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Record W2298955823 · doi:10.1021/acs.chemmater.5b04028

Biological Imaging and Sensing with Multiresponsive Microgels

2015· article· en· W2298955823 on OpenAlexafffund
Qiang Zhang, Wenda Wang, Yaqiong Su, Emiel J. M. Hensen, Michael J. Serpe

Bibliographic record

VenueChemistry of Materials · 2015
Typearticle
Languageen
FieldMaterials Science
TopicPhotochromic and Fluorescence Chemistry
Canadian institutionsUniversity of Alberta
FundersGrand Challenges CanadaCanada Foundation for InnovationNatural Sciences and Engineering Research Council of CanadaGovernment of CanadaGovernment of Alberta
KeywordsSpiropyranMaterials scienceResponsivityIsomerizationPhotochromismMerocyaninePhotochemistryFluorescenceOptoelectronicsNanotechnologyOpticsPhotodetectorChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

High Resolution Image Download MS PowerPoint Slide Multiresponsive spiropyran-modified poly( N -isopropylacrylamide)-based microgels were synthesized and their response to temperature; UV, visible, and near-infrared radiation; pH; and Cu 2+ was investigated. The responses were a result of the spiropyran groups undergoing a reversible isomerization/reaction from a neutral to a charged form. The isomerization process was investigated via experiment and theory. The two-photon excited fluorescence of the spiropyran-modified microgels was also characterized, and their ability to be used to image live cells was determined. Finally, optical devices (etalons) were fabricated using the spiropyran-modified microgels, and the ability of the devices to change color in response to the above-mentioned stimuli was also investigated. We found that the microgel’s responsivity was retained in the etalon, which yielded color tunable devices and sensors. This investigation illustrates the versatility of pNIPAm-based microgels and microgel-based etalons and showcases the clear utility of such devices for remote actuation, color tunable optics, sensing, and remotely triggered drug delivery systems.

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)0.000
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 score0.468

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.022
GPT teacher head0.240
Teacher spread0.218 · 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

Citations94
Published2015
Admission routes2
Has abstractyes

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