Data-knowledge dual-driven intelligent framework for full-chain, experiment-efficient synthesis of 2D dendrites
Exemplified by the chemical vapor deposition growth of two-dimensional dendrites, which has potential applications in catalysis and presents a parameter-intensive, data-scarce and reaction process-complex model problem, we devise a machine intelligence-empowered framework for the full chain support of material synthesis, encompassing rapid process optimization, accurate customized synthesis, and comprehensive mechanism deciphering.First, active learning is integrated into the experimental workflow, identifying an optimal recipe for the growth of highly-branched, electrocatalytically-active ReSe2 dendrites through 60 experiments (4 iterations), which account for less than 1.3% of the numer...
| Authors | Wenqiang Huang, Xuhang Gu, Susu Fang et al. |
|---|---|
| Primary category | cond-mat.mtrl-sci |
| Published | 17 March 2026 |
| Last updated at source | 17 August 2026 |
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