(4cp) Computational Studies On Self- and Directed-Assembly of Soft Matter Nano Building Blocks

Fabricating nanostructures that exhibit a well-defined ordering and are adaptive to environment has been highly desirable for a huge array of novel applications ranging from photonics, bio-sensing to drug delivery. Using computer simulation as a design tool, I have explored numerous approaches to engineering such structures from bottom up perspectives.

In my PhD studies, I have demonstrated that various nanostructures with one-, two- and three- dimensional periodicity can be obtained from the self-assembly of soft matter building blocks such as polymer-tethered nanoparticles and colloidal particles[1,2]. Remarkably, the interplay between the energetic and entropic interactions between the building blocks can lead to unexpectedly higher order structures that are uniform in geometry even when the building blocks are highly polydisperse[2]. In many cases, the assembled structures such as helical ribbons and bilayer sheets are shown to reversibly reconfigure upon toggling building block interactions and/or morphing their geometry[3,4]. I have also proposed unconventional, yet efficient, pathways along which target assembled structures are obtained by shifting the building block geometry[5]. Alternatively, the formation of nano- and micro-structures can be induced either by applying an external field on a system of Janus particles[6], or by taking advantage of the inherent instability of nanometer-thick films on solid substrates[7]. Specifically, as a postdoctoral researcher at ORNL I have been investigating the interplay between spinodal instability and thermal nucleation in thin liquid films wetting solid substrates. Using large-scale Molecular Dynamics simulations, I have focused on understanding the mechanisms by which metallic and liquid crystal films first rupture, and how instability develops in the presence of thermal fluctuations. The results will provide useful information at the atomistic level, which is inaccessible with experiment and continuum models.

Throughout my study, I have also implemented and re-evaluated new computational methods and models to exploit the potential performance of new computer hardware such as GPUs and coprocessors[8,9]. Among my contributions to the open-source community, I have involved in implementing the rigid body integrators for LAMMPS and HOOMD-Blue[8], and various GPU-accelerated force fields for LAMMPS. These GPU-accelerated force fields allow for simulations performed at a much larger scale and at a much more affordable expense than before. Overall, my research serves not only as a framework for designing functional nanostructured materials via bottom-up approaches, but also to connect and inspire further theoretical and experimental investigations.

References

1. T. D. Nguyen, Z. Zhang, S. C. Glotzer, J. Chem. Phys., 129, 249903, 2008.

2. Y. Xia, T. D. Nguyen, M. Yang, B. Lee, P. Podsiadlo, A. Santos, Z. Tang, S. C. Glotzer, N. A. Kotov, Nature Nano, 6, 580-587, 2011.

3. T. D. Nguyen, S. C. Glotzer, Small, 5, 2092-2096, 2009.

4. T. D. Nguyen and S. C. Glotzer, ACS Nano, 4, 2585-2595, 2010.

5. T. D. Nguyen, E. Jankowski and S. C. Glotzer, ACS Nano, 5, 8892-8903, 2011.

6. S. Hwang, T. D. Nguyen, S. Bhaskar, J. Yoon, D. Chickering, H. Bernstein, S. C. Glotzer, J. Lahann, In Preparation, 2013.

7. T. D. Nguyen, M. Fuentes-Cabrera, J. D. Fowlkes, J. A. Diez, A. G. Gonzalez, L. Kondic, P. D. Rack, Langmuir, 28, 13960-13967, 2012.

8. T. D. Nguyen, C. L. Phillips, J. A. Anderson, S. C. Glotzer, Comput. Phys. Comm., 182, 2307-2313, 2011.

9. T. D. Nguyen, J.-M. Y. Carrillo, A. V. Dobrynin, W. M. Brown, J. Chem. Theory Comput., 9, 73-83, 2013.