(4bm) Designing Structures and Functions of Soft Materials By Tuning Interactions

Design of building blocks with specific interactions is a key factor to achieve programmable self-assembly. For soft materials systems, these specific interactions can be tuned continuously, providing us with a combinatorially large design space from which we can search for novel materials. The key technical gap is to find ways to search through the design space of experimentally realizable materials to identify the optimal interactions for a material to have a given property. During my PhD and postdoc, I have worked on two different types of systems for materials-property design, where I designed the interactions of building blocks. The first is colloidal particles with either different shapes or interactions, and the second is magnetic handshake materials [4], a newly invented materials platform that encodes specific interactions in printed dipole patterns.

For colloidal systems, I designed targeted density driven solid--solid phase transitions by finding the best shape of hard colloidal particles [3] with “Digital Alchemy”, a statistical mechanics inspired method. In addition, I am currently working on inverse design of the best nucleation seed for crystallization for attractive colloidal particles. Whereas classically, these seeds are designed with classical nucleation theory, we are using JAX MD (a newly developed molecular dynamics engine with auto-differentiation) to explore whether entropy can modify these seeds For magnetic handshake materials, I introduced a scale-free design rule to efficiently generate dipole patterns that encode distinct interactions for heterogeneous self-assembly in both simulation and experiments [1]. Choice of dipole patterns together with building block geometry also regulates the persistence length of self-assembled magnetic polymers, confirmed by experimental collaborators [2].

My experience with these different soft materials systems enables me to quickly come up with minimal models to describe any new type of interactions from both analytical and numerical perspectives. I aim to lead a research group to inverse design soft materials functions more robustly, by combining the theoretical frameworks based on statistical mechanics, computational tools such as molecular dynamics simulations, and close collaborations with experimental groups.

Teaching Interests:

I am interested in teaching a broad range of core engineering courses such as thermodynamics and statistical mechanics at both undergraduate and graduate level. I believe that given advances in computation, simulation will become increasingly more important for advances in engineering, and as such I am excited about developing courses that bring this modern perspective. With my experience in soft matter and molecular dynamics simulations, I look forward to designing and teaching topical courses on soft matter, self-assembly, numerical methods and scientific computing. Previously, I have taught discussion sessions of graduate level Physical Mathematics online, introductory physics labs and helped adding computational elements to the course. I have also mentored several undergraduate students during my PhD and postdoc and taken a month-long seminar on Preparing Future Faculty offered by University of Michigan that had a big component on teaching philosophy. In addition, I also have experience in mentoring high school students preparing for various physics competitions.

Education & Training:

since 2018: Postdoctoral fellow, School of Engineering and Applied Sciences, Harvard University, Cambridge, MA; advisor: Michael P. Brenner

2012-2018: PhD in Physics, University of Michigan, Ann Arbor, MI; advisor: Sharon C. Glotzer and Greg van Anders

2008-2012: Bachelor of Arts in Physics and Mathematics, Beloit College, Beloit, WI

Selected Honors & Awards:

Soft Matter for All Symposium Speaker, Princeton University/University of Delaware, 2020

Frank Sevcik Award, Department of Physics, University of Michigan, 2018

Rackham Predoctoral Fellowship, University of Michigan, 2017

Graduate Student Speaker Award Winner, APS Group of Statistical and Nonlinear Physics, 2017

Selected Publications:

[1] Chrisy Xiyu Du, Hanyu Alice Zhang, Tanner Pearson, Jakin Ng, Paul L. McEuen, Itai Cohen, Michael P. Brenner, “Programming Interactions in Magnetic Handshake Materials”, (in prep)

[2] Hanyu Alice Zhang, Chrisy Xiyu Du, Ran Niu, Michael P. Brenner, Paul L. McEuen, Itai Cohen, “Designing the Persistence Length of Digital Magnetic Polymers”, (in prep)

[3] Chrisy Xiyu Du, Greg van Anders, Julia Dshemuchadse, Paul M. Dodd, Sharon C. Glotzer, “Inverse Design of Compression-Induced Solid—Solid Transitions in Colloids” (2020). Molecular Simulation 46 (14), 1037-1044.

[4] Ran Niu, Chrisy Xiyu Du, Edward Esposito, Jakin Ng, Michael P. Brenner, Paul L. McEuen, Itai Cohen, “Magnetic Handshake Materials as a Scale-Invariant Platform for Programmed Self-Assembly” (2019). Proc. Natl. Acad. Sci. USA 116 (49), 24402-24407.

[5] Chrisy Xiyu Du, Greg van Anders, Richmond S. Newman, Sharon C. Glotzer, “Shape-Driven Solid—Solid Transitions in Colloids” (2017). Proc. Natl. Acad. Sci. USA 114 (20), E3892-E3899.

Successful Research Proposals:

I have contributed to successfully funded proposals during my PhD and postdoc, such as compute time proposals from XSEDE and INCITE, and grant proposals from NSF and Sloan Foundation.

Service:

I co-chaired an APS March Meeting 2021 focus session on “Programmable Self-Assembly: Particle, Interaction and Pathway Design”. I was the co-chair of the 2019 Soft Condensed Matter Gordon Research Seminar, where I helped inviting speakers and panelists, as well as fundraising. I co-organized the 2019 APS Group (now Division) of Soft Matter short course on “Structures and Order in Soft Matter Physics” at the APS March Meeting, which had more than 70 attendees. Currently I am also serving on the APS Division of Soft Matter Membership Committee.