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Record W1986894181 · doi:10.1063/1.3122052

Observation of surface enhanced IR absorption coefficient in alkanethiol based self-assembled monolayers on GaAs(001)

2009· article· en· W1986894181 on OpenAlexaff
Gregory M. Marshall, Farid Bensebaa, Jan J. Dubowski

Bibliographic record

VenueJournal of Applied Physics · 2009
Typearticle
Languageen
FieldEngineering
TopicMolecular Junctions and Nanostructures
Canadian institutionsNational Research Council CanadaUniversité de Sherbrooke
Fundersnot available
KeywordsMonolayerAbsorbanceAnalytical Chemistry (journal)Infrared spectroscopyAbsorption (acoustics)Phase (matter)Fourier transform infrared spectroscopyAbsorption spectroscopyAttenuation coefficientInfraredMaterials scienceFourier transformChemistryOpticsNanotechnologyOrganic chemistry

Abstract

fetched live from OpenAlex

Alkanethiol self-assembled monolayers (SAMs) of various methylene group chain lengths [HS–(CH2)n–CH3] (n=9,11,13,15,17) were fabricated on the GaAs(001) surface followed by characterization using Fourier transform infrared spectroscopy. Modal analysis of the CH2 stretching mode region (2800–3000 cm−1) showed that linear scaling of the n-dependent factors accurately reproduced the spectral data, supporting a chain-length consistent physical model upon which a measurement of the absorption coefficient was based. Evaluated from the linearity of the absorbance data, a peak coefficient of 3.5×104 cm−1 was obtained and a domain for ordered self-assembly was assigned for values n>9. Compared with measurements of the absorption coefficient made in the liquid phase, the SAM phase coefficient was determined to be about six times greater. This enhancement effect is discussed in terms of contributions relating to the locally ordered environment and is largely attributed to the chemical properties of the interface. We believe this to be the first demonstration of IR spectral enhancement of a molecular species chemisorbed on the semiconductor surface.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.352
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 head0.008
GPT teacher head0.210
Teacher spread0.202 · 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

Citations22
Published2009
Admission routes1
Has abstractyes

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