Novel aluminium (hydr) oxide-functionalized activated carbon derived from Raffia palm (Raphia hookeri) shells: Augmentation of its adsorptive properties for efficient fluoride uptake in aqueous media
Bibliographic record
Abstract
In this study a novel activated carbon derived from Raffia palm shells was synthesized firstly by activating the precursor with phosphoric acid to produce Raffia Palm Shell Activated Carbon (RPSAC) and further functionalized by coating its surface with aluminium hydroxide to produce a composite called Aluminium Oxide-coated Raffia Palm Shell Activated Carbon (ACRPSAC). These adsorbents were extensively characterized and tested for fluoride adsorption in aqueous media using batch adsorption experiment in comparison with a commercially available activated carbon (CAC). ACRPSAC demonstrated excellent qualities and fluoride adsorption capacity as compared to RPSAC. SEM/EDX revealed that ACRPSAC developed both micro and meso-pores on its surface with BET-surface area and pore volume of 715.80 m2/g and 0.47 cm3/g respectively. FTIR and XRD proved that ACRPSAC was largely amorphous and had sufficient functionality for fluoride uptake in solution. Batch adsorption studies showed that the fluoride removal abilities were in the order of ACRPSAC > RPSAC > CAC with maximum Langmuir adsorption capacity of 4.10 > 2.26 > 2.24 mg/g. respectively. The experimental data was well described by the Langmuir (R2 = 0.8802–0.9751) and the pseudo-second order kinetic (R2 = 0.9974–0.9999) models, signifying that fluoride uptake by the adsorbents was a chemisorption process. Thermodynamic studies revealed that the process was spontaneous, endothermic and feasible for ACRPSAC and RPSAC but was non-spontaneous for CAC. It was concluded that ACRPSAC is an excellent activated carbon for eliminating fluoride from groundwater and can be further studied for its commercialization.
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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) | 0.001 | 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".