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Record W1868458082 · doi:10.1063/1.4919803

Tailoring the electronic transitions of NdNiO<sub>3</sub> films through (111)<sub>pc</sub> oriented interfaces

2015· article· en· W1868458082 on OpenAlexafffund
Sara Catalano, Marta Gibert, Valentina Bisogni, Feizhou He, Ronny Sutarto, M. Viret, Pavlo Zubko, R. Scherwitzl, G. A. Sawatzky, Thorsten Schmitt, J.‐M. Triscone

Bibliographic record

VenueAPL Materials · 2015
Typearticle
Languageen
FieldMaterials Science
TopicMagnetic and transport properties of perovskites and related materials
Canadian institutionsUniversity of British ColumbiaCanadian Light Source (Canada)
FundersCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaEuropean CommissionSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungUniversity of SaskatchewanCanadian Light SourceNational Science Foundation
KeywordsMaterials scienceOrthorhombic crystal systemCondensed matter physicsEpitaxyMetal–insulator transitionThin filmLattice (music)CrystallographyTransition temperatureTransition metalCrystal structureMetalNanotechnologySuperconductivityLayer (electronics)CatalysisPhysicsMetallurgy

Abstract

fetched live from OpenAlex

Bulk NdNiO 3 and thin films grown along the pseudocubic (001) pc axis display a 1st order metal to insulator transition (MIT) together with a Nel transition at T = 200 K. Here, we show that for NdNiO 3 films deposited on (111) pc NdGaO 3 , the MIT occurs at T = 335 K and the Nel transition at T = 230 K. By comparing transport and magnetic properties of layers grown on substrates with different symmetries and lattice parameters, we demonstrate a particularly large tuning when the epitaxy is realized on (111) pc surfaces. We attribute this effect to the specific lattice matching conditions imposed along this direction when using orthorhombic substrates.

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 score0.002
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 head0.017
GPT teacher head0.218
Teacher spread0.202 · 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

Citations77
Published2015
Admission routes2
Has abstractyes

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