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Record W2949647327 · doi:10.48550/arxiv.0807.1048

How the surrounding water changes the electronic and magnetic properties of DNA

2008· preprint· en· W2949647327 on OpenAlexafffund
Julia Berashevich, Tapash Chakraborty

Bibliographic record

VenuearXiv (Cornell University) · 2008
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA and Nucleic Acid Chemistry
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsNucleobaseElectronChemical physicsAntiparallel (mathematics)SpinsMoleculeSpintronicsDNAElectron transferMaterials scienceChemistryNanotechnologyPhysicsMagnetic fieldCondensed matter physicsFerromagnetismPhotochemistry

Abstract

fetched live from OpenAlex

Strong influence of water molecules on the transport and magnetic properties of DNA, observed in this study, opens up real opportunities for application of DNA in molecular electronics. Interaction of the nucleobases with water molecules leads to breaking of some of the $π$ bonds and appearance of unbound pi electrons. These unbound electrons contribute significantly to the charge transfer at room temperature by up to 1000 times, but at low temperature the efficiency of charge transfer is determined by the spin interaction of the two unbound electrons located on the intrastrand nucleobases. The charge exchange between the nucleobases is allowed only when the spins of unbound electrons are antiparallel. Therefore, the conductance of the DNA molecule can be controlled by a magnetic field. That effect has potential applications for developing a nanoscale spintronic device based on the DNA molecule, where efficiency of spin interaction will be determined by the DNA sequence.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.035
GPT teacher head0.152
Teacher spread0.117 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations0
Published2008
Admission routes2
Has abstractyes

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