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Record W7071955756

Threshold Voltage Instability and Relaxation in Hydrogenated Amorphous Silicon Thin Film Transistors

2006· dissertation· en· W7071955756 on OpenAlexfundno aff

Bibliographic record

VenueUWSpace (University of Waterloo) · 2006
Typedissertation
Languageen
FieldEngineering
TopicThin-Film Transistor Technologies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Waterloo
KeywordsThreshold voltageVoltageStress (linguistics)High voltageNoise (video)
DOInot available

Abstract

fetched live from OpenAlex

This thesis presents a study of the bias-induced threshold voltage metastability phenomenon of the hydrogenated amorphous silicon (a-Si:H) thin film transistors (TFTs). An application of gate bias stress shifts the threshold voltage of a TFT. After the bias stress is removed, the threshold voltage eventually returns to its original value. The underlying physical mechanisms for the shift in threshold voltage during the application of the bias and after the removal of the bias stress are investigated. <br /><br /> The creation of extra defect states in the band gap of a-Si:H close to the gate dielectric interface, and the charge trapping in the silicon nitride (SiN) gate dielectric are the most commonly considered instability mechanisms of threshold voltage. In the first part of this work, the defect state creation mechanism is reviewed and the kinetics of the charge trapping in the SiN is modelled assuming a simplified mono-energetic and a more realistic Gaussian distribution of the SiN traps. The charge trapping in the mono-energetic SiN traps was approximated by a logarithmic function of time. However, the charge trapping with a Gaussian distribution of SiN traps results in a more complex behavior. <br /><br /> The change in the threshold voltage of a TFT after the gate bias has been removed is referred to threshold voltage relaxation, and it is investigated in the second part of this work. A study of the threshold voltage relaxation sheds more light on the metastability mechanisms of a-Si:H TFTs. Possible mechanisms considered for the relaxation of threshold voltage are the annealing of the extra defect states and the charge de-trapping from the SiN gate dielectric. The kinetics of the charge de-trapping from a mono-energetic and a Gaussian distribution of the SiN traps are analytically modelled. It is shown that the defect state annealing mechanisms cannot explain the observed threshold voltage relaxation, but a study of the kinetics of charge de-trapping helps to bring about a very good agreement with the experimentally obtained results. Using the experimentally measured threshold voltage relaxation results, a Gaussian distribution of gap states is extracted for the SiN. This explains the threshold voltage relaxation of TFT after the bias stress with voltages as high as 50V is removed. <br /><br /> Finally, the results obtained from the threshold voltage relaxation make it possible to calculate the total charge trapped in the SiN and to quantitatively distinguish between the charge trapping mechanism and the defect state creation mechanisms. In conclusion, for the TFTs used in this thesis, the charge trapping in the SiN gate dielectric is shown to be the dominant threshold voltage metastability mechanism caused in short bias stress times.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.436
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.006
GPT teacher head0.166
Teacher spread0.160 · 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.

Study designQualitative
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
Published2006
Admission routes1
Has abstractyes

Explore more

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