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Record W2781276313 · doi:10.5539/jmsr.v7n1p20

Ionizing Radiations (Alpha, Beta, Gamma) Effects on CdS / P-Si Heterojunction Solar Cell for Electrical and Optical Properties

2017· article· en· W2781276313 on OpenAlexvenueno aff
A. A. El-Amin, Magdi Hassan Saad

Bibliographic record

VenueJournal of Materials Science Research · 2017
Typearticle
Languageen
FieldEngineering
TopicSilicon and Solar Cell Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsIrradiationMaterials scienceIonizing radiationRadiationGamma raySolar cellGamma irradiationBETA (programming language)Carrier lifetimeOptoelectronicsHeterojunctionShort circuitOpen-circuit voltageSolar cell efficiencyRadiochemistryOpticsPhysicsVoltageSiliconChemistryNuclear physics

Abstract

fetched live from OpenAlex

The effect of ionizing radiations (Alpha, Beta, Gamma) in CdS/p-Si heterojunction solar cells are discussed in this paper. The short-circuit current density parameters before Gamma irradiation conditions have been improved up to 35 mA/cm2 and after Gamma irradiation was 30 mA/cm2. The open circuit voltage before Gamma irradiation was 0.59 and 0.565 V after Gamma irradiation. The limitations of these devices were discussed by investigating the dependence of electrical and efficiency parameters in function of radiation time. The efficiency of the cell before radiation was equal to (11.2%) whenever, after the impact of both Alpha, Beta, and Gamma was follows, 4.7, 4.9, and 5.1% respectively. The fill factor before and after Gamma irradiation was 54.5 and 53 %. Studying and analyzing the cells using the I-V, with the change of time rate of Gamma radiation played a critical role in reducing the efficiency of solar cells. The campaign was carried out with different doses of a series of solar cells by exposing them to different time. The deterioration parameters of CdS/p-Si solar cells by Gamma radiation led to strongly supports the results of minority carrier lifetime, which clearly showed diminishing minority carrier lifetime with increasing radiation dose.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.007
Threshold uncertainty score0.828

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.072
GPT teacher head0.332
Teacher spread0.260 · 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 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

Citations6
Published2017
Admission routes1
Has abstractyes

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