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Record W4225254772 · doi:10.3390/ma15093253

Snail Based Carbonated-Hydroxyapatite Material as Adsorbents for Water Iron (II)

2022· article· en· W4225254772 on OpenAlexaff
Bernard Owusu Asimeng, Edward Kwame Amenyaglo, David Dodoo‐Arhin, J.K. Efavi, Bright Kwakye-Awuah, Elvis K. Tiburu, E. Johan Foster, Jan Czernuska

Bibliographic record

VenueMaterials · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicAdsorption and biosorption for pollutant removal
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAdsorptionFreundlich equationLangmuirLangmuir adsorption modelChemistryRaman spectroscopyChemical engineeringMaterials scienceNuclear chemistryInorganic chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Carbonated hydroxyapatite (CHAp) adsorbent material was prepared from Achatina achatina snail shells and phosphate-containing solution using a wet chemical deposition method. The CHAp adsorbent material was investigated to adsorb aqua Fe(II) complex; [Fe(H2O)6]2+ from simulated iron contaminated water for potential iron remediation application. The CHAp was characterized before and after adsorption using infrared (IR) and Raman spectroscopy. The IR and the Raman data revealed that the carbonate functional groups of the CHAp adsorbent material through asymmetric orientation in water bonded strongly to the aqua Fe(II) complex adsorbate. The adsorption behaviour of the adsorbate onto the CHAp adsorbent correlated well to pseudo-second-order kinetics model, non-linear Langmuir and Freundlich model at room temperature of a concentration (20–100 mg L−1) and contact time of 180 min. The Langmuir model estimated the maximum adsorption capacity to be 45.87 mg g−1 whereas Freundlich model indicated an S-type isotherm curvature which supported the spectroscopy revelation.

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 score0.001
Threshold uncertainty score0.002

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 head0.008
GPT teacher head0.213
Teacher spread0.206 · 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

Citations7
Published2022
Admission routes1
Has abstractyes

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