Liquid Printing in Nanochitin Suspensions: Interfacial Nanoparticle Assembly Toward Volumetric Elements, Organic Electronics and Core–Shell Filaments
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A nanoparticle-nanoparticle assembly is introduced using electrostatic complexation to precisely control volumetric structuring at the water/alcohol interface. In this system, an aqueous graphene oxide (GO) ink interacts electrostatically with partially deacetylated chitin nanofibers (mChNF), modified with benzophenone and dispersed in 1-butanol, which serves as the external phase. Upon extrusion of the GO ink, a jammed interfacial network forms, stabilizing the printed patterns within the external suspension, which provides suitable viscoelasticity for support-free printing. This approach is further extended to inks incorporating metal-organic frameworks or cellulose nanoparticles, demonstrating the advantages of mChNF as a stabilizer. Additionally, by incorporating a conductive polymer, the inks can be tailored for programmable and conductive patterning, opening new opportunities in liquid electronics and reconfigurable systems. Finally, GO inks containing an anionic polyelectrolyte (sodium alginate) undergo osmosis-driven solidification, facilitating the demolding of high-fidelity 3D structures formed by the printed threads of struts. These structures exhibit coreshell morphologies and high mechanical strength (∼175 MPa at 4% strain). Overall, this liquid-in-liquid fabrication approach, enabled by the integration of mChNF in the external phase, unlocks new possibilities for the design of versatile and multifunctional materials.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it