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Record W4403950118 · doi:10.1021/acs.accounts.4c00509

Design, Exploitation, and Rational Improvements of Diazirine-Based Universal Polymer Crosslinkers

2024· article· en· W4403950118 on OpenAlexaff
Mathieu L. Lepage, Stefania F. Musolino, Jeremy E. Wulff

Bibliographic record

VenueAccounts of Chemical Research · 2024
Typearticle
Languageen
FieldChemistry
TopicChemical Reactions and Mechanisms
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsPolymerMaterials sciencePolypropyleneDiazirineFunctional polymersDendrimerPolymer sciencePolymer chemistryCovalent bondHydrosilylationChemistryChemical engineeringOrganic chemistryComposite materialCopolymerPhotochemistry

Abstract

fetched live from OpenAlex

Conspectus Addition of new covalent bonds between the chains of thermoplastic polymers (i.e., crosslinking) provides improved mechanical strength and enhanced high-temperature performance while also providing an effective strategy for photopatterning. Traditionally, however, crosslinking of each polymer substrate has required the use of a specific crosslinking technology (hydrosilylation for PDMS, vulcanization for rubber, etc.). The lack of a general solution to the challenge of polymer crosslinking means that there are many thermoplastics (e.g., polypropylene or polyhydroxyalkanoates) that have desirable properties, but which cannot be upgraded by traditional crosslinking technologies. Our lab developed the first universal crosslinkers for aliphatic polymers by leveraging trifluoromethyl aryl diazirine motifs, functional groups that have been widely used in chemical biology for >30 years, but which have seldom been exploited in materials science. These novel reagents work (via C–H insertion) on essentially any commodity polymer that contains aliphatic C–H bonds, including industrial plastics like polypropylene (the crosslinking of which has been an outstanding challenge in the field for >50 years), as well as commercially important elastomers (e.g., polydimethylsiloxane), biodegradable polymers (e.g., polycaprolactone), and green polymer materials derived from biomass (e.g., polyhydroxyalkanoates). Subsequent structure–function work from our group led to crosslinkers that were >10-fold more effective in undergoing C–H insertion with aliphatic substrates. We then developed an improved synthesis of our electronically optimized diazirines and incorporated them into a family of cleavable crosslinker reagents, which permit the on-demand generation of reprocessable thermosets. At the same time, other groups replaced the perfluoropropyl linker in our first-generation crosslinker with a series of dynamic linkages; these permit the ready generation of vitrimeric materials and can be used in the reactive compatibilization of immiscible plastic waste. Since the publication of our initial Science paper in 2019, this burgeoning field of diazirine-based polymer crosslinkers has experienced an explosion of interest. Publications from our lab and others have described the use of these reagents in covalent adhesion, photopatterning of low dielectric materials for microelectronics, and direct optical printing of quantum dots. Our crosslinkers have also been shown to heighten the robustness of ice-phobic coatings and improve the performance of woven ballistic fabric, while─perhaps most unexpectedly─substantially improving the stability of high-performance perovskite solar cells. Electronically optimized diazirines can also be used to covalently link proteins to polymer surfaces, suggesting a broad range of applications in the biocompatibilization of medical devices. This Account will summarize the development of trifluoromethyl aryl diazirine reagents for materials science over the past 5 years. A brief comparison will also be made, in the Summary and Outlook section at the end of the Account, to competing (and often complementary) reagents based upon azide and diazoalkyl motifs. Finally, we have compiled a Frequently Asked Questions list that covers many practical aspects of crosslinker design and application; this is appended as Supporting Information.

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)0.001
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.058
GPT teacher head0.360
Teacher spread0.302 · 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

Citations22
Published2024
Admission routes1
Has abstractyes

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