Progress in Bioinspired Dry and Wet Gradient Materials from Design Principles to Engineering Applications
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
Nature does nothing in vain. Through millions of years of revolution, living organisms have evolved hierarchical and anisotropic structures to maximize their survival in complex and dynamic environments. Many of these structures are intrinsically heterogeneous and often with functional gradient distributions. Understanding the convergent and divergent gradient designs in the natural material systems may lead to a new paradigm shift in the development of next-generation high-performance bio-/nano-materials and devices that are critically needed in energy, environmental remediation, and biomedical fields. Herein, we review the basic design principles and highlight some of the prominent examples of gradient biological materials/structures discovered over the past few decades. Interestingly, despite the anisotropic features in one direction (i.e., in terms of gradient compositions and properties), these natural structures retain certain levels of symmetry, including point symmetry, axial symmetry, mirror symmetry, and 3D symmetry. We further demonstrate the state-of-the-art fabrication techniques and procedures in making the biomimetic counterparts. Some prototypes showcase optimized properties surpassing those seen in the biological model systems. Finally, we summarize the latest applications of these synthetic functional gradient materials and structures in robotics, biomedical, energy, and environmental fields, along with their future perspectives. This review may stimulate scientists, engineers, and inventors to explore this emerging and disruptive research methodology and endeavors.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it