MétaCan
Menu
Back to cohort
Record W1713446010 · doi:10.1139/cjp-2013-0618

Electronic properties of undoped microcrystalline silicon oxide films

2014· article· en· W1713446010 on OpenAlexvenueno aff
S. Michard, Shuo Wang, Vladimir Smirnov

Bibliographic record

VenueCanadian Journal of Physics · 2014
Typearticle
Languageen
FieldEngineering
TopicThin-Film Transistor Technologies
Canadian institutionsnot available
FundersChina Scholarship Council
KeywordsPhotoconductivityBand gapPhotocurrentMicrocrystallineAmorphous solidMaterials scienceAmorphous siliconOptoelectronicsPhoton energyAbsorption (acoustics)Analytical Chemistry (journal)SiliconOpticsPhysicsChemistryCrystalline siliconPhotonCrystallography

Abstract

fetched live from OpenAlex

The electronic properties of undoped microcrystalline silicon oxide films have been investigated by transient photocurrent (TPC) density of states (DOS) spectroscopy, supported by dark conductivity, steady-state photoconductivity, and constant-photocurrent measurements (CPM). Film compositions span the range from amorphous to microcrystalline and contain up to 10% oxygen content, yielding optical bandgap values E 04 (the photon energy at which the absorption depth equals one micrometre) between 1.85 and 2.11 eV. Carrier transport is consistent with multiple-trapping in a localised DOS, which depends upon film structure and oxygen content. TPC measurements indicate that both conduction band-tail energy and deep defect density increase with increasing oxygen content, accompanied by a reduction in majority carrier mobility-lifetime product. CPM measurements on amorphous films show a broadening of the Urbach tail with increasing oxygen content. Significantly higher oxygen incorporation without seriously compromising electronic quality appears possible in microcrystalline films. This suggests potential application as solar cell absorber layers offering increased optical bandgap and open-circuit voltage.

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 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 score0.029
Threshold uncertainty score0.449

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 head0.160
Teacher spread0.152 · 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 teacher head, 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

Citations1
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of PhysicsSame topicThin-Film Transistor TechnologiesFrench-language works237,207