Spontaneous hierarchical surface engineering of minerals through coupled dissolution‐precipitation chemistry
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
Abstract Peculiar hierarchical microstructures in creatures inspire modern material design with distinct functionalities. Creatures can effortlessly construct sophisticated yet long‐range ordered microstructure across bio‐membrane through ion secretion and precipitation. However, microstructure biomimicry in current technology generally requires elaborate, point‐by‐point fabrication. Herein, a spontaneous yet controllable strategy is developed to achieve surface microstructure engineering through a natural surface phenomenon similar to ion secretion‐precipitation, that is, coupled dissolution‐precipitation. A series of hierarchical microstructures on mineral surfaces in fluids with tunable morphology, orientation, dimension, and spatial distribution are achieved by simply controlling initial dissolution and fluid chemistry. In seawater, long‐range ordered film of vertically aligned brucite flakes forms through interfacial dissolution, nucleation, and confinement‐induced orientation of flakes with vertically grown {110} plane, on the edge of which, fusiform aragonite epitaxially precipitates. With negligible initial surface dissolution, prismatic aragonite epitaxially grows on a calcite polyhedron‐packed surface. By tuning fluid chemistry, closely packed calcite polyhedron and loosely packed calcite micro‐pillars are engineered through rapid and retarded precipitation, respectively. Surprisingly, the spontaneously grown microstructures resemble those deliberately created by human or found in nature, and tremendously modulate surface functionality. These findings open new possibilities for facile and customizable engineering of microstructural surfaces, hierarchical heterostructures, and biomimetic 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 | 0.000 | 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 it