Research

Computational Research

Oxides for Water-Splitting Technologies and Beyond
Galli Group, University of Chicago (ongoing)

Using first-principles methods to elucidate the relationship of the bulk, surface, and interface in water splitting applications, in parallel with experiments.

Artistic rendition of electrochromism in a perovskite

First-Principles Calculations of Transition Metal Oxides
Van de Walle Computational Group, UC Santa Barbara (2013-2018)

Density functional theory (DFT) offers a powerful way to predict and understand material properties from a first principles basis. The project uses DFT to characterize and understand the electronic, optical, and transport properties of perovskites for applications in energy efficiency applications.
(Image rendered in Blender)

SEM image of solar cell cross-section

Mechanical Characterization of Solar Cells
Fraunhofer CSP, with Dr. Stephan Schoenfelder and Felix Kaule (Summer 2012)

Metallization and firing of solar cells causes large bending moments that lead to premature fracture due to differing coefficients of thermal expansion in the silicon and metallization layers. The firing process results in a solar cell with a complex multilayer microstructure that not well mechanically understood. This project focused on analytical, computational, and experimental modeling of the solar cell to understand the elastic, plastic, and brittle mechanics of the cell, and provided the theoretical basis for understanding the composite behavior.

(SEM image taken by M. Oswald at Fraunhofer CSP)

Schematic of Radial Magnetic Bearing

Design and Optimization of Radial Magnetic Bearings
Siemens AG, with Dr. Matthias Lang (Summer 2011)

Magnetic bearings are used in various industrial applications, such as in power generation, gas turbines, and reactors. Because magnetic bearings involve a levitating rotor, it avoids friction, usage of chemicals, and fire hazards. The objective of this project was to design a series of magnetic bearings of various sizes and force ratings while minimizing losses from eddy currents for future manufacturing purposes. A variety of optimization algorithms, such as Nelder-Mead and Genetic Algorithm, were used in generating final design parameters.

(Image from Schweitzer, Gerhard and Maslen, Eric H., ed.
Magnetic Bearings: Theory, Design, and Application to Rotating Machinery. p. 2 Springer, 2009.)

Experimental Research

A sample during tensile testing

Structural Health Monitoring in Carbon Nanotube Reinforced Composites
MIT NECST Lab, with Prof. Brian L. Wardle and Dr. Sunny S. Wicks (Fall 2011- Spring 2013)

Carbon nanotubes (CNTs) have remarkable electronic and mechanical properties that have yet to be fully realized on the macroscopic scale. This project aimed to understand how various architectures and growth processes of CNTs influenced the structural health monitoring ability of the composite via changes in electrical resistance and the resistance to fracture via tensile testing. The work was done in collaboration with Metis Design Corporation. Thesis report here.