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Record W2013997877 · doi:10.1063/1.3272684

Origin of inverse tunneling magnetoresistance in a symmetric junction revealed by delaminating the buried electronic interface

2009· article· en· W2013997877 on OpenAlexaff
J. Joshua Yang, Hua Xiang, Chengxiang Ji, William F. Stickle, Duncan R. Stewart, Douglas A. A. Ohlberg, R. Stanley Williams, Yufang Chang

Bibliographic record

VenueApplied Physics Letters · 2009
Typearticle
Languageen
FieldEngineering
TopicAdvanced Memory and Neural Computing
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsMagnetoresistanceQuantum tunnellingMaterials scienceOxideIon milling machineElectronic structurePhotoemission spectroscopyX-ray photoelectron spectroscopyCondensed matter physicsChemical physicsOptoelectronicsNanotechnologyChemical engineeringChemistryMagnetic fieldMetallurgyLayer (electronics)

Abstract

fetched live from OpenAlex

Electrical properties of modern electronic devices are usually controlled by the physical and chemical structure of one or more buried material interfaces. Accessing these buried interfaces by energetic ion milling can destroy this structural information. We report a delamination technique that exposes pristine buried interfaces for x-ray photoemission spectroscopy. We use this technique to show that unusual inverse tunneling magnetoresistance in a nominally symmetric (Co,Fe)/AlOx/(Co,Fe) magnetic tunnel junction devices is attributable to subtle over-oxidation of the lower AlOx/CoFe interface. Ion-milling investigation of the same samples misleads by chemically reducing the signature Fe oxide species during milling.

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 head0.007
GPT teacher head0.211
Teacher spread0.204 · 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

Citations6
Published2009
Admission routes1
Has abstractyes

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