(7js) Modeling of Polymer Material Processing from Molecular Basis

My research group will concentrate on linking different modeling techniques and tools for hierarchical polymer material design. Polymeric materials have been empowering industrial growth for decades. Polymers are present in everyday consumer products, and are rapidly seizing new roles in bio-medicine and hi-tech applications, like drug delivery and computer chip fabrication. However, our understanding of the fundamental relations between polymer chemical composition and the properties of the final product is rudimentary.
The emphasis of my research plan will be on the development of comprehensive connections between different levels of description for dynamics predictions. My group will employ common tools for molecular modeling, such as atomistic and molecular dynamics simulations, mesoscopic/coarse-grained models, dynamic/kinetic Monte-Carlo, analytical theory, and computational fluid dynamics. However, transparent connections will allow to easily switch to a coarse-grained representation of the system, thus facilitating accessible prediction built upon detailed chemical structure. Building upon my experience with rigorous coarse-graining and polymer modeling, with focus on dynamic properties, the group will create a hierarchical framework, where the most detailed members explicitly contain full information about chemistry, while the least detailed members are suitable for macroscopic simulations of final products for direct manufacturing optimization. Currently I propose to address challenges in the following three research areas:
• Multi-level polyelectrolyte complexation modeling
• Coarse-grained model for dynamics of topological constraints
• Non-equilibrium processes in polymer manufacturing with molecular models and computational fluid dynamics

Teaching Interests:

Rapidly growth computational research increases role of programming for engineering, however there are no classes in a chemical engineering curriculum that cover it thoughtfully. The absence of such a class is a frequent complaint among PhD students. To address this problem, I would like to apply extensive experience with high-performance computations to develop High-Performance Computing in a Molecular Modeling class. In this class, I will cover common computational methods for molecular modeling, like coarse-grained molecular dynamics, atomistic simulations and self-consistent filed theory. Specific algorithms and their implementations on GPU and other parallel environments will be discussed. The course will also provide general skills for a large-scale software development and cover modern software optimization techniques. I was involved with chemical engineering departments throughout my career and I am prepared to teach common core classes, like Transport Phenomena, Thermodynamics, Statistical Mechanics, both at graduate and undergraduate levels. In addition, my research was in the field of polymer physics, and can teach a Rheology or Polymer Science class.

Selected Publications:

1. M Andreev, A Chremos, JJ de Pablo and JF Douglas, Coarse-Grained Model of the Dynamics of Electrolyte Solutions, J. Phys. Chem. B, 2017
2. S Srivastava, M Andreev, AE Levi, DJ Goldfeld, J Mao, WT Heller, V Prabhu, JJ de Pablo and MV Tirrell, Gel Phase Formation in Dilute Triblock Copolyelectrolyte Complexes, Nature Communications, 8, 14131, 2017
3. M Andreev, JD Schieber, Accessible and Quantitative Entangled Polymer Rheology Predictions, Suitable for Complex Flow Calculations, Macromolecules, 48 (5), 1606-1613, 2015
4. JD Schieber, M Andreev, Entangled polymer dynamics in equilibrium and flow modeled through slip links, Annual Review of Chemical and Biomolecular Engineering (5), 367-381, 2014
5. M Andreev, RN Khaliullin, RJA Steenbakkers, JD Schieber, Approximations of the discrete slip-link model and their effect on nonlinear rheology predictions, Journal of Rheology, (57), 535-557, 2013