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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 OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

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.

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 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 score0.257
Threshold uncertainty score0.967

Codex and Gemma teacher scores by category

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)0.0000.000

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