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Record W4381511369 · doi:10.5267/j.ccl.2023.4.003

Isotherms, kinetics, and thermodynamics of methionine adsorption onto poorly crystalline hydroxyapatite with different Ca/P ratios

2023· article· en· W4381511369 on OpenAlexvenueno aff
Abdelhadi El Rhilassi, Oumaima Oukkass, M. Bennani-Ziatni

Bibliographic record

VenueCurrent Chemistry Letters · 2023
Typearticle
Languageen
FieldMedicine
TopicBiochemical effects in animals
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryAdsorptionPhysisorptionKineticsPoint of zero chargeFreundlich equationLangmuirCrystallinityFourier transform infrared spectroscopyThermodynamicsInfrared spectroscopyIonInorganic chemistryPhysical chemistryChemical engineeringOrganic chemistryCrystallography

Abstract

fetched live from OpenAlex

The adsorption properties of hydroxyapatite of low crystallinity towards methionine have been examined. The chemical composition of hydroxyapatite was taken as an experimental variable in order to have a point of view on the parameters of the adsorption process and the mechanisms established between adsorbent-adsorbate. The adsorption kinetics are relatively fast, and the high amounts adsorbed at saturation are obtained for non-stoichiometric hydroxyapatite, containing more HPO42- ions and having a high specific surface area. The good agreement of the experimental data with kinetic models confirms that the mechanism can be perfectly described by pseudo-second-order kinetics. Adsorption isotherm models show that Langmuir's model gives a better fit of experimental data compared to that of Freundlich, Temkin and Dubinin-Kaganer-Radushkevich. Fourier transform infrared spectroscopy confirmed the interaction between the -COO- ions of methionine and the Ca2+ ions of hydroxyapatite. The thermodynamic parameters, the isoelectric point of methionine and the point of zero charge of hydroxyapatite with different Ca/P ratios show that the adsorption process is considered spontaneous, exothermic and often controlled by physisorption with interactions electrostatic.

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 score0.021
Threshold uncertainty score0.740

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 head0.012
GPT teacher head0.259
Teacher spread0.246 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

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