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Record W2955254893 · doi:10.1080/10426507.2019.1603234

Carbon nanotube alignment and sorting: Attempting a sulfur moiety as anchoring component

2019· article· en· W2955254893 on OpenAlexaff
Monika R. Kulak, Derek J. Schipper

Bibliographic record

VenuePhosphorus, sulfur, and silicon and the related elements · 2019
Typearticle
Languageen
FieldMaterials Science
TopicCarbon Nanotubes in Composites
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsAnchoringMoietyComponent (thermodynamics)Carbon nanotubeSortingSulfurNanotubeNanotechnologyMaterials scienceChemistryComputer scienceStereochemistryEngineeringPhysicsOrganic chemistryStructural engineeringAlgorithm

Abstract

fetched live from OpenAlex

Previously, the Schipper group established a method for simultaneously sorting and aligning single walled carbon nanotubes using an alignment relay technique (ART) with molecule 1. Here, further synthetic investigations were pursued to explore another anchoring group and expand functionalization onto different surfaces, in particular for gold substrates. A thiophosphonate moiety (2) is attempted as a substitute for the phosphonate ester on 1 as sulfur has been shown to efficiently chemisorb onto gold surfaces and could make an interesting substrate pursuit for better carbon nanotube alignment. For 2 – it has potential to be obtained through the use of Lawesson’s reagent, although currently the synthesis here failed to demonstrate isolation of the compound. Therefore, additional screening for different intermediate sulfur aligning molecules was also conducted, as to improve the density along side molecule 1 for ART applications. Outcomes are compared with the results on gold surfaces yielding from 1 to establish if more or fewer nanotubes are present on the surface in a horizontally aligned manner with respect to one another. Orientation is characterized via atomic force microscopy and chiralities of the nanotubes are observed via Raman spectroscopy.

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)0.001
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 score0.079
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.001
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 head0.007
GPT teacher head0.226
Teacher spread0.219 · 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

Citations7
Published2019
Admission routes1
Has abstractyes

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