(2fm) Programming Nanoparticles: Inverse Design for Next-Generation Materials

The drastic increase in our nanoparticle synthesis capabilities over the past decade has enabled the creation of particles with an incredible degree of tailorability. From metal nanocrystals to liposomes, particles with almost any arbitrary combination of constituent material, shape, and interaction anisotropy can be created. This tailorability leads us into a new age of materials science where customizable nanoparticles serve as the nanoscale building blocks to create the new materials that will allow us to solve our most pressing technological challenges. However, the enormous design space that makes nanoparticle-based materials so promising presents a unique challenge: its size and dimensionality means we cannot directly sample it experimentally. Computational modeling and simulation will therefore play a crucial role in ushering in this next generation of materials. Still, directly sampling the particle design space computationally is prohibited by its size, so the development of more efficient means of exploring this space is key to leveraging the full power of modern high performance computers to solve the open questions and challenges in the field.

The recent advances in particle synthesis techniques ultimately allow for control over different types of particle anisotropy, and it is this control over anisotropy that ultimately gives rise to the tailorability of synthetic nanoparticles. Two key types of anisotropy that influence particle assembly and phase behavior are particle shape and orientation-dependent interparticle interactions (i.e., “patchiness”), which are independent properties and can therefore be modulated separately. Even considering these two anisotropy dimensions, the size of the particle design space is both experimentally and computationally intractable. Efficient exploration of the design space therefore calls for inverse design methods, whereby the conventional forward-discovery paradigm is reversed, and we seek to discover building block attributes that give rise to specific desired behavior. Desired behavior may be any number of system properties, including a specific spatial arrangement of particles, a bulk material property, or a reconfigurability transition. Inverse design techniques, coupled with modern particle syntheses, open new avenues of research, for example, how to design functional nanomaterials.

One particularly challenging class of functional nanomaterials are open or porous structures. Because of their pores, open structures are promising candidates for the filtration and storage of nanoscale objects. Additionally, the amount of void space allows for rich fluctuations that endow open structures with exotic properties, e.g., negative thermal expansion, negative Poisson’s ratio, and photonic activity. While open structures are common in atomic and molecular materials, e.g., clathrates, zeolites, and metal–organic frameworks, no open colloidal crystals have been observed to date in the broad range of colloidal crystals that have been experimentally assembled. I aim to characterize the properties that are required to stabilize and assemble open colloidal crystals. My recent work has suggested and computationally validated a route to open structures via a host–guest strategy. However, many questions remain open, e.g., how do patchy interactions affect the assembly and stability of open structures, what is the specific role of the guest particle in the host–guest strategy, or what combinations of particle shape, patch arrangement, and system conditions best favor the formation of open structures? I will use inverse design in combination with direct simulation and advanced sampling to answer these types of questions. Importantly, I will seek experimental collaborators that can synthesize particles based on design rules I develop; this simulation–experimental collaboration provides a synergy whereby each side can guide the other towards promising new results.

I am in a unique position to make significant contributions to this important field given my experience in developing and implementing inverse design algorithms and simulation methods. The methods and tools we develop will be made freely available as open-source software to the benefit of the entire molecular simulation community. By constructing and studying simple models, we will be able to solve problems that span a wide range of size scales. These models and tools will be instrumental in realizing the possibilities offered by modern particle synthesis techniques, and will contribute to solving the world’s most pressing technological challenges.

Teaching interests and philosophy

In teaching, I have two goals for my students and mentees. First is the transfer of the technical skills that are directly relevant to the curriculum of study. Students that take my courses should leave with a broad understanding of the material and how it fits in with the larger curriculum, and they should be able to solve related problems in the real world. Graduate student mentees should leave my lab with the research skills that make them strong, independent researchers. However, teaching involves more than just the transfer of these hard skills. I strive to be a teacher that empowers students through the transfer of soft skills. Students that leave my classroom should not only have a firm grasp on the course material, but should grow in their abilities to independently learn new material and effectively communicate complex ideas. These are the skills that will set students apart beyond their university education. These technical and soft skills are best learned in a flipped classroom, where students are responsible for first encountering new material outside of the classroom, and using classroom time to practice using the new material through solving problems and explaining their solutions to their peers and instructors. This scenario forces students to take ownership of their education and gives them ample opportunities to develop their communication skills

My educational background in chemical engineering means I can teach any core course in the graduate and undergraduate curricula. My research experience has equipped me with the skills and desire to develop a hybrid graduate–undergraduate course that teaches the basics of molecular simulation and how it can be used to solve problems in chemical engineering. In addition to obtaining molecular-level insight into chemical processes that is becoming increasingly important as chemical engineering becomes a more molecular science, students will gain first-hand experience in using high-performance computing environments; these skills continue to become more broadly valuable as more fields increase their reliance on computation. In addition to teaching, a university faculty position gives one a platform from which they can make an impact in the community. I will continue to pursue outreach opportunities, especially those serving underrepresented groups, to foster interest in and support for the STEM fields within the community.