NRC Postdoctoral Fellowship at NIST on Computational Self-Assembly of Soft Matter Systems
We are looking for a highly motivated postdoctoral candidate to use theory, molecular simulation, and machine learning to understand how chemical functionalization of soft matter systems (e.g., colloids, polymers) affects their self-assembly into different structures. Recent work has shown how phase diagrams can be predicted for multicomponent colloidal assemblies using novel structure enumeration schemes based on symmetry [1,2]. This project will focus on extending previous work and connecting it with experimentally viable design routes to enable the rational design and synthesis of colloidal crystals, monolayers, and functional materials.
[1] “Using symmetry to elucidate the importance of stoichiometry in colloidal crystal assembly,” N. A. Mahynski, E. Pretti, V. K. Shen, J. Mittal, Nature Commun., 10 2028 (2019).
[2] “Symmetry-based crystal structure enumeration in two dimensions,” E. Pretti, V. K. Shen, J. Mittal, N. A. Mahynski, J. Phys. Chem. A 124, 3276-3285 (2020).