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Record W2053791020 · doi:10.1002/adfm.201402468

Long Passage Times of Short ssDNA Molecules through Metallized Nanopores Fabricated by Controlled Breakdown

2014· article· en· W2053791020 on OpenAlexafffund
Harold Kwok, Matthew Waugh, José Bustamante, Kyle Briggs, Vincent Tabard‐Cossa

Bibliographic record

VenueAdvanced Functional Materials · 2014
Typearticle
Languageen
FieldEngineering
TopicNanopore and Nanochannel Transport Studies
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaSecretaría de Educación Superior, Ciencia, Tecnología e Innovación
KeywordsNanoporeMaterials scienceSilicon nitridePassivationNanotechnologyMembraneDielectricDwell timeDielectric strengthFabricationMillisecondNitrideOptoelectronicsSiliconChemistryLayer (electronics)

Abstract

fetched live from OpenAlex

The fabrication of individual nanopores in metallized dielectric membranes using controlled breakdown directly in solution is described. Nanopores as small as 1.5‐nm in diameter are fabricated in Au‐coated silicon nitride membranes immersed in 1 m KCl by subjecting them to high electric fields. The physical and electrical characteristics of nanopores produced with this method are presented. The translocation of short single‐stranded DNA molecules is demonstrated through such nanopore devices without further passivation of the metallic surface. Metallized nanopores can prolong the translocation times of 50‐nt ssDNA fragments by as much as two orders of magnitude, while the slowest events can reach an average speed as slow as 2 nucleotides per millisecond. The mechanism for the long dwell‐time distribution is differentiated from prior studies, which relied on friction to slow down DNA, and is attributed to nucleotide‐Au interactions.

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 categoriesMeta-epidemiology (narrow)
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 score0.131
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.007
GPT teacher head0.205
Teacher spread0.197 · 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.

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

Citations37
Published2014
Admission routes2
Has abstractyes

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