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Record W2951550797 · doi:10.1021/nl302562f

Strain-Induced Spin States in Atomically Ordered Cobaltites

2012· article· en· W2951550797 on OpenAlexafffund

Bibliographic record

VenueNano Letters · 2012
Typearticle
Languageen
FieldMaterials Science
TopicMagnetic and transport properties of perovskites and related materials
Canadian institutionsUniversity of SaskatchewanMax Planck - University of Ottawa Centre for Extreme and Quantum PhotonicsCanadian Light Source (Canada)University of British Columbia
FundersCanadian Institutes of Health Research
KeywordsFerromagnetismEpitaxyMagnetismThin filmScanning transmission electron microscopyRelaxation (psychology)Transmission electron microscopyOxide

Abstract

fetched live from OpenAlex

Epitaxial strain imposed in complex oxide thin films by heteroepitaxy is recognized as a powerful tool for identifying new properties and exploring the vast potential of materials performance. A particular example is LaCoO(3), a zero spin, nonmagnetic material in the bulk, whose strong ferromagnetism in a thin film remains enigmatic despite a decade of intense research. Here, we use scanning transmission electron microscopy complemented by X-ray and optical spectroscopy to study LaCoO(3) epitaxial thin films under different strain states. We observed an unconventional strain relaxation behavior resulting in stripe-like, lattice modulated patterns, which did not involve uncontrolled misfit dislocations or other defects. The modulation entails the formation of ferromagnetically ordered sheets comprising intermediate or high spin Co(3+), thus offering an unambiguous description for the exotic magnetism found in epitaxially strained LaCoO(3) films. This observation provides a novel route to tailoring the electronic and magnetic properties of functional oxide heterostructures.

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 score0.003

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 head0.012
GPT teacher head0.227
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

Citations181
Published2012
Admission routes2
Has abstractyes

Explore more

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