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Record W7056566943

GaAs Solar Cells Grown on Unpolished, Spalled Ge Substrates: Preprint

2018· other· en· W7056566943 on OpenAlexfundno aff

Bibliographic record

VenueOSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · 2018
Typeother
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
FundersOffice of Energy EfficiencyOffice of Energy Efficiency and Renewable EnergyNational Renewable Energy LaboratoryCanada Excellence Research Chairs, Government of CanadaU.S. Department of Energy
KeywordsWaferSolar cellPolishingCarrier lifetimeGallium arsenideReuse
DOInot available

Abstract

fetched live from OpenAlex

Decreasing the cost of single-crystal substrates by wafer reuse techniques has long been sought for III-V solar cells. Controlled spalling of III-V devices is a possible pathway for epitaxial liftoff, which would help reduce costs, but chemo- mechanical polishing after liftoff tends to limit the potential cost savings. Growth on an unpolished spalled surface would be an additional step toward lower costs, but it is crucial to show high efficiency solar cell devices on these unprocessed substrates. In this study, we spalled 2-inch Ge wafers using a Ni stressor layer, and then grew GaAs solar cells by HVPE on the spalled Ge surface without any other surface treatment. We show a 12.8% efficient single-junction device, without anti-reflection coating, with quantum efficiency very close to identical devices grown by HVPE on non-spalled GaAs substrates. Demonstrating a high carrier collection on unpolished spalled wafers is a step toward reducing substrate-related liftoff and reuse costs.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

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)0.0030.001

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 head0.011
GPT teacher head0.237
Teacher spread0.225 · 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 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

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueOSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)→Same topicMagnetic confinement fusion research→French-language works237,207→