Jian Qin

Dr. Jian Qin is working on multiple projects in Professor de Pablo's group, including: (1) building theory and simulation models to understand the formation and properties of polyelectrolyte coacervates; (2) understanding phase behavior of salt-doped diblock copolymer melts; (3) developing free energy sampling algorithm for identifying the order-disorder temperature; (4) developing algorithm to optimize directed self-assembly pattern design with evolutionary strategy.

(1) Charged polymers of opposite signs can form complex aggregation in aqueous solutions known as the coacervate phase. The distinguishing feature of the coacervate phase is that it contains a large amount of water, which results in an extremely low interfacical tension while in contact with water. The process of coacervation was initially studied in the co-solution of arabic gums and gelatin, and have been investigated for decades. In this project, Dr. Jian Qin's goal is to understand the phase behavior of coacervation, by using both coarse-grained simulations and theoretical modeling. The preliminary results have been achieved on the study of interfacial tension between the coacervate phase and the coexisting supernatant water rich phase by using the classical Voorn-Overbeek model, and the manuscript summarizing these is currently being prepared.

(2) Salt-doped block copolymers is a promising lithium-ion conducting membrane solid electrolyte that can be used as electrode separation membranes in lithium-ion batteries, since it nicely combined the mechanical stability and relatively high ion conductivity, both entailed by the micro-phase separation. The project is aimed at studying the morphology and structures of ion-doped block copolymers (e.g., poly-(styrene-ethylene oxide)) by developing an efficient simulation package treating long ranged Coulomb interactions explicitly. The results related to this project are being assembled for publication.

(3) Identifying order-disorder transition temperatures in block copolymer materials accurately is challenging, even for the simplest lamella forming symmetric block copolymers, because of the issue of incommensurability and the presence of many closely-competing metastable phases. Sampling free energy directly would be a very reliable method for achieving this. To get the free energy or effective potential, a sensitive order parameter which delineates the disordered phase and the ordered phase nicely is defined, and an efficient and power free energy sampling technique using EXE-DOS (expanded ensemble density of state simulation) is implemented. The results related to this project are being assembled for publication.

(4) Directed self-assembling offered a suitable avenue for synthesizing large scale devices of feature sizes at the order of tens of nanometers. From the point of view of application, the challenging inverse problem is to design an economic (minimal) pattern to direct materials self-assembly. The approach is to abstract the pattern design into a few parameters, map the problem of designing a target pattern into an optimization problem, then implement a novel yet powerful optimization technique inspired by nature evolution, CMA-ES (covariance matrix adaptation—evolutionary strategy) to find the optimal solution. This project is in collaboration with graduate students Daman, Grant, Yongrui, and Marc (physics department). The preliminary results on this project have been accepted for publication in Soft Matter.