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Record W2742179840 · doi:10.3390/app7080795

An Innovative Dual-Column System for Heavy Metallic Ion Sorption by Natural Zeolite

2017· article· en· W2742179840 on OpenAlexafffund
Amanda L. Ciosek, Grace K. Luk

Bibliographic record

VenueApplied Sciences · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicMine drainage and remediation techniques
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsZeoliteSorptionMetal ions in aqueous solutionChemistryCopperMetalHeavy metalsIndustrial wastewater treatmentAdsorptionEnvironmental engineeringWastewaterEnvironmental chemistryEnvironmental scienceOrganic chemistry

Abstract

fetched live from OpenAlex

This study investigates the design and performance of a novel sorption system containing natural zeolite. The apparatus consists of packed, fixed-bed, dual-columns with custom automated controls and sampling chambers, connected in series and stock fed by a metering pump at a controlled adjustable distribution. The purpose of the system is to remove heavy metallic ions predominately found in acid mine drainage, including lead (Pb2+), copper (Cu2+), iron (Fe3+), nickel (Ni2+) and zinc (Zn2+), combined in equal equivalence to form an acidified total 10 meq/L aqueous solution. Reported trends on the zeolite’s preference to these heavy metallic ions is established in the system breakthrough curve, as Pb2+ >> Fe3+ > Cu2+ > Zn2+ >> Ni2+. Within a 3-h contact period, Pb2+ is completely removed from both columns. Insufficient Ni2+ removal is achieved by either column with the promptest breakthrough attained, as zeolite demonstrates the least affinity towards it; however, a 48.97% removal is observed in the cumulative collection at the completion of the analysis period. The empty bed contact times for the first and second columns are 20 and 30 min, respectively; indicating a higher bed capacity at breakthrough and a lower usage rate of the zeolite mineral in the second column. This sorption system experimentally demonstrates the potential for industrial wastewater treatment technology development.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.880

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 studies0.0010.001
Scholarly communication0.0000.001
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 head0.015
GPT teacher head0.276
Teacher spread0.261 · 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

Citations13
Published2017
Admission routes2
Has abstractyes

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