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Record W4281863244 · doi:10.5539/jsd.v15n4p63

Lignocellulosic Biomass Waste Adsorbent for Removal of Dye from Aqueous Solution

2022· article· en· W4281863244 on OpenAlexvenueno aff
Basma G. Alhogbi

Bibliographic record

VenueJournal of Sustainable Development · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicDate Palm Research Studies
Canadian institutionsnot available
FundersKing Abdulaziz University
KeywordsAdsorptionSorbentLangmuirFreundlich equationBiomass (ecology)WastewaterLangmuir adsorption modelAqueous solutionChemistryExtraction (chemistry)Raw materialPulp and paper industryMethylene blueNuclear chemistryChromatographyChemical engineeringEnvironmental engineeringEnvironmental scienceOrganic chemistryPhotocatalysis

Abstract

fetched live from OpenAlex

Date Palm Tree Fiber (DPTF) is a renewable raw material which is considered a biomass waste excess of date farms and manufactures. This biomass was successfully utilized as solid phase extractor (SPE) for removal of methylene Blue dye (MB) from polluted water. The chemical composition and the surface morphology of the SPE was critically assigned based on FT-IR, and FE-SEM. In batch separation mode, the impact of several analytical parameters e.g. contact time, weight of biomass, solution pH and initial concentration on the MB dye uptake from aqueous media by DPTF solid adsorbent was critically studied. At the optimized parameters, good adsorption capacity (qe,exp =9.153 mg/g) at pH 6 was achieved. The data of MB uptake were subjected to Langmuir and Freundlich to assign the most probable retention mechanism. The adsorption fitted well with Langmuir isotherm models qm 648 mg/g. The data were fitted well with pseudo- second order model as supported from the qe,cal (9.225 mg/g) value. Excellent extraction (99%) of MB dye was achieved from the environmental water samples. The DPTF solid sorbent is a non-toxic and renewable raw material of lignocellulosic biomass has a potential to uptake MB dye from wastewater.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.700
Threshold uncertainty score0.365

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.023
GPT teacher head0.237
Teacher spread0.214 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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