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Record W2510660050 · doi:10.1021/acs.jpcc.5b05418

Tailoring the Reaction Path in the On-Surface Chemistry of Thienoacenes

2015· article· en· W2510660050 on OpenAlexafffund
Laurentiu E. Dinca, Jennifer MacLeod, Josh Lipton‐Duffin, Chaoying Fu, Dongling Ma, Dmitrii F. Perepichka, Federico Rosei

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2015
Typearticle
Languageen
FieldEngineering
TopicSurface Chemistry and Catalysis
Canadian institutionsMcGill UniversityInstitut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of CanadaFonds de recherche du Québec – Nature et technologiesAlexander von Humboldt-Stiftung
KeywordsIntramolecular forceDehydrogenationChemistryTransition metalMoleculeIntermolecular forceMetalOrganosiliconMonomerAnthraceneThiophenePhotochemistryCatalysisPolymer chemistryOrganic chemistryPolymer

Abstract

fetched live from OpenAlex

Oligothiophenes provide rich opportunities for surface confined reactions that can lead to two-dimensional materials. We have performed systematic studies of tetrathieno-anthracene (TTA) based molecules on different transition metal surfaces to reveal the details of their on-surface chemistry. On the (111) surfaces of Ni, Pd, and Cu, we observe the sulfur abstraction from the monomer following thermal activation, whose yield varies with the type of metal surface. On Ni(111) and Pd(111) the internal design of the 2TTA isomer promotes intramolecular rebonding to produce pentacene, whereas geometrical constraints prevent the 3TTA isomer from intramolecular rebonding, promoting oligomerization. On Cu(111), desulfurization is preceded by dehydrogenation, which introduces metal-mediated intermolecular coupling in 2TTA. This organometallic phase is stable up to 200 °C. On all surfaces, the desulfurization and dehydrogenation of the molecules are important reaction pathways which define the bonding geometries of the products.

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 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 score0.057
Threshold uncertainty score0.298

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
Research integrity0.0000.001
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 head0.225
Teacher spread0.208 · 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

Citations12
Published2015
Admission routes2
Has abstractyes

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