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Record W4389527256 · doi:10.1002/adts.202300600

Modulating Optical Properties of Graphene with the help of Two‐Dimensional Metal‐Organic Networks

2023· article· en· W4389527256 on OpenAlex
Hamed Abbasian

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

VenueAdvanced Theory and Simulations · 2023
Typearticle
Languageen
FieldMaterials Science
TopicGraphene research and applications
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsGrapheneExcitationMaterials scienceDensity functional theoryModulation (music)Chemical physicsAb initioThermal stabilityMetalThermalMolecular dynamicsNanotechnologyOptoelectronicsComputational chemistryChemistryPhysicsQuantum mechanicsThermodynamics

Abstract

fetched live from OpenAlex

Abstract We utilize density functional theory to explore dicarbonitrile‐polyphenyl networks overlaid on graphene as a method for manipulating the density of Li atoms in a specific assembly pattern. Ab initio molecular dynamics calculations affirm the thermal stability of the introduced systems. We scrutinized the electronic structure and optical properties of the resultant systems, illustrating a systematic modulation of optical characteristics. Our results suggest that the optical excitation frequencies of (Li‐dicarbonitrile‐polyphenyl)/G can be efficiently tuned by systematically adjusting the density of Li atoms on graphene.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.228
Threshold uncertainty score0.197

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 head0.018
GPT teacher head0.272
Teacher spread0.255 · 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