MétaCan
Menu
Back to cohort
Record W2092346907 · doi:10.1116/1.1771661

Process issues with Mo∕a-Si:H Schottky diode and thin film transistors integration for direct x-ray detection

2004· article· en· W2092346907 on OpenAlexaff
Czang-Ho Lee, Y. Vygranenko, Arokia Nathan

Bibliographic record

VenueJournal of Vacuum Science & Technology A Vacuum Surfaces and Films · 2004
Typearticle
Languageen
FieldEngineering
TopicThin-Film Transistor Technologies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMaterials scienceSchottky diodeOptoelectronicsThin-film transistorTransistorMasking (illustration)FabricationStress (linguistics)DiodeLayer (electronics)Sensitivity (control systems)Amorphous solidMolybdenumVoltageElectronic engineeringNanotechnologyElectrical engineeringMetallurgyCrystallography

Abstract

fetched live from OpenAlex

This article presents an alternate strategy to reduce mechanical stress issues pertinent to the process integration of molybdenum/hydrogenated amorphous silicon (Mo∕a-Si:H) Schottky diodes and thin film transistors (TFTs), used as x-ray sensor pixels for medical imaging. The previous approach was to minimize the intrinsic stress in the Mo layer through appropriate process conditions and film thickness. However, that approach resulted in narrow process latitude and compromised x-ray sensitivity. Alternatively, the mechanical stress in the Mo can be reduced by reducing and/or avoiding the extrinsic stress exerted on the Mo by the underlying films through a different masking sequence in the fabrication. This modified process allows for a more flexible design of the Mo layer for enhanced x-ray sensitivity, while maintaining the mechanical integrity of the various layers. Also, the performance of the Schottky diode is improved in terms of its forward current. The x-ray sensitivity has been measured at different x-ray spectra in the range of 40–100kVp. The pixel shows good linearity with x-ray dosage and high detection efficiency at low x-ray tube voltages.

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)0.001
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 score0.027
Threshold uncertainty score0.949

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.225
Teacher spread0.218 · 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

Citations0
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Vacuum Science & Technology A Vacuum Surfaces and FilmsSame topicThin-Film Transistor TechnologiesFrench-language works237,207