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Record W4231546550 · doi:10.18494/sam.2016.1206

Application of Single-Crystalline N-type and P-type ZnO Nanowires in Miniaturized Gas Ionization Sensor

2016· article· en· W4231546550 on OpenAlex
Svetlana Spitsina, Mojtaba Kahrizi

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

VenueSensors and Materials · 2016
Typearticle
Languageen
FieldEngineering
TopicGas Sensing Nanomaterials and Sensors
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of CanadaConcordia University
KeywordsNanowireType (biology)Materials scienceNanotechnologyIonizationOptoelectronicsChemistryIon

Abstract

fetched live from OpenAlex

Gas ionization sensors (GISs) based on n-type and p-type ZnO nanowires (NWs) have been fabricated and successfully tested in field ionization (FI) and field emission (FE) modes in sub-Torr atmospheres of various gases (Ar, He, N 2 , and O 2 ). Novel GISs demonstrated good stability and low breakdown voltages. Significantly decreased electrical breakdowns in gases were attained in the vicinity of positively charged p-type ZnO NWs' tips. The applied voltages were less than 40 V. These experimental outcomes can be ascribed to the fact that Ag-doped ZnO NWs have an increased number of empty states below the Fermi level and because of the observed high curvature on the NWs' apexes. The calculated enhancement factors were 45 and 1.49 10 4 in the GIS based on n-type ZnO NWs and in the GIS based on p-type ZnO NWs, respectively. The novel GIS based on p-type ZnO NWs described here is inexpensive, simple in operation, consumes little power, and can be used for environmental monitoring and gas detection in industrial and living environments or for space applications.

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 score0.005
Threshold uncertainty score0.498

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 head0.008
GPT teacher head0.194
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