(2bw) Improving the Understanding of Dynamics and Mechanical Response of Mixed Moduli Polymer Materials through Simulation

My research focuses on furthering our understanding of the dynamics and properties of soft material systems through novel simulation methods. The separation of timescales in many activated processes makes obtaining adequate sampling of phase space in simulations difficult to impossible through brute force alone. By using advanced sampling and free energy techniques it is possible to advance the timescales currently accessible by computer simulation and gain new insights into material dynamic properties.

In keeping with this theme, as a faculty member I seek to extend our understanding and ability to control the dynamics and pathways of complex polymer materials. In self-assembled polymeric materials the assembly process relies on collective motion of individual polymer chains. I seek to develop new methods based upon recent advances in machine learning and data analysis techniques to identify and characterize these collective processes. Identification of these collective modes will enable the design of new material design pathways and control of these materials. Furthermore the computational tools developed will additionally apply beyond just polymeric systems and can be used to assist in designing kinetic pathways in other soft materials such as proteins and colloidal assembled structures.

During my time as a postdoc at the University of Chicago my work has focused on predicting polymer properties through machine learning and finding improved methods for simulation of thermoplastic elastomers. Using a model diblock copolymer, with a variable sequence block, I created a dataset containing information about the chi parameter, sequence, and lamellar period. Using a combination of dimensionality reduction techniques and machine learning methods this data set was used to show that ML models can be applied to such a dense polymer system to predict properties, as well as provide insights into heuristics to describe the underlying behavior.

My studies of thermoplastic elastomers focused on two distinct issues with their simulation. First, because of their bridged nature, these structures take a tremendously long time to relax. Second, these materials overall mechanical response depends on two domains each with a very different Young’s modulus. To overcome the first issue I developed advance sampling methods to bring the system to true equilibrium. In order to better quantify the mechanical response I studied the behavior of the bridging rubbery domain with different connectivities. To obtain computational resources necessary for this work I co-wrote and obtained an ASCR Leadership Computing Challenge grant for usage with the upcoming Polaris cluster located at Argonne National Lab.

As a graduate student at the University of Minnesota my work focused on the dynamic properties of micellar surfactant systems. Using coarse grained simulation models I determined the properties of a model surfactant. In order to do so, I developed methods to determine the micelle free energy as a function of aggregation number, as well as insertion and expulsion rates of surfactant to and from micelles. These parameters were used in a numerical model to determine long time behaviors beyond what could be reached in particle based simulation, and led to confirmation of several regimes of surfactant behavior.

Teaching Interests

As a faculty member I believe I have a duty to teach and assist in education of the next generation of engineers. My primary teaching interests are thermodynamics, mass and energy transfer, statistical mechanics, and introductory mass and energy balance courses. While the first three topics my interest stems from their relation to my research, my interest in teaching the last topic stems from a fervent desire to ensure that young chemical engineers are given an understanding the most fundamental tools they will use throughout their careers. I am prepared to teach any chemical engineering course at the undergraduate level. At the graduate level I am qualified to teach courses concerning thermodynamics, statistical mechanics, transport, polymer physics, and colloid and interface science. In addition to direct teaching I am a strong believer in mentoring at the undergraduate, graduate, and post graduate level. During my postdoc at the University Chicago I led a regular discussion session and lecture focusing on polymer physics for new graduates students in the group, as well as serving as co-instructor for a course in classical molecular dynamics simulation.