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Record W2054040854 · doi:10.1021/ac015635a

Monitoring the Interfacial Capacitance at Self-Assembled Phosphate Monolayers on Gold Electrodes upon Interaction with Calcium and Magnesium

2002· article· en· W2054040854 on OpenAlexaff
Johan Ekeroth, Peter Konradsson, Fredrik Björefors, Ingemar Lundström, Bo Liedberg

Bibliographic record

VenueAnalytical Chemistry · 2002
Typearticle
Languageen
FieldEngineering
TopicMolecular Junctions and Nanostructures
Canadian institutionsEngineering Link (Canada)
FundersVINNOVAStiftelsen för Strategisk Forskning
KeywordsChemistryMagnesiumCapacitanceMonolayerInorganic chemistryElectrolyteCalciumElectrodePhosphateDivalentElectrochemistryBiochemistryOrganic chemistryPhysical chemistry

Abstract

fetched live from OpenAlex

Electrochemical impedance spectroscopy has been used to evaluate the change in interfacial capacitance upon calcium and magnesium coordination to a phosphate-modified electrode. The phosphate electrode was prepared via immobilization of phosphorylated, thiol-containing, serine analogues onto gold. Upon subjection to calcium and magnesium, a substantial drop in capacitance was observed. Magnesium displayed the largest influence on the capacitance: a 27% capacitance drop was observed upon introduction of a 1 mM solution of magnesium ions. The lowered capacitance is a result of a change in the potential and charge distribution at the film/electrolyte interface as the cations coordinate to the phosphate groups. Moreover, the relationship between electrode potential and capacitance has been investigated and reveals a significant difference between monovalent and divalent cations. As complementary information, infrared reflection absorption spectra of the phosphorylated monolayer having different counterions are presented. The results reported in this paper indicate that the phosphorylated amino acid analogue monolayers could be used in investigations of the biochemically important coordination of calcium and magnesium to phosphates and phosphorylated amino acids.

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 score0.038
Threshold uncertainty score0.493

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 head0.010
GPT teacher head0.206
Teacher spread0.196 · 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

Citations19
Published2002
Admission routes1
Has abstractyes

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