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Record W4250395954 · doi:10.1021/ma8020344

Self-Doped Polyaniline Nanoparticle Dispersions Based on Boronic Acid−Phosphate Complexation

2008· article· en· W4250395954 on OpenAlexaff
Bhavana Deore, Michael S. Freund

Bibliographic record

VenueMacromolecules · 2008
Typearticle
Languageen
FieldMaterials Science
TopicConducting polymers and applications
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsBoronic acidPolyanilineChemistryMoietyPhosphoric acidNanoparticleFluoridePhosphateInorganic chemistryPolymer chemistryPolymerNuclear chemistryOrganic chemistryMaterials sciencePolymerizationNanotechnology

Abstract

fetched live from OpenAlex

Poly(anilineboronic acid)/phosphate nanoparticle dispersions are produced in high yields using the reactivity of the boronic acid moiety with phosphate in the presence of fluoride. The poly(anilineboronic acid)/phosphate dispersions have been characterized using spectroscopic, microscopic, and electrochemical techniques. According to 11 B NMR studies, the formation of anionic tetrahedral boronate group in phosphoric acid in the presence of fluoride forms the basis of self-doped, stabilized PABA nanoparticle dispersion. Transmission electron microscope images show that 25−50 nm diameter PABA nanoparticles are formed under these conditions. UV−vis, FT-IR-ATR spectroscopic, and cyclic voltammetric results confirm the formation of the conducting form of PABA. Films produced from these particles exhibit enhanced redox stability and potential dependent conductivity under neutral and basic pH conditions due to the formation of a boron−phosphate complex containing fluoride, which results in a self-doped form of the polymer.

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 score0.009
Threshold uncertainty score0.740

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.021
GPT teacher head0.251
Teacher spread0.230 · 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

Citations44
Published2008
Admission routes1
Has abstractyes

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