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Programmable Nanoparticle Ensembles via High-Throughput Directed Self-Assembly
Langmuir (2013)
  • Qiu Dai, IBM Almaden Research Center
  • Yingyu Chen, San Jose State University
  • Chi-Chun Liu Liu, IBM Almaden Research Center
  • Charles T. Rettner, IBM Almaden Research Center
  • Bryan Holmdahl, San Jose State University
  • Stacy H. Gleixner, San Jose State University
  • Richard Chung, San Jose State University
  • Jed W. Pitera, IBM Almaden Research Center
  • Joy Cheng, IBM Almaden Research Center
  • Alshakim Nelson, IBM Almaden Research Center
Abstract
We present a simple and facile strategy for the directed self-assembly of nanoparticles into complex geometries using a minimal set of post guiding features patterned on a substrate. This understanding is based on extensive studies of nanoparticle self-assembly into linear, dense-packed, circular, and star-shaped ensembles when coated onto patterned substrates of predefined post arrays. We determined the conditions under which nanoparticles assemble and “connect” two adjacent post features, thereby forming the desired shapes. We demonstrate that with rational design of the post patterns to enforce the required pairwise interactions with posts, we can create arbitrary arrangements of nanoparticles—for example, to write “IBM” in a deterministic manner. This demonstration of programmable, high-throughput directed self-assembly of nanoparticles shows an alternative route to generate functional nanoparticle assemblies.
Publication Date
2013
DOI
10.1021/la4000457
Publisher Statement
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Citation Information
Qiu Dai, Yingyu Chen, Chi-Chun Liu Liu, Charles T. Rettner, et al.. "Programmable Nanoparticle Ensembles via High-Throughput Directed Self-Assembly" Langmuir Vol. 29 Iss. 11 (2013) p. 3567 - 3574
Available at: http://works.bepress.com/stacy_gleixner/32/