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Record W4407375361 · doi:10.1002/aic.18772

Thioether‐bridged surfactants for interfacial hydrophobic regulation and enhanced mineral flotation recovery

2025· article· en· W4407375361 on OpenAlexafffund
Qing Sun, Diling Yang, Jingsi Chen, Ziqian Zhao, Hao Zhang, Hong Zhong, Hongbo Zeng

Bibliographic record

VenueAIChE Journal · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicMinerals Flotation and Separation Techniques
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaCentral South UniversityCanada Foundation for InnovationNational Natural Science Foundation of ChinaCanada Research ChairsChina Scholarship Council
KeywordsThioetherMineralChemical engineeringPulmonary surfactantChemistryFroth flotationOrganic chemistryBiochemistry

Abstract

fetched live from OpenAlex

Abstract Surfactant modification to improve interfacial hydrophobicity is widely employed in separation applications such as mineral recovery. However, few modifications effectively enhance both the inherent hydrophobicity of the surfactant and its surface‐anchoring capacity. In this study, we propose a strategy to incorporate a thioether group into a hydroxamate surfactant, resulting in the synthesis of N‐hydroxy‐2‐(octylthio)acetamide (OTHA). Compared to the thioether‐free surfactant (OHA), the thioether group significantly improves the metal‐anchoring capability of the surfactant, demonstrating a twofold increase in adsorption on hydrophilic cassiterite surfaces. Meanwhile, the inherent hydrophobicity of the thioether group enhances the hydrophobization of the target mineral surface and improves bubble‐surface interactions. The robust hydrophobicity‐inducing ability of OTHA successfully increases the flotation recovery of hydrophilic cassiterite particles, with a marked improvement from 72.5% to 95.0%. This work presents a paradigm for surfactant modification, enabling tailored hydrophobic interfaces for practical applications such as mineral separation, oil‐gas extraction, waterproof materials, and functional coatings.

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 score0.120
Threshold uncertainty score0.518

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 head0.010
GPT teacher head0.276
Teacher spread0.266 · 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

Citations5
Published2025
Admission routes2
Has abstractyes

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