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Record W2793533029 · doi:10.1088/1361-6463/aab395

Simultaneous determination of effective carrier lifetime and resistivity of Si wafers using the nonlinear nature of photocarrier radiometric signals

2018· article· en· W2793533029 on OpenAlexafffund
Qiming Sun, Alexander Melnikov, Jing Wang, Andreas Mandelis

Bibliographic record

VenueJournal of Physics D Applied Physics · 2018
Typearticle
Languageen
FieldEngineering
TopicThermography and Photoacoustic Techniques
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of ChinaCanada Research ChairsCanada Foundation for Innovation
KeywordsWaferMaterials scienceElectrical resistivity and conductivityRadiometric datingOptoelectronicsNonlinear systemAnalytical Chemistry (journal)ChemistryRemote sensingEnvironmental chemistryPhysicsGeology

Abstract

fetched live from OpenAlex

Abstract A rigorous treatment of the nonlinear behavior of photocarrier radiometric (PCR) signals is presented theoretically and experimentally for the quantitative characterization of semiconductor photocarrier recombination and transport properties. A frequency-domain model based on the carrier rate equation and the classical carrier radiative recombination theory was developed. The derived concise expression reveals different functionalities of the PCR amplitude and phase channels: the phase bears direct quantitative correlation with the carrier effective lifetime, while the amplitude versus the estimated photocarrier density dependence can be used to extract the equilibrium majority carrier density and thus, resistivity. An experimental ‘ripple’ optical excitation mode (small modulation depth compared to the dc level) was introduced to bypass the complicated ‘modulated lifetime’ problem so as to simplify theoretical interpretation and guarantee measurement self-consistency and reliability. Two Si wafers with known resistivity values were tested to validate the method.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.087
Threshold uncertainty score0.598

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.006
GPT teacher head0.240
Teacher spread0.234 · 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

Citations17
Published2018
Admission routes2
Has abstractyes

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