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Record W4306766510 · doi:10.3390/min12101312

Recovery of Lead (II) Ions from Aqueous Solutions Using G-26 and MTS9570 Resins with Sulfonic/Phosphonic Functional Groups

2022· article· en· W4306766510 on OpenAlexafffund
Salem Elfeghe, Qiuyue Sheng, Abbas Mamudu, Lesley James, Yahui Zhang

Bibliographic record

VenueMinerals · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicAdsorption and biosorption for pollutant removal
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of CanadaMemorial University of Newfoundland
KeywordsEndothermic processAdsorptionAqueous solutionIon-exchange resinChemistryLangmuirIon exchangeFreundlich equationNuclear chemistryIonInorganic chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

This study presents Pb(II) recovery/removal from water solutions using two different commercial ion-exchange resins, i.e., Dowex G-26 with sulfonic functional group and Puromet™ MTS9570 with sulfonic and phosphonic functional groups. Overall, 100% Pb(II) recovery/removal by both resins was obtained at solution pH 3.5, resin dosage 25 g/L, adsorption time 30 min, room temperature, and initial Pb(II) concentration 1000 mg/L. Langmuir, Freundlich, and Temkin isotherms were used to model the experimental data. The mechanism of the adsorption process was investigated using kinetic and thermodynamic models. The experimental data fitted very well with the pseudo-second-order kinetic model, and thermodynamic analysis showed that the adsorption of Pb(II) from acidic solution onto both resins was a spontaneous and endothermic process in nature. Regeneration of the resins loaded with lead ions was tested for three cycles to evaluate the resin recyclability. Good stability of G-26 and performance degradation of MTS9570 resin was observed.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.900
Threshold uncertainty score0.995

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.026
GPT teacher head0.208
Teacher spread0.182 · 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.

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 routes2
Has abstractyes

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