“Shine & Click” Photo‐Induced Interfacial Unmasking of Strained Alkynes on Small Water‐Soluble Gold Nanoparticles
Bibliographic record
Abstract
Abstract In this study, we report the design, synthesis, and characterization of small 3 nm water soluble gold nanoparticles (AuNPs) that feature cyclopropenone‐masked strained alkyne moieties capable of undergoing interfacial strain‐promoted cycloaddition (i‐SPAAC) with azides after exposure to UV‐A light. A strained alkyne precursor was incorporated onto AuNPs by direct ligand exchange of a thiol‐modified cyclopropenone‐masked dibenzocyclooctyne (photoDIBO) ligand. These photoDIBO‐AuNPs were characterized by 1H NMR, IR, and UV/Vis spectroscopy, as well as transmission electron microscopy (TEM) and thermogravimetric analysis (TGA), and the extent of modification was quantified. Upon irradiation with UV‐A light, photoDIBO‐AuNPs underwent efficient and quantitative regeneration of the parent strained alkyne by photochemical decarbonylation to afford DIBO‐derivatized AuNPs. DIBO‐AuNPs were found to react cleanly and rapidly (k=5.3×10−2 m−1 s−1) by an interfacial strain‐promoted alkyne‐azide cycloadditon (i‐SPAAC) with benzyl azide, which served as a simple model system. Furthermore, DIBO‐AuNPs were reacted with various azides and a nitrone (interfacial strain‐promoted alkyne‐nitrone cycloaddition, i‐SPANC) to showcase the generality of this approach for the facile modification of AuNP surfaces and their properties. The cyclopropenone‐based photo‐triggered click chemistry at the interface of water‐soluble AuNPs offers exciting opportunities for the atom‐by‐atom control and assembly of functional materials for applications in materials and biomaterials science as well as in chemical biology.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".