Infiltration of Proteins in Cholesteric Cellulose Structures
Bibliographic record
Abstract
Cellulose nanocrystals (CNCs) can spontaneously self-assemble into chiral nematic (cn) structures, similar to natural cholesteric organizations. The latter display highly dissipative fracture propagation mechanisms given their "brick" (particles) and "mortar" (soft matrix) architecture. Unfortunately, CNCs in liquid media have strong supramolecular interactions with most macromolecules, leading to aggregated suspensions. Herein, we describe a method to prepare nanocomposite materials from chiral nematic CNCs (cn-CNCs) with strongly interacting secondary components. Films of cn-CNCs were infiltrated at various loadings with strongly interacting silk proteins and bovine serum albumin. For comparison and to determine the molecular weight range of macromolecules that can infiltrate cn-CNC films, they were also infiltrated with a range of poly(ethylene glycol) polymers that do not interact strongly with CNCs. The extent and impact of infiltration were evaluated by studying the optical reflection properties of the resulting hybrid materials (UV-vis spectroscopy), while fracture dissipation mechanisms were observed via electron microscopy. We propose that infiltration of cn-CNCs enables the introduction of virtually any secondary phase for nanocomposite formation that is otherwise not possible using simple mixing or other conventional approaches.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".