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Record W4321645944 · doi:10.48550/arxiv.2302.10742

Group IV Mid-Infrared Thermophotovoltaic Cells on Silicon

2023· preprint· en· W4321645944 on OpenAlexfundno aff
Gérard Daligou, Richard Soref, Anis Attiaoui, Jaker Hossain, Mahmoud R. M. Atalla, Patrick Del Vecchio, Oussama Moutanabbir

Bibliographic record

VenuearXiv (Cornell University) · 2023
Typepreprint
Languageen
FieldEngineering
TopicThermal Radiation and Cooling Technologies
Canadian institutionsnot available
FundersArmy Research OfficeHORIZON EUROPE Framework ProgrammeEuropean CommissionNatural Sciences and Engineering Research Council of CanadaAir Force Office of Scientific ResearchMitacsCanada Research Chairs
KeywordsThermophotovoltaicOptoelectronicsMaterials scienceSemiconductorWaferInfraredBand gapEnergy conversion efficiencySiliconOpticsPhysicsCommon emitter

Abstract

fetched live from OpenAlex

Compound semiconductors have been the predominant building blocks for the current mid-infrared thermophotovoltaic devices relevant to sub-2000 K heat conversion and power beaming. However, the prohibitively high cost associated with these technologies limits their broad adoption. Herein, to alleviate this challenge we introduce an all-group IV mid-infrared cell consisting of GeSn alloy directly on a silicon wafer. This emerging class of semiconductors provides strain and composition as degrees of freedom to control the bandgap energy thus covering the entire mid-infrared range. The proposed thermophotovoltaic device is composed of a fully relaxed Ge$_{0.83}$Sn$_{0.17}$ double heterostructure corresponding to a bandgap energy of 0.29 eV. A theoretical framework is derived to evaluate cell performance under high injection. The black-body radiation absorption is investigated using the generalized transfer matrix method thereby considering the mixed coherent/incoherent layer stacking. Moreover, the intrinsic recombination mechanisms and their importance in a narrow bandgap semiconductor were also taken into account. In this regard, the parabolic band approximation and Fermi's golden rule were combined for an accurate estimation of the radiative recombination rate. Based on these analyses, power conversion efficiencies of up to 9% are predicted for Ge$_{0.83}$Sn$_{0.17}$ thermophotovoltaic cells under black-body radiation at temperatures in the 500-1500 K range. A slight improvement in the efficiency is observed under the frontside illumination but vanishes below 800 K, while the use of a backside reflector improves the efficiency across the investigated black-body temperature range. The effects of the heterostructure thickness, surface recombination velocity, and carrier lifetime are also elucidated and discussed.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.109
Threshold uncertainty score1.000

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 science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.056
GPT teacher head0.169
Teacher spread0.113 · 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.

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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