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Record W3035781666

X-ray Spectroscopy of Silver Nanostructures toward Antibacterial Applications

2019· article· en· W3035781666 on OpenAlexaff
Andrew G. Walsh, Ziyi Chen, Peng Zhang

Bibliographic record

VenueThe Journal of Physical Chemistry · 2019
Typearticle
Languageen
FieldMaterials Science
TopicNanocluster Synthesis and Applications
Canadian institutionsDalhousie University
Fundersnot available
KeywordsX-ray absorption spectroscopyNanoclustersExtended X-ray absorption fine structureXANESNanostructureChemistryAbsorption spectroscopyAbsorption (acoustics)NanotechnologyDensity functional theorySpectroscopyNanocrystalX-ray absorption fine structureComputational chemistryMaterials scienceOrganic chemistryPhysicsOptics
DOInot available

Abstract

fetched live from OpenAlex

Ag nanostructures have a wide variety of uses in areas such as biological science and catalysis. Determination of the structural properties of Ag nanostructures can assist in the understanding of the mechanisms involved in these processes. This review provides a summary of recently published work with Ag nanostructures including very small Ag nanoclusters, larger Ag nanocrystals, and Ag nanoalloys. X-ray absorption spectroscopy (XAS) is used to elucidate structural and electronic information about the Ag nanostructures, which is then used to provide insight as to the antibacterial activities of the Ag nanostructures. Some unique features of our XAS analysis on Ag nanostructures include multiedge and multielement measurements, multishell fitting and wavelet transformation (WT) of extended X-ray absorption fine structure (EXAFS), and the correlation between X-ray absorption near edge structure (XANES) and density functional theory (DFT) modeling.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.006
GPT teacher head0.240
Teacher spread0.234 · 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 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

Citations0
Published2019
Admission routes1
Has abstractyes

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