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Record W1942757787 · doi:10.1139/s08-049

Dissolution kinetics of struvite pellets grown in a pilot-scale crystallizerA paper submitted to the Journal of Environmental Engineering and Science.

2009· article· en· W1942757787 on OpenAlexafffundvenue
M. Iqbal H. Bhuiyan, D. S. Mavinic, Roger Beckie

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicPhosphorus and nutrient management
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDissolutionStruvitePelletsKineticsCrystallizationChemical engineeringChemistryMaterials scienceMineralogyPhosphateComposite materialOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

Dissolution kinetics of struvite are important for optimizing intentional struvite crystallization, as well as for ensuring the efficient use of the crystallized products. Dissolution experiments were carried out for struvite pellets grown in a pilot-scale fluidized bed reactor. To determine the kinetics and mechanism of the dissolution process in a batch reactor system, two different theoretical models were tested. The experimental values were found to fit well with both models. In a mixed flow-through reactor system, the constituents release became stoichiometric when the input solution had an alkaline pH. The dissolution rates for struvite pellets were found to decrease with increasing pH due to proton promoted dissolution. After a transition from around 7.5 to 8, the rate of dissolution increased with the increase in pH, because of the hydroxyl promoted dissolution.

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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.003
GPT teacher head0.156
Teacher spread0.153 · 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

Citations14
Published2009
Admission routes3
Has abstractyes

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