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Record W4303575287 · doi:10.1002/smtd.202201078

Emerging Applications of Synchrotron Radiation X‐Ray Techniques in Single Atomic Catalysts

2022· review· en· W4303575287 on OpenAlexafffund
Zhongxin Song, Junjie Li, Kieran Doyle Davis, Xifei Li, Jiujun Zhang, Lei Zhang, Xueliang Sun

Bibliographic record

VenueSmall Methods · 2022
Typereview
Languageen
FieldMaterials Science
TopicCatalytic Processes in Materials Science
Canadian institutionsWestern University
FundersWestern UniversityNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of ChinaCanada Foundation for Innovation
KeywordsSynchrotron radiationCharacterization (materials science)SynchrotronX-ray absorption spectroscopyAtom (system on chip)Materials scienceCatalysisX-rayAbsorption (acoustics)Absorption spectroscopyChemistryNanotechnologyPhysicsOpticsComputer science

Abstract

fetched live from OpenAlex

Single atom catalysts (SACs) can achieve a maximum atom utilization efficiency of 100%, which provides significantly increased active sites compared with traditional catalysts during catalytic reactions. Synchrotron radiation technology is an important characterization method for identifying single-atom catalysts. Several types of internal information, such as the coordination number, bond length and electronic structure of metals, can all be analyzed. This review will focus on the introduction of synchrotron radiation techniques and their applications in SACs. First, the fundamentals of synchrotron radiation and the corresponding techniques applied in characterization of SACs will be briefly introduced, such as X-ray absorption near edge spectroscopy and extended X-ray absorption fine structure spectroscopy and in situ techniques. The detailed information obtained from synchrotron radiation X-ray characterization is described through four routes: 1) the local environment of a specific atom; 2) the oxidation state of SACs; 3) electronic structures at different orbitals; and 4) the in situ structure modification during catalytic reaction. In addition, a systematic summary of synchrotron radiation X-ray characterization on different types of SACs (noble metals and transition metals) will be discussed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.068
GPT teacher head0.416
Teacher spread0.349 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations26
Published2022
Admission routes2
Has abstractyes

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