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Microelectronic Circuit Characterization via Photothermal Radiometry of Scribeline Recombination Lifetime

2002· article· en· W2172997743 on OpenAlexaff
M. Rodríguez, Andreas Mandelis, Guohua Pan, José Ángel García García

Bibliographic record

VenueAnalytical Sciences/Supplements Proceedings of 11th International Conference of Photoacoustic and Photothermal Phenomena · 2002
Typearticle
Languageen
FieldEngineering
TopicThermography and Photoacoustic Techniques
Canadian institutionsMitel (Canada)University of Toronto
Fundersnot available
KeywordsWaferMicroelectronicsMasking (illustration)OptoelectronicsMaterials sciencePhotolithographyPhotothermal therapyMultivibratorFabricationCharacterization (materials science)Carrier lifetimeOpticsNanotechnologySiliconElectrical engineering

Abstract

fetched live from OpenAlex

AbstractThree-dimensional (3D) photothermal radiometric microscopic imaging and laser-intensity-modulation frequencyscans have been used for the non-contact, non-intrusive measurement of electronic transport properties of integratedcircuits in patterned 40 Si wafers. The experimental data showed that carrier recombination lifetimes along eachscribeline remain constant. However, variations in surface recombination velocities and carrier di•usion coe†cientswere found. It was further found that such variations are related to the presence of highly doped poly-Si structuresadjacent to the scribeline. As a result of these measurements, it is concluded that scribeline photothermalradiometric probing can be used e•ectively for monitoring local values of the carrier recombination lifetime and,through those, wafer contamination and damage during device fabrication processing. 7 2000 Elsevier Science Ltd.All rights reserved.1. IntroductionThere are four basic operations performed on awafer during the fabrication process: layering, pattern-ing, doping and heat treating/oxidation. Layering isthe operation used to add thin layers to the wafer sur-face. These layers are insulators, semiconductors orconductors including interconnects; they are made ofdi•erent materials and are grown or deposited by avariety of techniques [1]. Patterning is the series ofsteps that results in the removal of selected portions ofthe added layers. This process is also known as photo-masking, masking, photolithography, and microlitho-graphy. It is the patterning operation that creates thesurface parts of the device that make up a circuit. Thisoperation sets the critical dimensions of devices. Errorsin the patterning process can cause changes in the elec-trical functionality of the devices and of the circuit.Contamination in any and all of the process steps canintroduce defects and/or electrical faults leading todevice failure. Contamination problems tend to bemagnified by the fact that patterning operations areperformed on the wafer several times in the course ofthe wafer fabrication process.In recent years the laser photothermal radiometric(PTR) technique has been under development in ourlaboratory and elsewhere to perform non-contact,remote measurements of electronic transport propertiesof industrial Si wafers [2]. Several recent studies [3–5]

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 score0.002
Threshold uncertainty score0.005

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)0.0020.000

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 head0.025
GPT teacher head0.233
Teacher spread0.208 · 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".

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Citations2
Published2002
Admission routes1
Has abstractyes

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