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Record W2088975050 · doi:10.1002/pssa.200673003

Magneto‐transport properties of NiMnSb thin films on InSb single crystals: Negative giant magnetoresistance

2006· article· en· W2088975050 on OpenAlexaff
S. Gardelis, John Androulakis, Z. Viskadourakis, Evie L. Papadopoulou, J. Giapintzakis, Sanjay Rai, G. S. Lodha, Sthitadhi Roy

Bibliographic record

Venuephysica status solidi (a) · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic properties of thin films
Canadian institutionsNovelis (Canada)
Fundersnot available
KeywordsMagnetoresistanceCondensed matter physicsMaterials scienceGiant magnetoresistancePulsed laser depositionThin filmMagnetic fieldOhmic contactScatteringCrystalliteFilm planeLayer (electronics)MagnetizationMagnetic anisotropyOpticsNanotechnologyPhysicsMetallurgy

Abstract

fetched live from OpenAlex

Abstract In this study we investigated the magneto‐transport properties of the ohmic contact between polycrystalline NiMnSb thin films grown by pulsed laser deposition and n‐type degenerate InSb (100) substrates. An unusual negative giant magnetoresistance (n‐GMR) effect is found when the external magnetic field is parallel to the in‐plane current direction. A similar effect is also observed when Ni films are deposited on InSb substrates. On the other hand, no n‐GMR effect is displayed when the deposited film is nonmagnetic. Grazing‐incidence X‐ray reflectometry shows the formation of a low‐density NiMnSb layer at the interface. The presence of such a layer coincides with the appearance of the n‐GMR.We argue that the n‐GMR effect is due to magnetic precipitates formed at the interface during the growth of the magnetic films. We propose that these precipitates align their magnetic moments in the direction of the external magnetic field and thus, the spin dependent scattering of the electrons is reduced. The effect of these precipitates on the magnetoresistance depends on the thermal processing of the system. (© 2007 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)

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 score0.160
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.015
GPT teacher head0.210
Teacher spread0.195 · 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

Citations1
Published2006
Admission routes1
Has abstractyes

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