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Record W3031205490 · doi:10.1002/adom.201902098

Microscale Polarization Color Pixels from Liquid Crystal Elastomers

2020· article· en· W3031205490 on OpenAlexfundno aff
Yubing Guo, Hamed Shahsavan, Metin Sitti

Bibliographic record

VenueAdvanced Optical Materials · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced Materials and Mechanics
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaMax-Planck-GesellschaftAlexander von Humboldt-Stiftung
KeywordsMaterials scienceMicroscale chemistryLiquid crystalPixelPolarization (electrochemistry)BrightnessOpticsHueOptoelectronicsPhysics

Abstract

fetched live from OpenAlex

Abstract Liquid crystal elastomers (LCEs) attract burgeoning research interests due to their programmable 3D shape transformation and achievable large strain (up to 400%), which allow their diverse applications. One exciting application is soft microrobots towards biomedical applications. Here, it is demonstrated that polarization colors, an intrinsic property from the anisotropic nature of LCEs, can assist LCEs in their diverse applications. Microscale color pixels with sizes as small as 15 µm × 15 µm are obtained with designable colors from precisely controlled thicknesses enabled by two‐photon polymerization technique. It is then demonstrated that in‐plane rotation of LCE pixels only changes their color brightness instead of color hue and small tilting angle (<15°) causes almost no change of their color. These properties enable high‐contrast tracking of LCEs under polarized microscope. Furthermore, it is exhibited that both 2D and 3D microstructures with pre‐designed multiple colors can be realized, allowing for LCE applications requiring precise discrimination of different components. Finally, dynamic polarization colors are explored by insertion of waveplates and change of temperature, which allows for either better tracking of LCEs or applications of LCEs in temperature sensing and information encryption. It is expected that polarization colors will assist various LCE applications, especially soft microrobot and art display applications.

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 categoriesMeta-epidemiology (narrow)
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 score0.052
Threshold uncertainty score1.000

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)0.0010.000

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 head0.007
GPT teacher head0.202
Teacher spread0.195 · 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.

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

Citations41
Published2020
Admission routes1
Has abstractyes

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