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Record W2083969468 · doi:10.1063/1.2803890

Time evolution of charged defect states in tritiated amorphous silicon

2007· article· en· W2083969468 on OpenAlexaff
S. Costea, Nazir P. Kherani, S. Źükotyński

Bibliographic record

VenueJournal of Applied Physics · 2007
Typearticle
Languageen
FieldEngineering
TopicThin-Film Transistor Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDangling bondAmorphous siliconAnnealing (glass)Amorphous solidMaterials scienceAnalytical Chemistry (journal)SiliconActivation energyChemistryCrystallographyCrystalline siliconPhysical chemistryOptoelectronics

Abstract

fetched live from OpenAlex

Tritiated hydrogenated amorphous silicon (a-Si:H:T) thin films were deposited on crystalline silicon and high resistivity glass substrates. The time evolution of the density of defect states in these films was studied using the constant photocurrent method (CPM) and isothermal capacitance transient spectroscopy (ICTS). The density of defect states was found to change with time and to recover upon thermal annealing. The ICTS results revealed that, following thermal annealing, in a sample with approximately 1at.% tritium, the concentration of positively charged dangling bonds (D+) decreased by more than an order of magnitude over a period of 300h. The CPM results showed that, over the same period of time, the concentration of negatively charged dangling bonds (D−) increased by over two orders of magnitude. The D+ and D− concentrations followed exponential functions of time, but the rate was different than that of tritium decay. At the same time, the Urbach energy was found to decrease with time to about 1∕2 of its postanneal value. The change in the D+ and D− concentrations is primarily the result of capture of the beta particle generated electrons in dangling bonds and weak bonds, with steady state achieved through the development of a balance between carrier generation and carrier capture processes. The role of excess carriers was confirmed by CPM experiments under electrical bias.

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 score0.138
Threshold uncertainty score0.502

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 head0.006
GPT teacher head0.192
Teacher spread0.186 · 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
Published2007
Admission routes1
Has abstractyes

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