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Record W2093650333 · doi:10.1063/1.4792219

The influence of a Pb surfactant on the magnetism of dilute Si1–<i>x</i>Mn<i>x</i> films

2013· article· en· W2093650333 on OpenAlexafffund
Samer Kahwaji, William J. Bowman, M. Robertson, T. L. Monchesky

Bibliographic record

VenueJournal of Applied Physics · 2013
Typearticle
Languageen
FieldMaterials Science
TopicZnO doping and properties
Canadian institutionsAcadia UniversityDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCurie temperatureFerromagnetismMagnetismMagnetic momentSaturation (graph theory)Analytical Chemistry (journal)Molecular beam epitaxyMagnetic semiconductorParamagnetismMaterials scienceMonolayerPulmonary surfactantCondensed matter physicsThin filmEpitaxyChemistryNanotechnologyPhysics

Abstract

fetched live from OpenAlex

We investigated the effect of Pb surfactant on the growth mode and magnetism of dilute Si1−xMnx thin films grown by molecular beam epitaxy. We find that the nanocolumns that form in Pb-free samples are paramagnetic with a small saturation moment that drops with increasing Mn concentration. On the contrary, samples grown with 2 monolayers of Pb contain MnSi1.7 nanorods that lie in the plane of the films. Although the saturation moment of these samples also drops rapidly with increasing Mn concentration, it is as high as 0.65 μB/Mn. At the lowest Mn concentration (x = 0.5%), the samples grown with a Pb surfactant exhibit two ferromagnetic transitions at the Curie temperatures TC1≈40 K and TC2>400 K. While the transition at TC1 is consistent with the Curie temperature of bulk MnSi1.7 crystals, TC2 is possibly due to a second phase resulting from Mn in the Si matrix.

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)0.001
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.204
Teacher spread0.192 · 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

Citations4
Published2013
Admission routes2
Has abstractyes

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Same venueJournal of Applied PhysicsSame topicZnO doping and propertiesFrench-language works237,207