Biofabrication with microbial cellulose: from bioadaptive designs to living materials
Bibliographic record
Abstract
Nanocellulose is not only a renewable material but also brings functions that are opening new technological opportunities. Here we discuss a special subset of this material, in its fibrillated form, which is produced by aerobic microorganisms, namely, bacterial nanocellulose (BNC). BNC offers distinct advantages over plant-derived counterparts, including high purity and high degree of polymerization as well as crystallinity, strength, and water-holding capacity, among others. More remarkably, beyond classical fermentative protocols, it is possible to grow BNC on non-planar interfaces, opening new possibilities in the assembly of advanced bottom-up structures. In this review, we discuss the recent advances in the area of BNC-based biofabrication of three-dimensional (3D) designs by following solid- and soft-material templating. These methods are shown as suitable platforms to achieve bioadaptive constructs comprising highly interlocked biofilms that can be tailored with precise control over nanoscale morphological features. BNC-based biofabrication opens applications that are not possible by using traditional manufacturing routes, including direct ink writing of hydrogels. This review emphasizes the critical contributions of microbiology, colloid and surface science, as well as additive manufacturing in achieving bioadaptive designs from living matter. The future impact of BNC biofabrication is expected to take advantage of material and energy integration, residue utilization, circularity and social latitudes. Leveraging existing infrastructure, the scaleup of biofabrication routes will contribute to a new generation of advanced materials rooted in exciting synergies that combine biology, chemistry, engineering and material sciences.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.006 |
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".