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Record W2019173492 · doi:10.1038/srep02928

Broadband solar absorption enhancement via periodic nanostructuring of electrodes

2013· article· en· W2019173492 on OpenAlexafffund
Michael M. Adachi, André J. Labelle, Susanna M. Thon, Xinzheng Lan, Sjoerd Hoogland, Edward H. Sargent

Bibliographic record

VenueScientific Reports · 2013
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsUniversity of Toronto
FundersChina Scholarship CouncilNatural Sciences and Engineering Research Council of CanadaMitacsKing Abdullah University of Science and Technology
KeywordsMaterials scienceAbsorption (acoustics)OptoelectronicsPhotovoltaicsFinite-difference time-domain methodSolar cellPlanarQuantum dotNanostructureBroadbandMultiple exciton generationPlasmonic solar cellCurrent densityOpticsPhotovoltaic systemNanotechnologyPolymer solar cellPhysicsComputer science

Abstract

fetched live from OpenAlex

Solution processed colloidal quantum dot (CQD) solar cells have great potential for large area low-cost photovoltaics. However, light utilization remains low mainly due to the tradeoff between small carrier transport lengths and longer infrared photon absorption lengths. Here, we demonstrate a bottom-illuminated periodic nanostructured CQD solar cell that enhances broadband absorption without compromising charge extraction efficiency of the device. We use finite difference time domain (FDTD) simulations to study the nanostructure for implementation in a realistic device and then build proof-of-concept nanostructured solar cells, which exhibit a broadband absorption enhancement over the wavelength range of λ = 600 to 1,100 nm, leading to a 31% improvement in overall short-circuit current density compared to a planar device containing an approximately equal volume of active material. Remarkably, the improved current density is achieved using a light-absorber volume less than half that typically used in the best planar devices.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 head0.010
GPT teacher head0.210
Teacher spread0.200 · 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 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

Citations84
Published2013
Admission routes2
Has abstractyes

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