Bibliographic record
Abstract
Abstract Boron is a necessary element for plants that are generally found in the ground and seawater, but it can also be poisonous in large doses. Contamination of water with boric acid or borate ions is a global concern. Due to the absence of the chemical charge that boron possesses, its removal is often difficult. To investigate boron's adsorption characteristics, kinetic, isotherm, and isothermal studies were performed. The adsorption of boron was shown to be a pH‐dependent mechanism, with the best results at around pH 9.0. About 47% of the boron from a solution of 50 mg L −1 was removed using 5 g titanium dioxide in 30 min. It was also demonstrated that boron adsorption kinetics increased with temperature, which is best described by the pseudo‐second‐order kinetic model ( R 2 > 0.98) and also fits well with Elovich and pseudo‐first‐order models ( R 2 > 0.94) at pH 9.0. Equilibrium was reached in about 40 min for all the samples. The film boundary layer diffusion step limits the rate. Experimental results correspond well to the Freundlich isotherm ( R 2 = 0.95–0.99). Langmuir and Temkin's isotherms also fitted reasonably well ( R 2 = 0.94–0.98). The Freundlich and Langmuir constants indicate favourable adsorption. The Gibbs free energy (ΔG) values increased negatively (from −11.47 to −15.63 kJ mol −1 ) with increasing temperature, signifying a feasible and spontaneous process. The enthalpy change (ΔH) value of about 30.35 kJ mol −1 indicated endothermic physical adsorption. The results indicate that titanium dioxide is an excellent and safe adsorbent for the removal of boron from water.
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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".