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Record W1579548304 · doi:10.5772/18255

Optoelectronic Properties of Amorphous Silicon the Role of Hydrogen: from Experiment to Modeling

2011· book-chapter· en· W1579548304 on OpenAlexafffund
F. Gaspari

Bibliographic record

VenueInTech eBooks · 2011
Typebook-chapter
Languageen
FieldEngineering
TopicThin-Film Transistor Technologies
Canadian institutionsUniversity of Ontario Institute of Technology
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAmorphous siliconMaterials scienceOptoelectronicsDangling bondPhotoconductivitySiliconAmorphous solidContext (archaeology)Solar cellCrystalline siliconEngineering physicsChemistryCrystallographyPhysics

Abstract

fetched live from OpenAlex

Amorphous silicon, and its more useful alloy form, hydrogenated amorphous silicon (a-Si:H), has been the subject of investigation for more than three decades. A-Si:H is a lowcost, efficient material which is used extensively for electronic devices. Indeed, most recent electronic device textbooks contain a comprehensive review of the physics of amorphous materials and amorphous silicon in particular (Baranovski, 2006; Kasap, 2005; Street, 2000). The advantages of a-Si:H are particularly evident when considering the photovoltaic application context for the preparation of solar cells: in fact, a-Si:H has a large optical absorption coefficient (about 0.5 micron of the material will absorb 90% of the incident sunlight); the energy gap can be modulated to allow for near optimum conversion efficiency for sunlight; it can be alloyed with other elements (carbon, germanium) to create multijunction structures with increased energy conversion efficiency for sunlight. Finally, it is plentiful and can be deposited on a variety of materials (at low temperature, over large areas, and on flexible substrates). However, the presence of metastable defects in a-Si:H adversely affects the performance of photovoltaic cells and thin film transistors. Electrical conductivity, photoconductivity and luminescence degradation have been linked to defect formation, such as dangling bonds (DBs) in the a-Si:H film (Akkaya & Aktas, 1995; Street, 1980). Staebler and Wronski (1977) found that defects can be created by illuminating a-Si:H. The creation of these light-induced defects (LID) is therefore referred to as the Staebler-Wronski (SW) effect. The presence of these defects, or dangling bonds, is the major factor responsible for the deterioration of the optical and electronic properties of a-Si:H. On the other hand, these defects are metastable and can be cured. Indeed, we could define a SW process that can be described as a two-step reversible process: i. Exposure to sunlight leads to an increase in the density of states (dangling bonds) in the energy gap of a-Si:H; this represents the SW effect proper; ii. Subsequent annealing at elevated temperatures (150-200 OC) reduces the density of states back to the original value, thus restoring the optoelectronic properties. It has been shown experimentally that both optical and electronic properties of amorphous silicon, such as refractive index, optical gap, absorption coefficient, electron and hole

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.188
Teacher spread0.167 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

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

Citations11
Published2011
Admission routes2
Has abstractyes

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