MétaCan
Menu
Back to cohort
Record W2005393991 · doi:10.5539/ijc.v2n2p44

Poly(Furfural-Acetone) as New Adsorbent for Removal of Cu(II) from Aqueous Solution: Thermodynamic and Kinetic Studies

2010· article· en· W2005393991 on OpenAlexvenueno aff
Tariq S. Najim, Suhad A. Yassin, Ali J. Majli

Bibliographic record

VenueInternational Journal of Chemistry · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicAdsorption and biosorption for pollutant removal
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryPhysisorptionAdsorptionEndothermic processAqueous solutionKinetic energySorptionFurfuralAcetoneActivation energyInorganic chemistryThermodynamicsPhysical chemistryOrganic chemistryCatalysis

Abstract

fetched live from OpenAlex

Poly(furfural-acetone) was prepared and used for the removal of Cu(II) from aqueous solution. The optimum pHfor the removal was found to be 6. The adsorption kinetic of Cu(II) was studied, and the rates of sorption werefound to conform to Pseudo–Second-order kinetic with a correlation coefficient (R2=1), results indicate that thepH 6 of the system supported the adsorption of Cu(II) on PFA, which involve higher negative value of ?Go. Onthe other hand, the degree of spontaneity of the reaction increases with increasing temperature for allconcentrations of Cu(??). The positive values of ?H° reveals, the endothermic nature of the process and its valuelie in the range of physisorption. It was also observed that the randomness increases at the solid-solutioninterface from the positive values of ?S°. Estimation of sticking probability S* values reveal that the process isfavorable due to low value of S*(S*<1). Activation energy Ea values were consistent with values of ?H° bothare positive and their values lie in the range of physisorption.

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)0.0000.000

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 head0.013
GPT teacher head0.274
Teacher spread0.261 · 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

Citations5
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of ChemistrySame topicAdsorption and biosorption for pollutant removalFrench-language works237,207