Coassembling Hydroxypropyl Cellulose into a Chiral Nematic Composite and Patternization with a Photomask and Direct Ink Writing
Bibliographic record
Abstract
Additive manufacturing (AM) is a next-generation technique for engineering hierarchically structured materials. The development of sustainable ink materials for AM is imperative. In this work, we explored hydroxypropyl cellulose (HPC) as a sustainable photonic ink for patterning by photomask and direct ink writing techniques. Specifically, we comprehensively investigated the coassembly behavior of HPC with a guest monomer into a chiral nematic structure and the parameters that affect the transition from a solution to composite film of HPC/monomer. The results reveal that the HPC/monomer has the ability to form a chiral nematic structure, and such a hierarchical structure can reflect light with a specific wavelength. The helical pitch in the chiral nematic structure, corresponding to the reflected wavelength, can be modulated via HPC concentration, the addition amount of monomer, cross-linking time, and drying temperature. Additionally, the composite exhibits robust mechanical properties and is capable of tolerating a wet environment (both high relative humidity and water). This comprehensive study is a fascinating example of using a sustainable cellulose derivative as a 3D printing ink and provides powerful support for the development of structural color materials.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".