MétaCan
Menu
Back to cohort
Record W2031613325 · doi:10.1021/jp511396n

Structural and Electronic Properties of Pristine and Doped Polythiophene: Periodic versus Molecular Calculations

2015· article· en· W2031613325 on OpenAlexafffund

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2015
Typearticle
Languageen
FieldMaterials Science
TopicConducting polymers and applications
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanada Foundation for Innovation
KeywordsPolythiopheneStackingBilayerOligomerBand gapDensity functional theoryMonolayerDoping

Abstract

fetched live from OpenAlex

Based on density functional theory calculations, the structural and electronic properties of polythiophene in periodic and oligomer forms have been investigated. In particular, the effects of Li or Cl adsorption onto a monolayer and Li or Cl intercalation into bulk or bilayer polythiophene are addressed using periodic calculations. The binding energy of Li or Cl adsorbed bulk or bilayer polythiophene is significantly larger than for the monolayer. The trends in the binding energy as a function of adsorbent remain the same for both the periodic and molecular cases. The band gap or HOMO–LUMO gap and charge transfer are analyzed. In addition, for the bulk or bilayer, different kinds of stacking have been considered. It is found that the parallel bulk or bilayer structure is energetically favorable compared to flipping the second layer by 180°. This has been considered for both the periodic and oligomer forms. Moreover, for Li adsorption, polarons are found to be more stable than bipolarons, while the situation is opposite for Cl adsorption. The detailed analysis of the present study will be useful for understanding the structural properties and the tuneability of the electronic states, which is an important step to construct polythiophene-based electronic devices.

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 score0.001
Threshold uncertainty score0.144

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 head0.026
GPT teacher head0.262
Teacher spread0.236 · 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

Citations46
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueThe Journal of Physical Chemistry CSame topicConducting polymers and applicationsFrench-language works237,207