Phosphorylating Tannin in Urea System: A Simple Approach for Enhanced Methylene Blue Removal from Aqueous Media
Bibliographic record
Abstract
Tannin, after lignin, is one of the most abundant sources of natural aromatic biomolecules. It has been used and chemically modified during the past few decades to create novel biobased materials. This work intended to functionalize for the first time quebracho Tannin (T) through a simple phosphorylation process in a urea system. The phosphorylation of tannin was studied by Fourier transform infrared spectroscopy (FTIR), NMR, inductively coupled plasma optical emission spectroscopy (ICP-OES), and X-ray fluorescence spectrometry (XRF), while further characterization was performed by scanning electron microscopy/energy dispersive X-ray spectroscopy (SEM/EDX) and thermogravimetric analysis (TGA) to investigate the morphology, composition, structure, and thermal degradation of the phosphorylated material. Results indicated the occurrence of phosphorylation, suggesting the insertion of phosphate-containing groups into the tannin structure, revealing a high content of phosphate for modified tannin (PT). This elevated phosphorus content serves as evidence for the successful incorporation of phosphate groups through the functionalization process. The corresponding PT and T were employed as adsorbents for methylene blue (MB) removal from aqueous solutions. The results revealed that the Langmuir isotherm model effectively represents the adsorption isotherms. Additionally, the pseudo-second-order model indicates that chemisorption predominantly controls the adsorption mechanism. This finding also supports the fact that the introduced phosphate groups via the phosphorylation process significantly contributed to the improved adsorption capacity. Under neutral pH conditions and at room temperature, the material achieved an impressive adsorption capacity of 339.26 mg·g –1 in about 2 h.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".