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Record W2038559534 · doi:10.1021/la0626860

Electrochemical Evaluation of 4-(Dimethylamino)pyridine Adsorption on Polycrystalline Gold

2006· article· en· W2038559534 on OpenAlexaff
Burke C. Barlow, Ian J. Burgess

Bibliographic record

VenueLangmuir · 2006
Typearticle
Languageen
FieldChemistry
TopicElectrochemical Analysis and Applications
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsChemistryElectrolyteAdsorptionPyridineElectrochemistryElectrodeElectrode potentialInorganic chemistryPoint of zero chargeDifferential capacitancePhysical chemistryOrganic chemistryCapacitance

Abstract

fetched live from OpenAlex

Using differential capacity and chronocoulometry, we have studied the electrosorption of 4-(dimethylamino)pyridine (DMAP) on polycrystalline gold electrode surfaces. Our results indicate that the orientation of DMAP is highly dependent on the electrode potential and electrolyte pH. At pH values at or above the primary pKa, the adsorbed species is DMAP and orients vertically on the electrode surface via the lone pair of electrons on the pyridine ring's nitrogen atom. At very low pH values (<3) the adsorbed species is the protonated ion, DMAPH+, which can be desorbed from the electrode surface when the metal's surface charge density is made appreciably positive of the potential of zero charge. At intermediate electrolyte pH, either DMAP or DMAPH+ is adsorbed on the surface depending on the electrode's potential. At negative charge densities, DMAPH+ lies nearly flat on the gold electrode and the surface coverage is correspondingly low. When the electrode is positively charged, the adsorbate undergoes a phase transition to a vertical orientation and is simultaneously deprotonated to DMAP. Our results rationalize the stability of DMAP-ligated gold nanoparticles as a function of pH and demonstrate that the ligand's surface coverage is the principal factor in determining the stability of the colloidal system.

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 score0.023
Threshold uncertainty score0.473

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 head0.013
GPT teacher head0.256
Teacher spread0.243 · 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

Citations35
Published2006
Admission routes1
Has abstractyes

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