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Determination of Thermodynamic Parameters of Zinc (II) Adsorpton on Pulp Waste as Biosorbent

2014· article· en· W2048447099 on OpenAlexaff
Panida Sampranpiboon, Pisit Charnkeitkong, Xian She Feng

Bibliographic record

VenueAdvanced materials research · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicAdsorption and biosorption for pollutant removal
Canadian institutionsUniversity of Waterloo
FundersRangsit University
KeywordsGibbs free energyZincEndothermic processEnthalpyAdsorptionAqueous solutionChemistryPulp (tooth)Arrhenius equationExothermic reactionNuclear chemistryWaste managementMetallurgyMaterials scienceThermodynamicsActivation energyPhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Dried pulp waste, a manufactured solid waste by product was used as a biosorbent for the removal zinc (II) from aqueous solution. A series of experiments were conducted in a batch system to evaluate the thermodynamic parameters of the pulp waste for zinc (II) removal at an initial pH value of 6.0, ZnCl2 concentration of 50-200 ppm and temperature 30-50 °C. Thermodynamic parameters, such as Gibbs free energy change (ΔG°), enthalpy (ΔH°) and entropy (ΔS°), evaluation of zinc (II) adsorption on pulp waste showed that the adsorption process under the selected conditions was spontaneous and endothermic nature for all concentration and temperature studied. The activation energy of zinc (II) adsorption (Ea) was determined using modified Arrhenius equation as 1.89, 3.76, 4.73 and 6.46 kJ/mol at different concentration 50, 100, 150 and 200 ppm, respectively. The sticking probability (SP*) was also evaluated.

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 score0.002
Threshold uncertainty score0.004

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 head0.026
GPT teacher head0.317
Teacher spread0.291 · 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".

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Citations0
Published2014
Admission routes1
Has abstractyes

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