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Record W2256059315 · doi:10.1088/0957-4484/27/3/035702

Structure versus properties in<i>α</i>-Fe<sub>2</sub>O<sub>3</sub>nanowires and nanoblades

2015· article· en· W2256059315 on OpenAlexafffund
Chao Wang, Yiqian Wang, Xuehua Liu, Huaiwen Yang, Jirong Sun, Yuan Lü, Guangwen Zhou, Federico Rosei

Bibliographic record

VenueNanotechnology · 2015
Typearticle
Languageen
FieldEnergy
TopicIron oxide chemistry and applications
Canadian institutionsInstitut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceNanowireOhmic contactMagnetizationCondensed matter physicsSchottky diodeNanomaterialsSchottky barrierNanotechnologyNanostructureFerrimagnetismMagnetic fieldOptoelectronicsLayer (electronics)

Abstract

fetched live from OpenAlex

We report structure/property relationships in bicrystalline α-Fe2O3 nanowires (NWs) and nanoblades (NBs), synthesized by thermal oxidation of iron foils with different surface roughness. The electrical properties of individual nanostructures were studied by in situ transmission electron microscopy. Current-voltage (I-V) measurements using gold electrodes showed that a Schottky contact forms between α-Fe2O3 NWs whereas an ohmic contact forms between α-Fe2O3 NBs. The difference in transport properties is attributed to the existence of oxygen vacancies in the coincidence-site-lattice boundary region of α-Fe2O3 NBs. Magnetic measurements indicate that the temperature-dependent zero-field-cooled magnetization rises more rapidly near the Morin transition temperature for α-Fe2O3 NBs than that for NWs. The distinct magnetic properties of the NBs are ascribed to the enhanced magnetic order induced by the structural order in the two-dimensional NBs. These α-Fe2O3 NBs are promising building blocks for electronic and magnetic devices since their 2D geometries facilitate integration into devices with realistic pathways to manufacturing. In addition, our study shows that boundary engineering is an effective approach for tailoring the physical properties of nanomaterials.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.031
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0010.001
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 head0.020
GPT teacher head0.221
Teacher spread0.201 · 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.

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

Citations21
Published2015
Admission routes2
Has abstractyes

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