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Record W2766458979 · doi:10.1021/acs.jpcc.7b06311

Probing Surface Functionality on Amorphous Carbons Using X-ray Photoelectron Spectroscopy of Bound Metal Ions

2017· article· en· W2766458979 on OpenAlexafffund
Andrew Carrier, Inusa Abdullahi, Kelly Hawboldt, Barrie Fiolek, Stephanie MacQuarrie

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2017
Typearticle
Languageen
FieldEnergy
TopicIron oxide chemistry and applications
Canadian institutionsMemorial University of NewfoundlandCape Breton University
FundersMitacsCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada
KeywordsX-ray photoelectron spectroscopyPhysisorptionAdsorptionMetal ions in aqueous solutionMetalCrystallinityAmorphous solidAmorphous carbonInorganic chemistryBinding energyMaterials scienceChemistryPhysical chemistryCrystallographyChemical engineeringOrganic chemistry

Abstract

fetched live from OpenAlex

The surface functionality of amorphous carbons is difficult to directly measure because of a lack of crystallinity and overwhelming signals derived from the bulk material. Biochar, a form of amorphous carbon containing considerable oxygen surface functionality, was probed using metal ions and X-ray photoelectron spectroscopy to simultaneously measure the presence and proximity of functional groups and determine the preferred binding modes of a variety of metal ions. These binding motifs were correlated to the efficiency of metal adsorption as determined using the Langmuir isotherm and stability with respect to leaching. Three binding motifs were apparent: physisorption (Cd 2+, Mn 2+, and Zn 2+ ), chelation (Cu 2+, Ni 2+, and Zn 2+ ), and hydrolysis/precipitation (Cu 2+, Ni 2+, and Pb 2+ ).

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 score0.013
Threshold uncertainty score0.495

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 science0.0010.000
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 head0.024
GPT teacher head0.284
Teacher spread0.260 · 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

Citations12
Published2017
Admission routes2
Has abstractyes

Explore more

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