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Record W2078095698 · doi:10.1021/la901387q

Monodisperse Samarium and Cerium Orthovanadate Nanocrystals and Metal Oxidation States on the Nanocrystal Surface

2009· article· en· W2078095698 on OpenAlexafffund
Thanh‐Dinh Nguyen, Cao‐Thang Dinh, Trong‐On Do

Bibliographic record

VenueLangmuir · 2009
Typearticle
Languageen
FieldMaterials Science
TopicCatalytic Processes in Materials Science
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsX-ray photoelectron spectroscopyNanocrystalSelected area diffractionCeriumMaterials scienceSamariumCalcinationOxidation stateCerium oxideTransmission electron microscopyMetalOxideVanadiumChemical engineeringInorganic chemistryNanotechnologyChemistryMetallurgyCatalysisOrganic chemistry

Abstract

fetched live from OpenAlex

A new solvothermal method has been developed for the synthesis of monodisperse SmVO4 and CeVO4 nanocrystals with controlled size and shape. The obtained materials were characterized by X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), transmission electron microscopy (TEM), and selected area electron diffraction (SAED) techniques. The results reveal that uniform nanocrystals and pure tetragonal phase of SmVO4 and CeVO4 can be achieved. To investigate the oxidation states of the metals on the mixed oxide nanocrystal surface, the XPS technique was employed. The results exhibit that only one oxidation state of samarium, cerium, and vanadium for each metal (e.g., Sm3+, Ce3+, V5+) was surprisingly well stable on the particle surface at the nanoscale, even after calcination, while the existence of two oxidation states of these metals is observed (e.g., Sm3+/Sm2+, Ce4+/Ce3+, V5+/V4+) in the corresponding single metal oxide nanocrystals.

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 score0.004

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 head0.010
GPT teacher head0.224
Teacher spread0.215 · 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

Citations88
Published2009
Admission routes2
Has abstractyes

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