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Record W4311009656 · doi:10.26434/chemrxiv-2022-88vqk

Three-in-one: dye-volatile cocrystals exhibiting intensity-dependent photo-chromic, photo-mechanical and photo-carving response

2022· preprint· en· W4311009656 on OpenAlexafffund
Tristan H. Borchers, Filip Topić, Mihails Arhangelskis, Jogirdas Vainauskas, Hatem M. Titi, Oleksandr S. Bushuyev, Christopher J. Barrett, Tomislav Friščić

Bibliographic record

VenueChemRxiv · 2022
Typepreprint
Languageen
FieldMaterials Science
TopicPhotochromic and Fluorescence Chemistry
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsIrradiationMaterials sciencePhotochemistryAzobenzeneIsomerizationPhotochromismVisible spectrumMechanochemistryCocrystalLight intensityPhotodegradationOptoelectronicsMoleculeOpticsChemistryNanotechnologyPhotocatalysisComposite materialOrganic chemistry

Abstract

fetched live from OpenAlex

Cocrystallization of a cis-azobenzene dye with volatile cocrystal former molecules, such as pyrazine and dioxane, leads to materials that exhibit at least three different light intensity-dependent responses upon irradiation with low-energy visible light. Specifically, the halogen bond-driven assembly of cis-(p-iodoperfluorophenyl)azobenzene with volatile halogen bond acceptors produces cocrystals whose light-induced behaviour varies significantly depending on the intensity of the light applied. Low-intensity (<1 mW∙cm-2) light irradiation leads to a colour change due to low levels of cis-trans isomerization. Irradiation at higher intensities (150 mW∙mm-2) produces photo-mechanical bending, caused by more extensive azo dye isomerization. At still higher irradiation intensities (2.25 W∙mm-2) the cocrystals undergo photo-carving, i.e. they are readily shaped, punctured, and cut with micrometer precision using laser light. This work demonstrates how the recently reported photo-carving behaviour can be combined with different types of photo-responses, providing a design for multi-responsive materials that can respond to different levels of irradiation with optical colour change, photo-mechanical bending, or photo-carving, as laser power is increased.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

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)0.0010.000

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 head0.030
GPT teacher head0.262
Teacher spread0.232 · 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 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

Citations1
Published2022
Admission routes2
Has abstractyes

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