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Record W2072231339 · doi:10.1039/c5sc00353a

Visualizing electronic interactions between iron and carbon by X-ray chemical imaging and spectroscopy

2015· article· en· W2072231339 on OpenAlexafffund
Xiaoqi Chen, Jianping Xiao, Jian Wang, Dehui Deng, Yongfeng Hu, Jigang Zhou, Liang Yu, Thomas Heine, Xiulian Pan, Xinhe Bao

Bibliographic record

VenueChemical Science · 2015
Typearticle
Languageen
FieldMaterials Science
TopicCarbon Nanotubes in Composites
Canadian institutionsCanadian Light Source (Canada)Saskatoon Medical ImagingUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchChinese Academy of SciencesChina Postdoctoral Science FoundationNational Research Council CanadaNational Natural Science Foundation of ChinaUniversity of SaskatchewanCanadian Light Source
KeywordsCarbon nanotubeCarbon fibersSpectroscopyMaterials scienceNanotechnologyTransmission electron microscopyChemical imagingMicroscopyChemical engineeringChemical physicsChemistryOpticsPhysicsComposite numberComputer scienceComposite materialHyperspectral imaging

Abstract

fetched live from OpenAlex

The electronic interaction of a catalyst and its support is of vital importance to its catalytic performance. However, it is still a great challenge to directly probe the interaction due to the lack of well-defined models and efficient technical means. In this study, we report that pod-like carbon nanotubes with encapsulated iron particles (Pod-Fe) and scanning transmission X-ray microscopy (STXM) can be used as an ideal model and technique to study the electronic interaction between carbon shells and iron particles. The chemical imaging and spectroscopy of Pod-Fe by STXM show that the local electronic structures at C K-edge near edge (π*) of carbon shells can be significantly modified by the encapsulated iron particles, which promotes the adsorption of oxygen-containing species, and thereby further modifies the electronic structure (π* and σ*) of the carbon shells. Moreover, computed X-ray absorption near edge structure spectra (XANES) confirmed the electronic modifications of carbon shells by the encapsulated iron particles. The present study provides a direct evidence of electronic interactions with simultaneously collected images and spectra, which can promote the understanding towards the nature of active sites and supports.

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)0.001
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 score0.004
Threshold uncertainty score0.611

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.011
GPT teacher head0.293
Teacher spread0.282 · 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

Citations94
Published2015
Admission routes2
Has abstractyes

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