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Analysis of the attainable efficiency of a direct-bandgap betavoltaic element

2015· article· en· W2253641722 on OpenAlexaff

Bibliographic record

VenueJournal of Physics D Applied Physics · 2015
Typearticle
Languageen
FieldEnergy
TopicAdvanced Energy Technologies and Civil Engineering Innovations
Canadian institutionsMemorial University of NewfoundlandOntario Tech University
Fundersnot available
KeywordsRange (aeronautics)Carrier lifetimeEnergy conversion efficiencyVoltageEnergy (signal processing)DiffusionElectronIrradiation

Abstract

fetched live from OpenAlex

Conversion of energy of beta-particles into electric energy in a p-n junction based on direct-bandgap semiconductors, such as GaAs, is analyzed considering realistic semiconductor system parameters. An expression for the collection coefficient, Q , of the electron–hole pairs generated by beta-electrons is derived taking into account the existence of the dead layer. We show that the collection coefficient of beta-electrons emitted by a 3 H-source to a GaAs p-n junction is close to 1 in a broad range of electron lifetimes in the junction, ranging from 10 −9 to 10 −7 s. For the combination 147 Pm/GaAs, Q is relatively large ( ⩾ 0.4) only for quite long lifetimes (about 10 −7 s) and large thicknesses (about 100 μ m) of GaAs p-n junctions. For realistic lifetimes of minority carriers and their diffusion coefficients, the open-circuit voltage realized due to the irradiation of a GaAs p-n junction by beta-particles is obtained. The attainable beta-conversion efficiency η in the case of a 3 H/GaAs combination is found to exceed that of the 147 Pm/GaAs combination.

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)0.001
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.016
GPT teacher head0.234
Teacher spread0.218 · 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".

Quick stats

Citations5
Published2015
Admission routes1
Has abstractyes

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