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Record W2133755870 · doi:10.1109/mtdt.2003.1222366

An electrical simulation model for the chalcogenide phase-change memory cell

2004· article· en· W2133755870 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicPhase-change materials and chalcogenides
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaCMC Microsystems
KeywordsChalcogenideMaterials scienceAmorphous solidPhase-change memoryRecrystallization (geology)Joule heatingElectrical resistance and conductanceChalcogenide glassPhase (matter)Quenching (fluorescence)Melting pointPhase transitionOhmic contactOptoelectronicsComposite materialThermodynamicsOpticsCrystallographyChemistryPhysics

Abstract

fetched live from OpenAlex

Chalcogenide glass is being investigated by several companies as the basis for a scalable and embeddable nonvolatile phase-change memory technology. One phase is a high-resistance amorphous phase that is obtained by melting a small volume of glass using ohmic heating, and then quenching it. The second phase is a low-resistance crystalline phase that is obtained by heating the glass to just below the melting point to promote recrystallization. This paper describes two models for such a cell. The first is a very simple single-element, lumped model that exhibits correct phase transition behavior, but is unrealistic in its sensitivity to the heating current pulses. The second, multiple-element model is able to more realistically represent cell heating and cooling behavior, and appears to be the more suitable basis for an electrical simulation model.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.428
Threshold uncertainty score0.582

Codex and Gemma teacher scores by category

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

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 head0.108
GPT teacher head0.349
Teacher spread0.240 · 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

Quick stats

Citations10
Published2004
Admission routes2
Has abstractyes

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