Silicone Shell‐Encapsulated Cholesteric Liquid Crystals and Their Colorimetric Characterization in HSV Color Space
Bibliographic record
Abstract
ABSTRACT Cholesteric liquid crystals (ChLCs) display varying color upon the reflection of incident white light, whereby the half‐rotation spacing of their helical structures modulate in response to temperature changes. Blending multiple ChLCs allows fine‐tuning of the operation temperature. To achieve ChLC‐based colorimetric sensor at physiological temperature ranges in aqueous gel environment, current study provides solutions in preventing dissolution of ChLC molecules into the aqueous phase and analyzing molecular ordering of ChLC based on colorimetric information. Here, we developed a two‐step fabrication procedure to encapsulate liquid crystals in a silicone shell. A droplet of the ChLC melt was coated with Sylgard 184 base containing platinum (Pt) catalyst. Then, the coated droplets were immersed in a mixture of the base and curing agent. Robustly encapsulated ChLC samples were produced, followed by embedding in a polyacrylamide hydrogel matrix. The ChLC‐embedded hydrogel provided a colorimetric temperature sensor operating in physiological conditions. A hue‐saturation‐value (HSV) analysis of photo image taken by a cell phone camera provides valuable information not only on the ambient temperature, but also on the ordering of ChLC at various length scales. The ordering is correlated with varying temperature and confinement. Our novel fabrication and colorimetric analysis methods provide a second look at often overlooked aspects in ChLC and sensor research.
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 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) | 0.000 | 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".