(2bz) Colloidal Soft Materials Driven By Electromagnetic Fields

Colloidal particles are powerful building blocks for functional soft materials used in optoelectronic devices, consumer products, and biomedical applications. Colloids responsive to electromagnetic (EM) fields are especially useful because EM fields offer experimentally facile strategies for controlling interparticle interactions and directing motion. Most promising is the ability to vary EM fields over an enormous range of time scales to excite particle, ion, and electron motion and tune a variety of material properties on-the-fly. Strategic engineering of EM-driven colloidal materials requires a level of fundamental understanding that is difficult to develop through experiments alone. Unfortunately, EM phenomena are notoriously hard to incorporate into computational and theoretical models because they involve long-ranged, anisotropic, and many-bodied interactions. Throughout my graduate and postdoctoral studies, I have built a suite of rapid numerical tools to simulate colloids in time-varying EM fields, enabling simulations of hundreds of thousands of particles that accurately model the dynamics in experiments. My proposed research aims to leverage these computational tools to investigate how time-varying electromagnetic fields tune colloidal properties, allowing us to design responsive, functional soft materials.

Enhanced Magnetophoresis through Porous Media in Time-Varying Fields. Paramagnetic colloids are promising to transport molecular cargo for targeted therapeutic applications. The colloids can be rapidly localized to specific sites using magnetic field gradients that guide particles magnetophoretically. Target sites (e.g. tumor cells) are often surrounded by dense, porous tissue through which the particles must navigate. However, large dipole moments induced in the paramagnetic particles cause them to aggregate, hindering the particles' mobility, clogging pores, or preventing penetration into the tissue entirely. Experiments show that time-varying fields can suppress particle aggregation during magnetophoresis and greatly enhance particle flux through porous media. Beyond these promising proof-of-concept experiments, we have no theoretical or computational models to predict this transport process. My group will build computational models to investigate magnetophoresis of paramagnetic colloids through porous media in time-varying fields. This will enable rapid development of efficient magnetophoretic delivery systems for targeted therapies.

Inverse Design of Self-Assembled Plasmonic Materials. Metal and semiconductor nanoparticles exhibit localized surface plasmon resonance and interact strongly with resonant frequencies of light, making them useful in optoelectronic, catalytic, and biomedical technologies. The optical properties can be tailored through the nanoparticle structure, allowing for reconfigurable materials with multiple functionalities through self-assembly. However, a major challenge is the enormous number of physical parameters and structures to screen. Forward strategies are commonly adopted where parameter sweeps are used to screen materials with desirable properties through trial and error. To make materials discovery more systematic and amenable to meeting specified design constraints, I propose to couple self-assembly simulations and optical calculations with methods of numerical optimization to formulate plasmonic design as an inverse problem. We specify a target plasmonic response and use optimization routines to find tunable parameters that yield materials with the desired behavior. This strategy builds on inverse methods effective for target structures but allows for explicit control over material properties.

Responsive Materials from Field-Driven Colloids in Electrolytes. Colloids dispersed in electrolytes translate, rotate, and produce flows when exposed to an electric field, presenting design opportunities for energy storage, microfluidic, and electrorheological devices. These ``induced-charge electrokinetic'' (ICEK) phenomena originate from the coupling between polarization charges induced within a particle and mobile ions in the surrounding double layer. A wide variety of ICEK systems have been formulated for electroosmotic pumping, mixing, and self-propulsion in microfluidic devices, but connecting these transport mechanisms to material properties has historically been challenging due to the theoretical and computational complexity of multiple length scales and many-bodied effects on ion and particle dynamics. My group will address this by developing new coarse-grained simulation methods to study the coupled ICEK dynamics and material properties of colloid-electrolyte mixtures, enabling strategies for responsive materials with multifunctional ICEK responses.

Teaching Interests

Not all parts of a faculty position are enjoyable, but teaching and mentoring are aspects that I am excited about. I have sought out many extra opportunities to teach and mentor younger scientists, and each experience is a valued part of my academic career. I have been a teaching assistant (TA) for three courses at undergraduate and graduate levels and have mentored five undergraduate researchers and one elementary school teacher in the lab. I have also extended my interest in education beyond the university level through my roles as Outreach Chair in the Materials Research, Science, and Education Center (MRSEC) at UT Austin and Lead Facilitator of STEM Club at Hart Elementary School. I have even been recognized for these endeavors through several awards, including the MIT School of Engineering Graduate Student Award for Extraordinary Teaching and Mentoring and the MIT Department of Chemical Engineering Outstanding Graduate Teaching Assistant Award. Though I am eager to learn more, I have drawn on these experiences to formulate a set of core principles that I value as an educator and mentor and hope to incorporate into my future classroom and lab.

In the classroom, I strive to create a positive, optimistic learning environment where students are as excited about science as I am. Crucial to this goal is prioritizing inclusivity, to ensure everyone feels welcome, safe, and valued, and mental and physical well-being. I aim for reasonable expectations and workloads while being accommodating and flexible to the needs of students with different academic backgrounds and learning speeds. For example, as a TA for graduate statistical mechanics, I helped create a variety of resources that students could engage on their own schedules, including extra lectures, write-ups, videos, practice problems, and Q&A forums. I also helped develop short quizzes and small-group exercises to provide feedback on student progress as well as promote self-efficacy, both of which facilitate learning. I am particularly excited about teaching thermodynamics and statistical mechanics, numerical methods, transport, and fluid mechanics, though I am equipped to teach any course in the core chemical engineering curriculum. I am also eager to develop elective courses delving further into applied mathematics as well as creating computational modules to augment existing courses -- for example, a molecular simulation module for thermodynamics courses or a module on numerical differential equations for fluid mechanics/transport courses. Finally, I am interested in creating alternative resources for students beyond lectures, textbooks, and notes, such as short videos and web applets on particularly tough topics.

The same principles I value in my classroom are also important for my future lab. It is incredibly important for me to cultivate an uplifting, optimistic lab culture where members are excited to solve challenging research problem. In my own research, as well as with those I mentor, I try to maintain a growth mindset, rather than fixed mindset, where both successful and ``unsuccessful'' endeavors offer useful new information to improve our work. This positive mindset is crucial for navigating the ups and downs of academic research and maintaining mental and physical well-being, which results in higher productivity overall.

I have worked together with prior mentees to set realistic short-terms and long-term goals that were flexible to exams, travel, etc. and will continue this dialogue with my future students. I am also committed to inclusivity, and my lab will promote the diversity of members’ identities as well as their research backgrounds and approaches. This will facilitate a collaborative environment where my group members feel safe and encouraged to work together. I have ample experience working with computational and experimental collaborators from a variety of different academic backgrounds, which has resulted in some of my best and favorite work. Collaborative efforts will be a central part of my lab, and I will guide my students on how to effectively work with other researchers. Two other important values in my lab are: ensuring that our work is as accessible as possible by developing open source code, organizing clear data sets for data sharing, and disseminating pedagogical videos and graphics as well as extending our work beyond the university level to actively engage in K-12 education outreach, an area I have much experience. Because my career would not be the same without the tremendous support I have received from many people, I take my duty of providing professional support to my students seriously. As I have done with prior mentees, I will aid in any way possible to secure funding, internships, fellowships, and jobs as well as practice writing, presentation, interview, and other important communication skills. Finally, underlying all these values is transparency, and I will ensure that all information and expectations of my lab are clearly communicated. Inspired by other labs, I will create a lab manual which documents lab procedures, expectations, and values, providing a valuable reference for current and prospective members. Creating the lab manual will be a collaborative effort with my group; it will be a living document that we continually revise as my group and our needs change.