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Record W2273658547 · doi:10.1111/jace.14167

Etching Induced Stepped Nanostructure on Pb(Mg <sub> (1– <i>x</i> /2) </sub> Mn <sub> ( <i>x</i> /2) </sub> W <sub>1/2</sub> )O <sub>3</sub> Ceramics

2016· article· en· W2273658547 on OpenAlexafffund
Jing Liu, Zenan Jiang, Peyman Servati, Edouard Asselin

Bibliographic record

VenueJournal of the American Ceramic Society · 2016
Typearticle
Languageen
FieldMaterials Science
TopicFerroelectric and Piezoelectric Materials
Canadian institutionsUniversity of British Columbia
FundersShenyang National Laboratory for Materials ScienceNatural Sciences and Engineering Research Council of CanadaChinese Academy of Sciences
KeywordsNucleationOrthorhombic crystal systemMaterials scienceNanostructureCeramicMorphology (biology)Etching (microfabrication)Solid solutionPerovskite (structure)CrystallographyAtomic force microscopyMineralogyAnalytical Chemistry (journal)NanotechnologyCrystal structureChemistryMetallurgyLayer (electronics)Geology

Abstract

fetched live from OpenAlex

A new solid solution system, Pb(Mg (1– x /2) Mn ( x /2) W 1/2 )O 3 , is formed by replacing Mg 2+ with Mn 2+ in the Pb(Mg 1/2 W 1/2 )O 3 complex perovskite. The solid solution remains in the orthorhombic Pmcn symmetry up to x = 0.1. It is observed that for such a chemical modification, the surface of the grain changes significantly. A stepped surface nanostructure appears in the Mn‐substituted perovskite. Detailed surface morphology of the stepped patterns was revealed by atomic force microscopy ( AFM ), which determined that the interlayer step height varies from 2.3 to 8.3 nm. Analyse by XRD , SEM , EDX , and AFM suggest that the nature of the stepped surface structure may be the result of etching rather than spiral growth or two‐dimensional nucleation as it was previously believed.

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 score0.002

Distilled classifier scores by category (both heads)

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.224
Teacher spread0.214 · 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

Citations5
Published2016
Admission routes2
Has abstractyes

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Same venueJournal of the American Ceramic SocietySame topicFerroelectric and Piezoelectric MaterialsFrench-language works237,207