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Record W2077323214 · doi:10.1088/0957-4484/24/4/045701

Unlocking doping and compositional profiles of nanowire ensembles using SIMS

2013· article· en· W2077323214 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueNanotechnology · 2013
Typearticle
Languageen
FieldEngineering
TopicIon-surface interactions and analysis
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceSecondary ion mass spectrometryDopingDopantNanowirePlanarSubstrate (aquarium)HeterojunctionIonImpurityOptoelectronicsAnalytical Chemistry (journal)NanotechnologyPhysics

Abstract

fetched live from OpenAlex

Dynamic and time-of-flight (TOF) secondary ion mass spectrometry (SIMS) was performed on vertically standing III-V nanowire ensembles embedded in Cyclotene polymer. By embedding the NWs in Cyclotene, the top surface of the sample was made planar, while the space between the NWs was filled to protect the background substrate from the ion beam, thus allowing for the NWs to be sputtered and analyzed evenly as a function of depth. Using thin film standards, SIMS analysis was used to calculate the impurity dopant concentration as a function of height in the NW ensemble. This marked the first use of conventional SIMS to accurately determine the doping density with excellent depth resolution. Additionally, this is the first presentation of SIMS as the only reported tool for characterizing the segment height uniformity of any arbitrary axial heterostructure NW ensemble.

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 score0.296
Threshold uncertainty score0.338

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 head0.007
GPT teacher head0.210
Teacher spread0.202 · 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