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Quantitative Prediction of the Phase Diagram of DNA-Functionalized Nanosized Colloids

Bianca M. Mladek, Julia Fornleitner, Francisco J. Martinez-Veracoechea, Alexandre Dawid, and Daan Frenkel
Phys. Rev. Lett. 108, 268301 – Published 25 June 2012
Physics logo See Viewpoint: DNA Hairs Provide Potential for Molecular Self-Assembly

Abstract

We present a coarse-grained model of DNA-functionalized colloids that is computationally tractable. Importantly, the model parameters are solely based on experimental data. Using this highly simplified model, we can predict the phase behavior of DNA-functionalized nanocolloids without assuming pairwise additivity of the intercolloidal interactions. Our simulations show that, for nanocolloids, the assumption of pairwise additivity leads to substantial errors in the estimate of the free energy of the crystal phase. We compare our results with available experimental data and find that the simulations predict the correct structure of the solid phase and yield a very good estimate of the melting temperature. Current experimental estimates for the contour length and persistence length of single-stranded (ss) DNA sequences are subject to relatively large uncertainties. Using the best available estimates, we obtain predictions for the crystal lattice constants that are off by a few percent: this indicates that more accurate experimental data on ssDNA are needed to exploit the full power of our coarse-grained approach.

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  • Received 19 March 2012

DOI:https://doi.org/10.1103/PhysRevLett.108.268301

© 2012 American Physical Society

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DNA Hairs Provide Potential for Molecular Self-Assembly

Published 25 June 2012

A new model for DNA-covered nanoparticles predicts their stable crystal structures and may one day help in finding the optimal building blocks for self-assembling materials.

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Authors & Affiliations

Bianca M. Mladek1,2,*, Julia Fornleitner3, Francisco J. Martinez-Veracoechea1, Alexandre Dawid4, and Daan Frenkel1

  • 1Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW, United Kingdom
  • 2Department of Structural and Computational Biology, Max F. Perutz Laboratories GmbH, University of Vienna, 1030 Vienna, Austria
  • 3Institute for Complex Systems, Forschungszentrum Jülich, 52428 Jülich, Germany
  • 4Laboratoire Interdisciplinaire de Physique UMR 5588, Université Joseph Fourier Grenoble 1/CNRS, Grenoble, 38041, France

  • *bianca.mladek@univie.ac.at

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Issue

Vol. 108, Iss. 26 — 29 June 2012

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