Deconstruction and Reassembly of Renewable Polymers and Biocolloids into Next Generation Structured Materials
Bibliographic record
Abstract
This review considers the most recent developments in supramolecular and supraparticle structures obtained from natural, renewable biopolymers as well as their disassembly and reassembly into engineered materials. We introduce the main interactions that control bottom-up synthesis and top-down design at different length scales, highlighting the promise of natural biopolymers and associated building blocks. The latter have become main actors in the recent surge of the scientific and patent literature related to the subject. Such developments make prominent use of multicomponent and hierarchical polymeric assemblies and structures that contain polysaccharides (cellulose, chitin, and others), polyphenols (lignins, tannins), and proteins (soy, whey, silk, and other proteins). We offer a comprehensive discussion about the interactions that exist in their native architectures (including multicomponent and composite forms), the chemical modification of polysaccharides and their deconstruction into high axial aspect nanofibers and nanorods. We reflect on the availability and suitability of the latter types of building blocks to enable superstructures and colloidal associations. As far as processing, we describe the most relevant transitions, from the solution to the gel state and the routes that can be used to arrive to consolidated materials with prescribed properties. We highlight the implementation of supramolecular and superstructures in different technological fields that exploit the synergies exhibited by renewable polymers and biocolloids integrated in structured 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".