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Title: Mechanical Response of DNA–Nanoparticle Crystals to Controlled Deformation

Journal Article · · ACS Central Science
 [1];  [1];  [2];  [3]
  1. Univ. of Chicago, IL (United States). Institute for Molecular Engineering
  2. Univ. of Wisconsin, Madison, WI (United States). Department of Chemical and Biological Engineering
  3. Univ. of Chicago, IL (United States). Institute for Molecular Engineering; Argonne National Lab. (ANL), Argonne, IL (United States). Materials Science Division

The self-assembly of DNA-conjugated nanoparticles represents a promising avenue toward the design of engineered hierarchical materials. By using DNA to encode nanoscale interactions, macroscale crystals can be formed with mechanical properties that can, at least in principle, be tuned. Here we present in silico evidence that the mechanical response of these assemblies can indeed be controlled, and that subtle modifications of the linking DNA sequences can change the Young’s modulus from 97 kPa to 2.1 MPa. We rely on a detailed molecular model to quantify the energetics of DNA–nanoparticle assembly and demonstrate that the mechanical response is governed by entropic, rather than enthalpic, contributions and that the response of the entire network can be estimated from the elastic properties of an individual nanoparticle. The results here provide a first step toward the mechanical characterization of DNA–nanoparticle assemblies, and suggest the possibility of mechanical metamaterials constructed using DNA.

Research Organization:
Argonne National Laboratory (ANL), Argonne, IL (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Basic Energy Sciences (BES); National Institute of Standards and Technology (NIST)
Grant/Contract Number:
AC02-06CH11357
OSTI ID:
1352578
Journal Information:
ACS Central Science, Vol. 2, Issue 9; ISSN 2374-7943
Publisher:
American Chemical Society (ACS)Copyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 13 works
Citation information provided by
Web of Science

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Cited By (4)

Ideal isotropic auxetic networks from random networks journal January 2019
1CPN: A coarse-grained multi-scale model of chromatin journal June 2019
Bridging functional nanocomposites to robust macroscale devices journal June 2019
Ideal isotropic auxetic networks from random networks preprint January 2019

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