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Record W2161388381 · doi:10.1039/c3ta13750c

High-efficiency, air stable graphene/Si micro-hole array Schottky junction solar cells

2013· article· en· W2161388381 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Materials Chemistry A · 2013
Typearticle
Languageen
FieldEngineering
TopicNanowire Synthesis and Applications
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsGrapheneMaterials scienceDopingOptoelectronicsEnergy conversion efficiencyPhotolithographySchottky barrierNanotechnologyDegradation (telecommunications)Etching (microfabrication)Electrical engineeringLayer (electronics)

Abstract

fetched live from OpenAlex

Graphene/Si hole array (SiHA) Schottky junctions show great promise as high-efficiency, cost-effective solar cells. However, their applications are still limited by the severe surface recombination of the nano-hole SiHA and inferior device stability arising from volatile oxidant doping. Here, we demonstrate the construction of high-efficiency graphene/SiHA devices with enhanced device performance and stability. The micro-hole SiHA fabricated by photolithography and reaction ion etching (RIE) possesses a smooth surface, thus ensuring a low surface recombination velocity. Also, the light harvesting of the micro-hole SiHA could be readily tuned by adjusting the hole depth. Introduction of the micro-hole SiHA, along with the use of AuCl3 for graphene doping, gives rise to a high power conversion efficiency (PCE) of 10.40% for the graphene/SiHA devices. Additionally, the device stability is substantially improved and shows a relatively low degradation ratio after storing in air for 3 months. It is expected that the graphene/SiHA devices will have important applications in new-generation Si solar cells.

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.

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 categoriesInsufficient payload (model declined to judge)
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 score0.005
Threshold uncertainty score0.999

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)0.0010.000

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 head0.005
GPT teacher head0.176
Teacher spread0.172 · 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