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Record W2164479992 · doi:10.1080/01971520500287883

Cost-Effective, Silicon-Based Solar Cells: Material and Technology Issues

2006· article· en· W2164479992 on OpenAlexaff
Siva Sivoththaman, Mahdi Farrokh Baroughi

Bibliographic record

VenueInternational Journal of Green Energy · 2006
Typearticle
Languageen
FieldEngineering
TopicNanowire Synthesis and Applications
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsRenewable energyPhotovoltaicsCost reductionSolar energyProcess engineeringSolar cellCrystalline siliconPhotovoltaic systemCost effectivenessProduction costFabricationManufacturing costSiliconEnvironmentally friendlyEfficient energy useEngineeringMaterials scienceElectrical engineeringMechanical engineeringBusinessOperations management

Abstract

fetched live from OpenAlex

Affordability is the key to any renewable energy technology in becoming a viable alternative to conventional energy technology. Solar photovoltaics (PV) is a promising and environment-friendly energy conversion technique, experiencing steady market growth. Cost reduction of PV cells relies largely on the use of low-cost silicon materials which tend to compromise the device performance. This underscores the need for new, material-specific process technologies to be used in order to achieve an acceptable $/Wp. In this paper, first an overview of different techniques for the fabrication of low-cost silicon will be presented. We highlight the need to modify the processing technology while using defective, cost-effective Si substrates. This is followed by the description of research efforts on the development of a cost-effective heterojunction cell fabrication technology, as well as the results on the simplified process.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0010.000
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.005
GPT teacher head0.222
Teacher spread0.217 · 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 designTheoretical or conceptual
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

Citations8
Published2006
Admission routes1
Has abstractyes

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