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Diversifying Composition Leads to Hierarchical Composites with Design Flexibility and Structural Fidelity.
Ma, Le; Huang, Hejin; Vargo, Emma; Huang, Jingyu; Anderson, Christopher L; Chen, Tiffany; Kuzmenko, Ivan; Ilavsky, Jan; Wang, Cheng; Liu, Yi; Ercius, Peter; Alexander-Katz, Alfredo; Xu, Ting.
Afiliação
  • Ma L; Department of Materials Science and Engineering, University of California, Berkeley, California 94720, United States.
  • Huang H; Materials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States.
  • Vargo E; Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States.
  • Huang J; Department of Materials Science and Engineering, University of California, Berkeley, California 94720, United States.
  • Anderson CL; Materials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States.
  • Chen T; Department of Materials Science and Engineering, University of California, Berkeley, California 94720, United States.
  • Kuzmenko I; Department of Chemistry, University of California, Berkeley, California 94720, United States.
  • Ilavsky J; The Molecular Foundry, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States.
  • Wang C; Materials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States.
  • Liu Y; Department of Chemistry, University of California, Berkeley, California 94720, United States.
  • Ercius P; Advanced Photon Source, Argonne National Laboratory, Argonne, Illinois 60439, United States.
  • Alexander-Katz A; Advanced Photon Source, Argonne National Laboratory, Argonne, Illinois 60439, United States.
  • Xu T; Advanced Light Source, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States.
ACS Nano ; 15(9): 14095-14104, 2021 Sep 28.
Article em En | MEDLINE | ID: mdl-34324313
ABSTRACT
Although significant progress has been made in the self-assembly of nanostructures, present successes heavily rely on precision in building block design, composition, and pair interactions. These requirements fundamentally limit our ability to synthesize macroscopic materials where the likelihood of impurity inclusion escalates and, more importantly, to access molecular-to-nanoscopic-to-microscopic-to-macroscopic hierarchies, since the types and compositions of building blocks vary at each stage. Inspired by biological blends and high-entropy alloys, we hypothesize that diversifying the blend's composition can overcome these limitations. Increasing the number of components increases mixing entropy, leading to the dispersion of different components and, as a result, enhances interphase miscibility, weakens the dependence on specific pair interactions, and enables long-range cooperativity. This hypothesis is validated in complex blends containing small molecules, block copolymer-based supramolecules, and nanoparticles/colloidal particles. Hierarchically structured composites can be obtained with formulation flexibility in the filler selection and blend composition. It is worth noting that, by adding small molecules, we can solve the size constraint that plagues traditional block copolymer/nanoparticle blends. Detailed characterization and simulation further confirm that each component is distributed to locally mediate unfavorable interactions, cooperatively mitigate composition fluctuations, and retain structural fidelity. Furthermore, the blends have sufficient mobility to access tunable microstructures without compromising the order of the nanostructure. Besides establishing a kinetically viable pathway to release current constraints in the composite design and to navigate uncertainties during structure formation over multiple length scales, the present study demonstrates that entropy-driven behaviors can be realized in systems beyond high-entropy alloys despite inherent differences between metal alloys and organic/inorganic hybrids.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2021 Tipo de documento: Article