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Record W2061958168 · doi:10.1063/1.1852733

Concentration and ion-energy-independent annealing kinetics during ion-implanted-defect annealing

2005· article· en· W2061958168 on OpenAlexaff
Rachid Karmouch, Jean-François Mercure, Yonathan Anahory, F. Schiettekatte

Bibliographic record

VenueApplied Physics Letters · 2005
Typearticle
Languageen
FieldEngineering
TopicIon-surface interactions and analysis
Canadian institutionsUniversité de MontréalRegroupement Québécois sur les Matériaux de Pointe
Fundersnot available
KeywordsAnnealing (glass)Ion implantationKineticsIonMaterials scienceFluenceCrystallographic defectActivation energyCrystalliteAnalytical Chemistry (journal)CrystallographyMolecular physicsChemistryMetallurgyPhysical chemistry

Abstract

fetched live from OpenAlex

Nanocalorimetry revealed that the annealing kinetics of ion-implanted defects in polycrystalline Si is independent of ion fluence and implantation energy. Ion implantation of 30 keV Si−, 15 keV Si−, and 15 keV C− was performed at fluences ranging from 6×1011 to 1×1015atoms∕cm2, followed by temperature scans between 30 and 450 °C. The rate of heat release has the same shape for all fluences, featuring no peaks but rather a smooth, continuously increasing signal. This suggests that the heat release is dominated by the annealing of highly disordered zones generated by each implantation cascade. Such annealing depends primarily on the details of the damage zone–crystal interface kinetics, and not on the point defect concentration.

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 score0.002
Threshold uncertainty score0.004

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 head0.005
GPT teacher head0.190
Teacher spread0.185 · 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

Citations12
Published2005
Admission routes1
Has abstractyes

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