(376aj) Applications of Freud for Nanoscale Simulation Analysis

Authors: 
Ramasubramani, V., University of Michigan
Dice, B., University of Michigan
Harper, E. S., University of Michigan
Spellings, M., University of Michigan
Anderson, J. A., University of Michigan
Glotzer, S. C., University of Michigan
Although particle simulations span a wide range of length and time scales, most existing standardized analysis tools are strongly focused on biomolecular simulations, and few tools exist for colloidal and coarse-grained simulations. This talk will showcase freud, a Python package that aids in calculating quantities that are frequently of interest in simulations on colloidal length scales. Perhaps the most prominent use-case we will highlight is the identification of phase transitions, including 2-dimensional melting, shape-driven solid-solid phase transitions, and depletion-driven crystallization. We will also demonstrate that freud has been used to study such diverse problems as the inverse design of isotropic pair potentials and the engineering of strain fields in colloidal crystals. A particular emphasis will be the ease of building new analyses using the core infrastructure of freud. The poster’s final emphasis will be on how freud can be used in cutting-edge applications such as the computation of descriptors for machine learning algorithms or on-the-fly simulation analysis to study complex phenomena as they occur.