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Record W3107006790 · doi:10.3390/min10121054

Synthesis of Polymer Grafted Starches and Their Flocculation Properties in Clay Suspension

2020· article· en· W3107006790 on OpenAlexafffund
Nana Zhao, H. Bitar, Yunyin Zhu, Yuming Xu, Zhiqing Shi

Bibliographic record

VenueMinerals · 2020
Typearticle
Languageen
FieldChemistry
TopicAdvanced Polymer Synthesis and Characterization
Canadian institutionsNatural Resources CanadaNational Research Council Canada
FundersNatural Resources CanadaNational Research Council Canada
KeywordsFlocculationChemical engineeringStarchCationic polymerizationPolymerMaterials scienceGraftingCopolymerMonomerAtom-transfer radical-polymerizationPolymer chemistryChemistryOrganic chemistryComposite material

Abstract

fetched live from OpenAlex

Starch-based flocculants have been emerged as a promising alternative to conventional synthetic flocculants in wastewater treatment, especially for the treatment of oil sand tailings, as they are low cost, safe, biodegradable, fairly shear-stable, readily available from reproducible agricultural resources, and do not result in secondary pollution. In this paper, three types of polymer-grafted starches (St-g-Polymer) with different charge properties were synthesized and their molecular structures were controlled by atom transfer radical polymerization (ATRP). The correlations between the charge properties of starch-based flocculants, external environmental parameters, and flocculation performance were systematically investigated by conducting jar tests under various environmental conditions. It was found that the charge properties of the branch chain had a significant impact on flocculation performance. The cationic St-g-Polymer demonstrated the best performance due to the grafting of the cationic monomer to the starch backbone which improved the solubility of the copolymer and aided in the removal of small/water-soluble particles. The results obtained could assist in guiding the selection and design of suitable biodegradable flocculants when treating targeted wastewater.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.336

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.029
GPT teacher head0.219
Teacher spread0.190 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2020
Admission routes2
Has abstractyes

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