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Record W4406137483 · doi:10.1109/tdei.2025.3526737

A DFT Study of Polyethylene Chain Deformation and Copper Surface Oxidation Effects on Charge Injection Barriers at Cu-PE Interfaces

2025· article· en· W4406137483 on OpenAlexaff
Y. El-Sayed, A S Huzayyin, Essam M. A. Elkaramany

Bibliographic record

VenueIEEE Transactions on Dielectrics and Electrical Insulation · 2025
Typearticle
Languageen
FieldEngineering
TopicElectrostatic Discharge in Electronics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPolyethyleneMaterials scienceCopperPolymerDeformation (meteorology)Lamella (surface anatomy)Work functionImpurityCharge densityDensity functional theoryChemical physicsMetalPhysical chemistryComposite materialComputational chemistryChemistryMetallurgyOrganic chemistryPhysics

Abstract

fetched live from OpenAlex

Chemical and physical defects (impurities and deformations, respectively) at the metal/polymer hetero-structures play a vital role in the charge injection process at the metal/polymer interface. The objective of the present work is to study the effect of polyethylene chain deformation and copper surface oxidation on the barriers to charge injection at the Cu <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">(111)</sub> /PE <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">(001)</sub> interface. The chain deformation in polyethylene is represented by lamella structure, in addition, copper surface oxidation appears using oxygen adatom impurities. The electronic properties of these structures are studied using density functional theory as a computational quantum mechanical method. The computations concluded that lamella and oxygen adatom defects produce the deepest trap states for holes 0.6 eV and electrons 0.77 eV, respectively. Additionally, this work concludes that the studied defects cannot explain the barrier to injection of 1 eV at the copper/polyethylene interfaces alone.

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 categoriesMeta-epidemiology (narrow)
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 score0.337
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.225
Teacher spread0.220 · 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.

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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueIEEE Transactions on Dielectrics and Electrical InsulationSame topicElectrostatic Discharge in ElectronicsFrench-language works237,207