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Record W4392977325 · doi:10.1016/j.jhazmat.2024.134101

Urchin-like CO2-responsive magnetic microspheres for highly efficient organic dye removal

2024· article· en· W4392977325 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Hazardous Materials · 2024
Typearticle
Languageen
FieldMaterials Science
TopicCovalent Organic Framework Applications
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsChina Scholarship CouncilCanada Foundation for Innovation
KeywordsAdsorptionCationic polymerizationMethyl orangeChemistryWastewaterHazardous wasteChemical engineeringMethylene bluePhotocatalysisWaste managementOrganic chemistryEnvironmental engineeringCatalysisEnvironmental science

Abstract

fetched live from OpenAlex

CO2-responsive materials have emerged as promising adsorbents for the remediation of refractory organic dyes-contaminated wastewater without the formation of byproducts or causing secondary pollution. However, realizing the simultaneous adsorption−separation or complete removal of both anionic and cationic dyes, as well as achieving deeper insights into their adsorption mechanism, still remains a challenge for most reported CO2-responsive materials. Herein, a novel type of urchin-like CO2-responsive Fe3O4 microspheres (U-Fe3O4@P) has been successfully fabricated to enable ultrafast, selective, and reversible adsorption of anionic dyes by utilizing CO2 as a triggering gas. Meanwhile, the CO2-responsive U-Fe3O4@P microspheres exhibit the capability to initiate Fenton degradation of non-adsorbable cationic dyes. Our findings reveal exceptionally rapid adsorption equilibrium, achieved within a mere 5 minutes, and an outstanding maximum adsorption capacity of 561.2 mg g−1 for anionic dye methyl orange upon CO2 stimulation. Moreover, 99.8% of cationic dye methylene blue can be effectively degraded through the Fenton reaction. Furthermore, the long-term unresolved interaction mechanism of organic dyes with CO2-responsive materials is deciphered through a comprehensive experimental and theoretical study by density functional theory. This work provides a novel paradigm and guidance for designing next-generation eco-friendly CO2-responsive materials for highly efficient purification of complex dye-contaminated wastewater in environmental engineering. Massive discharge of organic dyes contaminated wastewater into the ecosystem threatens human health and the aquatic environment, ascribed to the hazardous and toxic natures of dyes. Thus, designing advanced materials for the highly efficient removal of organic dyes from wastewater is extremely promising. Herein, novel urchin-like CO2-responsive magnetic microspheres were devised to enable highly efficient selective adsorption−separation of anionic dyes and simultaneous removal of anionic/cationic dyes, even in the complex synthetic dye effluent by combining CO2-triggered adsorption and Fenton degradation. This work provides insights for developing 'smart' materials for the purification of complex dye-contaminated wastewater in environmental engineering.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.065
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.009
GPT teacher head0.257
Teacher spread0.248 · 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