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Record W1935573476 · doi:10.1109/mtdt.1994.397200

Mega bit CMOS SRAM chip failure analysis using external electrical testing and internal contactless laser beam testing

2002· article· en· W1935573476 on OpenAlex
V.N. Rayapati, Bożena Kamińska

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicIntegrated Circuits and Semiconductor Failure Analysis
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsStatic random-access memoryChipCMOSElectronic engineeringEmbedded systemCapacitive couplingComputer scienceComputer hardwareEngineeringElectrical engineeringVoltage

Abstract

fetched live from OpenAlex

A powerful failure analysis method for mega bit CMOS SRAM chip presented in this paper, is very useful in the CAD environment. The SRAM chip functional test allows the detection of permanent/intermittent faults which could cause the SRAM chip to function incorrectly. These faults are stuck-at-1 or stuck-at-0 based on physical failures like metallization shorts and capacitive coupling. Then, a laser beam, integrated in an automatic test equipment, provides an accurate localization of SRAM chip failures using memory chip layout. This paper demonstrates that the association of an electrical tester and an internal contactless laser beam tester makes easier the localization of failures in the SRAM chip and consequently reduces the test cost.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.846
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.029
GPT teacher head0.217
Teacher spread0.188 · 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