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Record W4386251282 · doi:10.1021/accountsmr.3c00124

Unlocking New Applications for Thermally Activated Delayed Fluorescence Using Polymer Nanoparticles

2023· article· en· W4386251282 on OpenAlexafffund
Jana R. Caine, Peiqi Hu, Athan T. Gogoulis, Zachary M. Hudson

Bibliographic record

VenueAccounts of Materials Research · 2023
Typearticle
Languageen
FieldMaterials Science
TopicLuminescence and Fluorescent Materials
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of British ColumbiaCanada Research Chairs
KeywordsNanoparticleNanotechnologyFluorescenceMaterials scienceNanomaterialsBiomoleculePolymerBiological imagingCyanineBioconjugationOLEDOptoelectronics

Abstract

fetched live from OpenAlex

Conspectus Thermally activated delayed fluorescence (TADF) materials are widely used in organic light-emitting diodes, but their long emission lifetimes also make them ideal for use in bioimaging probes, fluorescent sensors, and phototheranostics. Unfortunately, their development toward these applications has been restricted by the poor compatibility of most TADF materials with aqueous conditions. This problem can be addressed by encapsulating TADF dyes into nanoparticles that form stable aqueous suspensions, while preserving─or even enhancing─the photophysical properties of the TADF emitters they contain. Free of heavy metals, these nanoparticles can exhibit reduced cytotoxicity, improved oxygen tolerance, and higher brightness compared to unencapsulated TADF emitters. This Account discusses recent advances in the development and application of TADF-active polymer nanoparticles for use as biocompatible imaging probes and stimuli-responsive materials. We demonstrate that the encapsulation of TADF emitters into semiconducting polymer dots (Pdots), aggregated organic dots (a-Odots) and glassy organic dots (g-Odots) results in nanoparticles with tunable sizes, surface chemistries, and optoelectronic properties. These nanomaterials are particularly well-suited for bioimaging applications, with customizable bioconjugate chemistry and emission profiles ranging from deep-blue to near-infrared. As TADF materials generate long-lived emission, time-resolved fluorescence imaging can be used to obtain images with high signal-to-noise ratios against background biological autofluorescence. Materials with multiphoton absorbance properties capable of near-infrared excitation are also presented. We further discuss strategies for chemically modifying the nanoparticles’ coronas using biomolecules and cell-penetrating motifs to target biological structures both internal and external to the cell. With these strategies, high-contrast imaging of human breast, liver, and kidney cancer cells has been achieved. The ability to target TADF-active nanoparticles to specific tissues, such as cancer cells, has also spurred advances in phototheranostics, which harness the ability for TADF materials to produce cytotoxic singlet oxygen upon irradiation with light. Lastly, as TADF materials can exhibit changes in emission with response to oxygen, temperature, and solvent conditions, we discuss how polymer integration can be used to generate highly effective probes for environmental stimuli. These sensors have potential applications as both in vitro nanosensors and in vivo molecular reporters for disease detection. As an alternative type of sensor, TADF materials have also been employed as reporters in electrochemiluminescence assays for biomarker detection. To explore stimulus–polymer interactions on a fundamental level, the incorporation of TADF materials into bottlebrush polymers is also discussed. Overall, this Account demonstrates that polymer nanoparticles containing TADF emitters have great potential to spur new technologies in fluorescence imaging, sensing, and bioanalysis.

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)0.003
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 score0.003
Threshold uncertainty score0.875

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.112
GPT teacher head0.390
Teacher spread0.278 · 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

Citations49
Published2023
Admission routes2
Has abstractyes

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