Computational Nanoscience

Using the power of computer simulation
to self-assemble nanoparticles via entropy.

I am a graduate student working for Sharon C. Glotzer in the Glotzer Group at the University of Michigan.

I study the self-assembly of nanoparticle systems via entropy.

Skills

Computational nanoscience requires the synthesis of skills in many disciplines from statistical mechanics to computer science:

  • C++/Cuda/Python
  • Nanoscale self-assembly
  • Accelerate computation via parallel computing
  • Lead developer of Freud analysis suite
  • Statistical mechanics
  • Teaching undergraduate-level courses

Research

The focus of my research is how we can exploit entropy to create ordered phases and how to control these emergent entropic forces to create “entropic" bonds. But, as the great Isaac Newton once said, "If I have seen further than others, it is by standing upon the shoulders of giants." Below you will find some videos featuring the Glotzer Group and the research we do. You can find links to my specific work in the Publications section.

Sharon Glotzer describing adaptive materials

The materials of the future will need to adapt to our needs and our environment on demand, not unlike the T-1000 from Terminator 2: Judgment Day.

Sharon Glotzer's TEDx talk at The University of Michigan

Glotzer Group & Entropy featured on Sixty Symbols

The wonderful folks over at Sixty Symbols featured entropic self-assembly research done by the Glotzer Group (in particular Michael Engel). While most people think of entropy as disorder, we can in fact use entropy to form and control ordered structures.

Colloidal muscles

"Nanobots" of the future will need motors and muscles to move. This work investigates the self-assembly of colloidal muscles. This is a collaboration between the Solomon and Glotzer Groups at the University of Michigan.

Publications

Shape Allophiles Improve Entropic Assembly

Link to version on arXiv

Featured on cover of Soft Matter 7 October 2015

We investigate a class of “shape allophiles” that fit together like puzzle pieces as a method to access and stabilize desired structures by controlling directional entropic forces. Squares are cut into rectangular halves, which are shaped in an allophilic manner with the goal of re-assembling the squares while self-assembling the square lattice. We examine the assembly characteristics of this system via the potential of mean force and torque, and the fraction of particles that entropically bind. We generalize our findings and apply them to self-assemble triangles into a square lattice via allophilic shaping. Through these studies we show how shape allophiles can be useful for assembling and stabilizing desired phases with appropriate allophilic design.