Spectroscopic studies of vanadium biosorption on different types of carbohydrate biomass
Bibliographic record
Abstract
The biosorption potential of different types of carbohydrate biomass is investigated to evaluate their application to purify water contaminated by vanadium in environmentally relevant oxidation states (VIV and VV). Spectroscopic studies were done by electron paramagnetic resonance (EPR), vanadium nuclear magnetic resonance (51V NMR), circular dichroism (CD), and electronic absorption in the visible range (vis). Both d-galacturonic and d-glucuronic acids are major components of plant cellular wall polysaccharides. The interaction of VIV with the model ligands d-galacturonic and d-glucuronic acids showed that complexation starts at low pH values (pH 3) and that carboxylate and sugar–OH groups, as well as water molecules, are involved in the coordination. At pH > 4.5, coordination promotes the sugar–OH deprotonation and new species form with the ligand chelating the metal ion via oxygen atoms of carboxylate and of adjacent sugar–O− donors. The studies with pectin and citric acid show the ability of both compounds to partially reduce VV to VIV in solution and the EPR parameters suggest coordination of carboxylate, sugar–OH, and water molecules. The interaction of VV with biomass from different sources shows that grapefruit, orange peel, and plane tree fruit are the most suitable candidates for the biosorption of vanadium. Studies with VV and grapefruit (or the grainless stalk of corn) indicate that the reduction takes place at the “surface” of the solid. EPR studies on the interaction of VIV with different carbohydrate biomass show their ability to complex high amounts of VIV. We propose that the biosorption mechanism, when the biomass is in contact with VV species, involves sorption, reduction, and retention at the surface level of VIV coordinated by oxygen donors of the biomass. When the interaction starts with VIV, the main process just involves the uptake of the metal ion at the surface level.
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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".