Chitin Liquid-Crystal-Templated Oxide Semiconductor Aerogels
Bibliographic record
Abstract
Chitin nanocrystals have been used as a liquid crystalline template to fabricate layered oxide semiconductor aerogels. Anisotropic chitin liquid crystals are transformed to sponge-like aerogels by hydrothermally cross-linked gelation and lyophilization-induced solidification. The hydrothermal gelation of chitin aqueous suspensions then proceeds with peroxotitanate to form hydrogel composites that recover to form aerogels after freeze-drying. The homogeneous peroxotitanate/chitin composites are calcined to generate freestanding titania aerogels that exhibit the nanostructural integrity of layered chitin template. Our extended investigations show that coassembling chitin nanocrystals with other metal-based precursors also yielded semiconductor aerogels of perovskite BaTiO 3 and CuO x nanocrystals. The potential of these materials is great to investigate these chitin sponges for biomedicine and these semiconductor aerogels for photocatalysis, gas sensing, and other applications. Our results present a new aerogel templating method of highly porous, ultralight materials with chitin liquid crystals.
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) | 0.001 | 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".