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A method to estimate the size of single-chain nanoparticles under severe crowding conditions
Single-chain nanoparticles (SCNPs) result from the folding of isolated polymer chains via intramolecular interactions. Currently, there is no theory able to rationalize the astonishing conformational behaviour of SCNPs under severe crowding conditions (e.g., highly concentrated solutions, all-polyme...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society of Chemistry
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8978863/ https://www.ncbi.nlm.nih.gov/pubmed/35425196 http://dx.doi.org/10.1039/d1ra09088g |
Sumario: | Single-chain nanoparticles (SCNPs) result from the folding of isolated polymer chains via intramolecular interactions. Currently, there is no theory able to rationalize the astonishing conformational behaviour of SCNPs under severe crowding conditions (e.g., highly concentrated solutions, all-polymer nanocomposites) and, specifically, the significant size reduction observed in highly crowded solutions of covalent-bonded SCNPs and all-polymer nanocomposites containing SCNPs. Herein, we propose a valuable method to estimate the size of SCNPs under crowding. The method – which is based on combining MD simulations results with scaling concepts – is also useful for ring polymers and nanostructured Janus-shaped SCNPs. |
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