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Record W2802269219 · doi:10.1021/acs.est.8b00487

Sorption of Perfluoroalkyl Acids to Fresh and Aged Nanoscale Zerovalent Iron Particles

2018· article· en· W2802269219 on OpenAlexafffund
Yanyan Zhang, Yue Zhi, Jinxia Liu, Subhasis Ghoshal

Bibliographic record

VenueEnvironmental Science & Technology · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicPer- and polyfluoroalkyl substances research
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSorptionZerovalent ironChemistrySulfidationEnvironmental chemistryInorganic chemistryCarboxylateAdsorptionNuclear chemistryOrganic chemistrySulfur

Abstract

fetched live from OpenAlex

The sorption of perfluoroalkyl acids (PFAAs), particularly perfluorooctanesulfonic acid (PFOS), to freshly synthesized nanoscale zerovalent iron (nZVI) and aged (oxidized) and sulfidated nZVI, was investigated under anaerobic conditions. The sorption of PFAAs to nZVI was 2–4 orders of magnitude higher than what has been reported for sediments, soils, and iron oxides. The hydrophobicity of the perfluorocarbon chain dominated the sorption, although FTIR spectra indicated specific interactions between sulfonate and carboxylate head groups and nZVI. The contributions from electrostatic interactions depended on the surface charge and pH. Humic acids influenced sorption only at concentrations above 50 mg/L. nZVI aged in deoxygenated water up to 95 days showed similar sorption isotherms for PFOS to fresh nZVI, because Fe(OH)2 was the predominant phase on the nZVI surface independent of aging time. Sulfidation of nZVI reduced sorption of PFOS by 1 log unit owing to the FeS deposited, but the sorption affinity was restored after aging because of formation of Fe(OH)2. Oxidation of nZVI by water and dissolved oxygen also resulted in similar sorption of PFOS as fresh nZVI at environmentally relevant concentrations. The results suggest that injection of nZVI could reduce PFAA concentrations in groundwater despite changes to its surface chemistry with aging.

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
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 score0.131
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.007
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.248
Teacher spread0.239 · 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.

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

Citations61
Published2018
Admission routes2
Has abstractyes

Explore more

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