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Record W4388720548 · doi:10.1021/acsomega.3c07539

Selective Separation of Chalcopyrite from Pyrite Using Sodium Humate: Flotation Behavior and Adsorption Mechanism

2023· article· en· W4388720548 on OpenAlexaff
Da Sun, Maolin Li, Yingying Fu, Zhiqin Pan, Rui Cui, Daowei Wang, Ming Zhang, Wei Yao

Bibliographic record

VenueACS Omega · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMinerals Flotation and Separation Techniques
Canadian institutionsUniversity of Alberta
FundersWuhan University of Science and TechnologyNational Natural Science Foundation of China
KeywordsPyriteChalcopyriteDepressantAdsorptionXanthateChemistryBeneficiationInorganic chemistryEnvironmental pollutionEnvironmental chemistryOrganic chemistryMineralogyCopperEnvironmental science

Abstract

fetched live from OpenAlex

High Resolution Image Download MS PowerPoint Slide Flotation separation of chalcopyrite from pyrite using lime or cyanides as depressants results in serious problems, such as the blockage of pipelines and environmental pollution. Eco-friendly organics are a future trend for beneficiation plants. In this research, the eco-friendly organic depressant sodium humate (SH) was chosen as a depressant to separate chalcopyrite from pyrite by flotation. The results indicated that SH could selectively depress pyrite owing to the oxidation species (FeOOH, Fe 2 (SO 4 ) 3 ) on its surface. The oxidation species were the adsorption sites for the COO – in the SH structure and impeded the subsequent collector potassium ethyl xanthate (KEX) adsorption. However, chalcopyrite was slightly oxidized with fewer oxidation species for SH adsorption, and KEX could be adsorbed and functioned effectively. This research suggested that SH could be an effective and eco-friendly depressant in chalcopyrite–pyrite flotation separation, which had potential use in the industry.

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 score0.176
Threshold uncertainty score0.429

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 head0.029
GPT teacher head0.310
Teacher spread0.281 · 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

Citations17
Published2023
Admission routes1
Has abstractyes

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