Solid-Solid Phase Transitions in Colloidal Matter

Phase transitions are ubiquitous in nature, and observed throughout everyday life from the melting of ice to the magnetization of iron. In particular, solid–solid phase transitions are important in many areas such as metallurgy, geosciences, and the design of reconfigurable materials. Following the recent initiative of using nano building blocks to design next generation materials, we answer fundamental questions about solid–solid phase transitions in colloidal matter and guide the design of ma- terials that can change phase. Using the “Digital Alchemy” framework, we extend thermodynamic ensembles to include particle shape as a thermodynamic variable. This framework enables us to study the effect of altering particle shape in solid–solid phase transitions. We first study the thermodynamic order of two different solid–solid phase tran- sitions (face-centered cubic (FCC)↔body-centered cubic (BCC) and BCC↔simple cubic (SC)) in hard-particle systems upon an instantaneous change in particle shape. By calculating the Landau free energy, we are able to determine the thermody- namic order of these two phase transitions. We find FCC↔BCC is first order while BCC↔SC is second order. This work is followed up by a more detailed investigation of the FCC↔BCC transition to explore whether it can be second order. We next study the design of pressure-induced solid–solid phase transitions. Here, we incorporate varying particle shape as a part of the Monte Carlo process to find the optimal shape for a given phase transition. We successfully designed pressure driven FCC→BCC and BCC→SC transitions using three different particle shape constraints. We also study the kinetic transition pathway between solid phases. Our results show that there are similarities of the pathways of an entropic system and an atom- istic system. This demonstrates that we can use entropic systems as a toy model to understand better how the transformations happen in an atomistic system. Results from this dissertation give insight into the fundamental nature of the most common, yet poorly understood phase transitions in nature, and provide new minimal models for understanding solid–solid transitions in atomic systems. Our findings also provide guidance for the next generation of materials design.PHDPhysicsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/146134/1/xiyudu_1.pd

Using an Open Source Python Toolbox (Signac) to Manage High Dimensional Research Data

Many research fields have entered the age of Big Data. For some researchers, big data means computationally generating large datasets with high dimensional parameter sweeps; for others, big data means generating terabytes of experimental data with many different types of metadata based on experimental conditions. Recording and storing these data in an organized way for future analysis can be challenging, as many ad hoc solutions might help the exact current situation but hurt one's progress later on. Having battled these challenges, I want to share my experience working with an open-source data management system based on Python called Signac. Signac was first developed in the Glotzer Group at the University of Michigan, where I was a graduate student, to help manage different kinds of molecular dynamics simulations, but later extended to support many different kinds of data. In this talk, I want to briefly talk about the design philosophies of Signac and give a quick demonstration of how one could use Signac to help with their research based on my personal experiences