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Reduced material quality requirements for electronically coupled upconverters compared to intermediate band solar cells

2021· article· en· W3198912039 on OpenAlexaff
Zhaoxin Zhang, Jacob J. Krich

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSemiconductor Quantum Structures and Devices
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsOptoelectronicsSemiconductorSolar cellTraverseMaterials scienceTheory of solar cellsAbsorption (acoustics)Quality (philosophy)Engineering physicsOpticsSolar cell efficiencyPhysics

Abstract

fetched live from OpenAlex

Intermediate band (IB) materials allow the development of high efficiency solar cells by absorption of subgap photons. Standard IB devices have n-IB-p structures, which ensure that carriers are not directly extracted from the IB itself, but this geometry requires that holes from the front of the device must transit the IB region before being collected. This requirement forces IB materials to have relatively long carrier lifetimes before they can improve the efficiency of solar cells. The electronically coupled upconverter (ECUC) geometry puts the IB material at the back of the device. While more complicated 2D contact patterns are required to extract current directly from the standard semiconductor, carriers produced in the standard semiconductor do not need to traverse the IB region, allowing the ECUC to produce high efficiency with lower quality IB materials, as exist today. We study the potential efficiency of ECUC devices using the semianalytical modified Strandberg model, which describes the current-voltage performance of IB devices, including nonradiative recombination and the associated finite carrier collection. We find that even with moderate-to-low IB material quality, the ECUC geometry allows higher efficiency than the standard IB solar cell geometry. The ECUC is a promising architecture for near-term progress in IB 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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.031
GPT teacher head0.319
Teacher spread0.289 · 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
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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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