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Thermionic Energy Conversion:Fundamentals and Recent Progress Enabled by Nanotechnology

2019· article· en· W3023831513 on OpenAlexaff
Alireza Nojeh

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicThermal Radiation and Cooling Technologies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsThermionic emissionEnergy transformationNanotechnologyPresentation (obstetrics)ElectricitySystems engineeringComputer scienceEngineeringEngineering physicsMaterials scienceElectrical engineeringPhysics

Abstract

fetched live from OpenAlex

Thermionic energy conversion represents a simple and elegant approach for harvesting heat to generate electricity. This conversion mechanism has been known for over a century and has experienced several waves of interest in research and development. However, significant challenges related to materials properties and fabrication technologies have prevented the creation of efficient and practical devices, hindering broad adoption of this concept.In this presentation, the fundamentals of thermionic energy conversion will be reviewed and the parameters affecting converter performance discussed. Some of the past device examples will be briefly looked at and their challenges highlighted. Over the last two decades, interest in thermionic energy conversion has gradually resurfaced due to the advances in materials and fabrication processes, which have provided opportunities for addressing the long -standing challenges in this field. Several of the key recent developments will be described and the current status and future outlook discussed. It will be seen that new effects and nanomaterials sometimes necessitate a more sophisticated experimental approach to the study of their fundamental properties for thermionic emission and conversion than commonly used in the past.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.699
Threshold uncertainty score0.764

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 head0.004
GPT teacher head0.183
Teacher spread0.179 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations3
Published2019
Admission routes1
Has abstractyes

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