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Record W2023083500 · doi:10.1063/1.1617975

Nuclear spin polarization transfer across an organic-semiconductor interface

2003· article· en· W2023083500 on OpenAlexaff
Lucas Goehring, Carl A. Michal

Bibliographic record

VenueThe Journal of Chemical Physics · 2003
Typearticle
Languageen
FieldChemistry
TopicAdvanced NMR Techniques and Applications
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSpin diffusionOverlayerPolarization (electrochemistry)Spin polarizationSemiconductorOrganic semiconductorMagnetization transferChemistryOptical pumpingInduced polarizationChemical physicsNuclear magnetic resonanceCondensed matter physicsMolecular physicsMaterials scienceOptoelectronicsOpticsPhysicsNuclear physicsPhysical chemistryElectronMagnetic resonance imagingElectrical resistivity and conductivity

Abstract

fetched live from OpenAlex

Motivated by Tycko’s proposal to harness optically pumped nuclear spin polarization for the enhancement of nuclear magnetic resonance (NMR) signals from biological macromolecules, we investigate the transfer of thermal nuclear spin polarization between H1 or F19 in an organic overlayer and P31 at the surface of micron-sized InP particles by Hartmann–Hahn cross polarization. Comparison with analytic and numerical models indicates that the total quantity of polarization transferred across the semiconductor-organic interface is limited by the relatively short room-temperature H1 T1ρ (11 ms) and the slow diffusion of nuclear spin polarization in the semiconductor. Models and spin-counting experiments indicate that we are able to transfer approximately 20% of the total nuclear spin polarization originating in the organic overlayer to the semiconductor, supporting the feasibility of transferred optically pumped NMR.

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 score0.032
Threshold uncertainty score0.316

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 head0.017
GPT teacher head0.301
Teacher spread0.284 · 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

Citations16
Published2003
Admission routes1
Has abstractyes

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