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A statistical learning protocol to resolve the morphological complexity of two-dimensional macromolecules
Unraveling the morphological complexity of two-dimensional macromolecules allows researchers to design and fabricate high-performance, multifunctional materials. Here, we present a protocol based on statistical learning to resolve morphological complexity utilizing geometrical, topological, and phys...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Elsevier
2022
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9797609/ https://www.ncbi.nlm.nih.gov/pubmed/36223266 http://dx.doi.org/10.1016/j.xpro.2022.101767 |