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Record W3217495553 · doi:10.1002/ces2.10114

Carbonated hydroxyapatite‐assisted visible light degradation of methylene blue

2021· article· en· W3217495553 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Ceramic Engineering & Science · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMethylene blueReaction rate constantNuclear chemistryVisible spectrumChemistryScanning electron microscopeSpectroscopyAnalytical Chemistry (journal)Materials scienceMineralogyKineticsChromatographyOrganic chemistryPhotocatalysisComposite materialPhysics

Abstract

fetched live from OpenAlex

Abstract Carbonated hydroxyapatite (CHAp) material was prepared from calcite and phosphate‐containing solution using the wet chemical precipitation method. The CHAp material was used to remove methylene blue (MB) from simulated contaminated water and further degraded the MB with the help of visible light (VL). The structure of the CHAp was characterized using X‐ray diffractometry, infrared spectroscopy, Branuer–Emmett–Teller analysis, and scanning electron microscopy, while the energy bandgap, E g , reaction rate constant and MB removal/degradation efficiencies were studied using UV‐Vis spectroscopy. The characterization data revealed that the CHAp was a type‐B carbonate‐substituted hydroxyapatite material with a nonmicroporous network with an E g of 2.26–2.82 eV. The E g allowed VL entrapment that resulted in reactive free radicals that degraded the MBs in the CHAp. The reaction rate constant, K , and removal efficiencies, R , were modeled using the exponential decay function and descriptive statistics (DS), respectively. In close approximation, the K values of the reaction under VL were doubled when compared to the reaction under dark conditions. Under dark and under VL efficiencies, the DS showed a negative and zero skewness for MB removal by CHAp, respectively. The findings show that VL exposure on the CHAp causes a faster reaction rate constant and a higher MB removal efficiency within the time constraints, which would revolutionize dye removal from water industries in terms of cost‐effectiveness.

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.

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 score0.125
Threshold uncertainty score0.326

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.011
GPT teacher head0.259
Teacher spread0.248 · 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