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Record W2952235331 · doi:10.82308/13063

Flocculation kinetics of precipitated calcium carbonate induced by functional nanocellulose

2016· article· en· W2952235331 on OpenAlexfundno aff
Dezhi Chen

Bibliographic record

VenueeScholarship@McGill (McGill) · 2016
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaFPInnovationsFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsFlocculationChemistryNanocelluloseCelluloseDynamic light scatteringNanocrystalline materialChemical engineeringInorganic chemistryNuclear chemistryOrganic chemistryCrystallographyNanoparticle

Abstract

fetched live from OpenAlex

ABSTRACTThe interactions between precipitated calcium carbonate (PCC) and electrosterically stabilized nanocrystalline cellulose (ENCC) and dissolved carboxylated cellulose (DCC) have been studied in this thesis. ENCC and DCC usually have a high carboxylate content (3.5 mmol/g or higher) and can be produced by periodate, chlorite and TEMPO oxidations. ENCC/DCC showed a high flocculation efficiency with PCC particles and induced PCC flocculation by a combination of electrostatic and bridging forces. ENCC/DCC induces the maximum PCC flocculation when PCC particles reach to isoelectric point. Novel nanocellulose particles were prepared by periodate oxidation in this study. For partial oxidation (degree of substitution (DS)<2), three products were generated: fibrous cellulose, rod-like dialdehyde cellulose (DAC) nanofibers, which we refer to as sterically stabilized nanocrystalline cellulose (SNCC), and dissolved DAC which we refer to as dialdehyde modified cellulose (DAMC). SNCC has similar dimension (100–200 nm in length and 5–8 nm in width) as conventional nanocrystalline cellulose (NCC) made by sulfuric acid hydrolysis. SNCC was characterized and its properties were compared to NCC. In addition, morphological features and size distributions of three SNCCs prepared by different degrees of oxidation were measured by transmission electron microscopy and dynamic light scattering (DLS). It shows that the three SNCCs have similar diameters (5-10 nm). However, the average length of SNCC decreases with aldehyde content: from approximately 590 nm after 26 hrs of oxidation to 100 nm for an oxidation period of 84 hrs. It indicates that the morphology of SNCC can be well controlled by the degree of periodate oxidation, which depends on the amount of periodate and the reaction time. Based on this observation, we propose that periodate reacts preferentially with the amorphous region of cellulose, followed by proceeding at the boundary of amorphous and crystalline regions. The steric stability of SNCC is proved by DLS when adding cosolvents into aqueous SNCC suspensions. The flocculation of PCC induced by SNCC was also studied. SNCC particles can bridge PCC to induce flocculation at low dosage (above 1mg/g). SNCC induced the maximum flocculation when its fractional coverage was more than half coverage because SNCC particles become unstable after deposition on PCC. Adsorption isotherms of three SNCCs and dialdehyde modified cellulose (DAMC) on PCC particles were measured. It was found that DAMC had a higher affinity than three SNCCs with different aldehyde contents, and the affinity of SNCC increased with reaction time. This indicates DAMC chains adsorb stronger than nanocrystalline parts of SNCC on PCC.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.035
GPT teacher head0.263
Teacher spread0.227 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2016
Admission routes1
Has abstractyes

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