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Record W4323923774 · doi:10.17344/acsi.2022.7777

Comparison of Kinetics of Adsorption of Permanganate on Co-Al-Layered Double Hydroxide and MoS2 Nanocompounds

2023· article· en· W4323923774 on OpenAlexaff
Shahin Ghobadi, Babak Samiey, Enis Esmaili, Chil‐Hung Cheng

Bibliographic record

VenueActa chimica slovenica · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicAdsorption and biosorption for pollutant removal
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsAdsorptionHydroxideKineticsChemistryDiffusionIonic bondingInorganic chemistryIonic strengthIonPhysical chemistryThermodynamicsOrganic chemistryAqueous solution

Abstract

fetched live from OpenAlex

Permanganate ions were adsorbed on carbonate intercalated Co-Al-layered double hydroxide (Co-Al-LDH) and MoS2 and after a while the adsorbed ions were reduced to MnO2. Reduction of adsorbed ion was catalyzed on the surface of carbonate intercalated Co-Al-LDH but ions reacted with MoS2 surface. Adsorption kinetic tests were carried out at different temperatures, ionic strengths, pH, initial adsorbate concentrations and shaking rates. The adsorption kinetics was studied by the kinetics of adsorption study in the regions with constant adsorption acceleration (KASRA) model and KASRA, ideal-second-order (ISO), intraparticle diffusion, Elovich and (non-ideal process of adsorption kinetics (NIPPON) equations.In this work, a new equation called NIPPON equation was introduced. In this equation, it was assumed that during a non-ideal process, adsorbate species molecules were adsorbed simultaneously on the same type adsorption sites with different activities. Indeed, the average values of adsorption kinetic parameters were calculated by the NIPPON equation. Also, the character of boundaries of regions obtained from the KASRA model can be determined by this equation.

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 score0.089
Threshold uncertainty score0.564

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 head0.030
GPT teacher head0.310
Teacher spread0.280 · 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

Explore more

Same venueActa chimica slovenicaSame topicAdsorption and biosorption for pollutant removalFrench-language works237,207