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Record W2120206584 · doi:10.1002/cjce.20661

Utilisation of immobilised activated sludge for the biosorption of chromium (VI)

2011· article· en· W2120206584 on OpenAlexvenueaboutno aff
Ghodratallah Shams Khorramabadi, Reza Darvishi Cheshmeh Soltani, Abbas Rezaee, Alireza Khataee, Ahmad Jonidi Jafari

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicAdsorption and biosorption for pollutant removal
Canadian institutionsnot available
Fundersnot available
KeywordsBiosorptionNuclear chemistryChromiumChemistryLangmuirFreundlich equationCalcium alginateLangmuir adsorption modelActivated sludgeAdsorptionEnvironmental engineeringCalciumWastewaterSorption

Abstract

fetched live from OpenAlex

Abstract The objective of this investigation was to study the biosorption of Cr (VI) on immobilised activated sludge (IAS) and calcium alginate (CA) using batch system. The optimal pH for Cr (VI) biosorption by IAS and CA was 2.0 and 4.0, respectively. Equilibrium was attained at approximately 120 min for both biosorbents. For both biosorbents, the equilibrium biosorption capacity (mg/g) increased as the initial metal ion concentration increased and the concentration of biosorbent decreased. The rate of biosorption onto IAS and pure CA (as mg/g) increased from 5.02 to 87.66 and 4.97 to 79.09 as the concentration of Cr (VI) ions increased from 10 to 1000 mg/L, respectively. In the case of biosorbent concentration, as the concentration of IAS and pure CA increased from 1 to 20 g/L, the equilibrium uptake ( q e ) decreased from 21.33 to 1.57 and 19.41 to 1.38 mg/g, respectively. The biosorption data showed that the Langmuir model was more suitable than the Freundlich model. Also, the results indicated that the pseudo‐second order model was the most suitable for Cr (VI) biosorption onto IAS and CA. © 2011 Canadian Society for Chemical Engineering

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 score0.007
Threshold uncertainty score0.479

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 head0.020
GPT teacher head0.195
Teacher spread0.175 · 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

Citations50
Published2011
Admission routes2
Has abstractyes

Explore more

Same venueThe Canadian Journal of Chemical EngineeringSame topicAdsorption and biosorption for pollutant removalFrench-language works237,207