The removal of inorganic phosphate from water using carboxymethyl cellulose‐iron hydrogel beads
Bibliographic record
Abstract
Abstract BACKGROUND Inorganic phosphate (Pi) is key to improved crop yields; however, agricultural drainage leads to the accumulation of this nutrient in aquatic ecosystems and promotes the formation of harmful algal blooms. The aim of this study was to produce a hydrogel with high binding capacity and affinity towards Pi produced from carboxymethyl cellulose (CMC) and iron (III) chloride (FeCl3). RESULTS CMC was converted to CMC‐Fe composites by incubation with FeCl3. The half‐lives (t1/2) of CMC functionalization with 25 mmol L−1 FeCl3 were 11.56 min (1.5% CMC) and 13.91 min (3.0% CMC). The apparent dissociation constants (KD App) of CMC‐Fe were estimated to be 33.99 μmol L−1 (1.5% CMCFe) and 24.81 μmol L−1 (3.0% CMC‐Fe). The phosphate binding capacity (PBC) of the hydrated hydrogels were 74.0 ± 3.06 mg g−1 (1.5% CMCFe) and 91.4 ± 4.51 mg g−1 (3.0% CMC‐Fe). Laboratory‐scale continuous flow filtration studies showed an average removal of 91.3% (mixed filter) and 52.5% (unmixed filter). Batch type treatment of agricultural drainage showed a reduction in Pi content from 0.40 to 0.11 mg L−1 (1.5% CMC‐Fe) and 0.17 mg L−1 (3.0% CMC‐Fe). The amount of bound‐Pi was 26.7 ± 0.63 μg g−1 (1.5% CMC‐Fe) and 32.8 ± 1.31 μg g−1 (3.0% CMC‐Fe). The iron leached from 1.5% and 3.0% CMC‐Fe beads was 11.98 ± 1.80 and 3.57 ± 1.63 mg g−1, respectively. CONCLUSION The CMC‐Fe hydrogel shows great promise as a Pi‐adsorbing material with applications in the treatment of agricultural drainage. © 2020 Society of Chemical Industry (SCI)
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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".