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Record W4396222634 · doi:10.18280/rcma.340204

Efficient Removal of Zinc and Copper from Wastewater Using Activated Carbon Derived from Date Pits in a Continuous Fixed-Bed Column

2024· article· en· W4396222634 on OpenAlexvenueno aff
Huda A. Mohsen, Alaa N. Ghanim

Bibliographic record

VenueRevue des composites et des matériaux avancés · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicAdsorption and biosorption for pollutant removal
Canadian institutionsnot available
Fundersnot available
KeywordsZincCopperWastewaterColumn (typography)Activated carbonEnvironmental sciencePulp and paper industryChemistryMaterials scienceMetallurgyEnvironmental engineeringEngineeringAdsorptionStructural engineeringOrganic chemistry

Abstract

fetched live from OpenAlex

Adsorbents based on agricultural biomass have been subjected to several investigations in recent years owing to their low cost and promising adsorption capabilities.This paper aimed to demonstrate the efficiency of date pits activated with phosphoric acid as common activating agent that increases the porosity and surface area of date pits.This results in a greater number of binding sites for the heavy metals to attach to improving the bio-adsorbent's effectiveness.To get rid of heavy metals such as zinc and copper ions from industrial wastewater using a fixed bed with a continuous flow configuration, the derived adsorbent was tested under a variety of operating conditions, including a flow rate of 4-12mL/min, an initial metal ion concentration of 30-60mg/L, and temperatures ranging from 20 to 50℃, which were chosen based on industrial conditions and available data.The results revealed that the removal efficiency of heavy metals increased with an increase in the initial metal ion concentration, but conversely, it decreased with an increase in flow rate and temperature.Also, the results indicated that with the optimum conditions of 15cm static bed height, 60mg/L initial metal concentration, 8mL/min flow rate, and 25℃ temperature, determining the ideal conditions results in the efficient removal of pollutants in less time and the treatment of larger quantities.Mathematical modeling of the fixed bed column was achieved using the kinetic models of Adams Thomas, Yoon-Nelson, Bohar, and Modified Dose-Response, in this regard, the Thomas model is the closest to the experimental values, it is supposed that the adsorption mechanism was a Langmuir type adsorption followed by a pseudo-second-order chemical sorption.The Yoon-Nelson approach was employed on experimental data to predict breakthrough curves through nonlinear regression.This made it easier to determine the crucial characteristic column parameters for process design.According to thermodynamic studies, heavy metals spontaneously and exothermally adsorb activated carbon in date pits.Firstly, spontaneous adsorption indicates efficient processes that occur favorably without external energy input, offering cost-effective solutions for various applications.Secondly, the exothermic nature of adsorption suggests that lower temperatures may be sufficient, reducing energy consumption and preserving the stability of sensitive materials.Additionally, the process's exothermicity facilitates desorption at higher temperatures, enhancing the efficiency of regeneration processes.This study has shown that BDP can successfully remove heavy metals from aqueous solutions.Understanding these characteristics is crucial for optimizing applications, reducing costs, and improving overall efficiency in industrial and environmental contexts.

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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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 head0.031
GPT teacher head0.255
Teacher spread0.224 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

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