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Record W2736604616 · doi:10.3390/min7080129

Carbonate Apatite Precipitation from Synthetic Municipal Wastewater

2017· article· en· W2736604616 on OpenAlexaff
Jessica Ross, Lu Gao, Orysia Meouch, Essie Anthony, Divya Sutarwala, Helina Mamo, Sidney Omelon

Bibliographic record

VenueMinerals · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicPhosphorus and nutrient management
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsApatiteCarbonateCalcitePhosphateChemistryMineralogyInorganic chemistryNuclear chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

An important component of phosphorite (phosphate rock) is carbonate apatite, as it is required for phosphorous fertilizer production due to its increased phosphate solubility caused by carbonate substitution in the apatite mineral lattice. High phosphate concentrations in municipal wastewater treatment plants are commonly reduced by precipitating iron phosphate by addition of iron chloride. We investigated the possibility of precipitating carbonate apatite from a potential range of phosphate concentrations that could be available from municipal wastewater treatment plants with anaerobic digestion reactors (5 mM–30 mM). Synthetic phosphate solutions at neutral pH were mixed in batch experiments with a calcium carbonate solution produced by dissolving calcite in contact with carbon dioxide gas, with and without carbonate apatite seed. Batch experiments were used to identify the carbonate apatite supersaturation ranges for homogeneous and heterogeneous nucleation, and the precipitates analyzed with Raman spectroscopy, powder X-ray diffraction, inorganic carbon coulometry, and scanning electron microscopy. Some precipitates contained carbonate weight fractions within the range reported for geological phosphate rock (1.4–6.3 wt %). The precipitates were spherical, poorly crystalline carbonate apatite, suggesting an amorphous precursor transformed to a poorly crystalline carbonate apatite without changing morphology.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.628
Threshold uncertainty score1.000

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)0.0020.001

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 head0.015
GPT teacher head0.236
Teacher spread0.220 · 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; both teacher heads agree on what is shown here.

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

Citations4
Published2017
Admission routes1
Has abstractyes

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