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Record W2059240780 · doi:10.1117/12.873111

A low temperature fabrication process utilizing FIB implantation for CMOS compatible photovoltaic cells

2010· article· en· W2059240780 on OpenAlexaff
Jasbir N. Patel, Clinton Landrock, Badr Omrane, Bożena Kamińska, Bonnie L. Gray

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2010
Typearticle
Languageen
FieldEngineering
TopicIntegrated Circuits and Semiconductor Failure Analysis
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsCMOSFabricationPhotovoltaic systemMaterials scienceWaferOptoelectronicsIon implantationFocused ion beamDie (integrated circuit)Integrated circuitElectrical engineeringNanotechnologyIonEngineering

Abstract

fetched live from OpenAlex

In this article, we present a novel low temperature fabrication process using focused ion beam (FIB) for CMOS compatible photovoltaic cells. Photovoltaic cells are used for scavenging light energy to power CMOS devices and integrating photovoltaic cells on the same CMOS die for self-powering integrated circuits is highly desirable. Integrating such photovoltaic cells as a post-process of the pre-fabricated CMOS die will avoid many complex assembling steps as well as unpredictable interconnect problems. To demonstrate the proof of concept, we have developed low temperature fabrication process to avoid damage to the pre-fabricated CMOS dies. We are also going to introduce focused-ion beam (FIB) as an implantation source to dope silicon wafer for desired concentration. The successfully fabricated demonstration device is tested using a solar simulator. The results obtained from the experimental data indicate that the demonstration device works perfectly as a photovoltaic cell rather with very low efficiency (0.004%).

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 score0.001
Threshold uncertainty score0.004

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 science0.0010.000
Research integrity0.0010.000
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 head0.009
GPT teacher head0.222
Teacher spread0.214 · 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

Citations1
Published2010
Admission routes1
Has abstractyes

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Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicIntegrated Circuits and Semiconductor Failure AnalysisFrench-language works237,207