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Record W2769678064 · doi:10.5539/enrr.v7n4p44

Powerful Concentration of Rhodium in Plating Wastewater Using Homogeneous Liquid–Liquid Extraction (HoLLE) and Study for Scale-up

2017· article· en· W2769678064 on OpenAlexvenueno aff
Takeshi Kato, Shotaro Saito, Shigekatsu Oshite, Shukuro Igarashi

Bibliographic record

VenueEnvironment and Natural Resources Research · 2017
Typearticle
Languageen
FieldEngineering
TopicExtraction and Separation Processes
Canadian institutionsnot available
FundersMinistry of Education, Culture, Sports, Science and Technology
KeywordsRhodiumWastewaterHomogeneousExtraction (chemistry)ChromatographyChemistryPlating (geology)Phase (matter)Liquid phaseLiquid liquidLiquid–liquid extractionVolume (thermodynamics)Aqueous solutionEnvironmental engineeringCatalysisEnvironmental scienceOrganic chemistryMathematics

Abstract

fetched live from OpenAlex

A powerful technique for the concentration of rhodium (Rh) in plating wastewater was developed. The technique entails complexing Rh with 1-(2-pyridylazo)-2-naphthol (PAN) followed by homogeneous liquid–liquid extraction (HoLLE) with Zonyl FSA. The optimum HoLLE conditions were determined as follows: [ethanol]T = 30.0 vol.%, pH = 4.00, and Rh:PAN = 1:5. Under these optimum conditions, 88.1% of Rh was extracted into the sedimented liquid phase. After phase separation, the volume ratio [aqueous phase (Va) /sedimented liquid phase (Vs)] of Va and Vs was 1000 (50 mL → 0.050 mL). We then applied the new method to wastewater generated by the plating industry. The phase separation was satisfactorily achieved when the volume was scaled up to 1000 mL of the actual wastewater; 84.7% of Rh was extracted into the sedimented liquid phase. After phase separation, Va/Vs was 588 (1000 mL - 1.70 mL).

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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.044
GPT teacher head0.348
Teacher spread0.304 · 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

Citations2
Published2017
Admission routes1
Has abstractyes

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