(66a) Predictive Design of Biomimetic Nanomaterials Via Bottom­ up Approaches | AIChE

(66a) Predictive Design of Biomimetic Nanomaterials Via Bottom­ up Approaches

Authors 

Nguyen, T. - Presenter, Northwestern University
Developing transformative approaches for engineering materials and technologies is crucial for addressing urgent national and global challenges in healthcare, renewable energy and the global environment. One promising solution to this growing problem is to develop synthetic materials and devices that can mimic the complex functions of biological matter. Towards this end, bottom­ up approaches including self­ and directed ­assembly techniques have been shown as a powerful means for engineering the underlying nanostructure of this exciting class of materials and devices. The fundamental challenges to these bottom ­up techniques are to design the optimal nano building blocks such as block copolymers, nanoparticles and colloids, and efficient assembly pathways for desirable nanostructures. In this talk, I will summarize my past and current studies that are devoted to addressing these challenges. I will show how the size and shape of the assembled nanostructures can be controlled through the electrostatic interactions between nanoparticles and colloids. The resulting assemblies are highly uniform size, reminiscent of virus capsids. I will also demonstrate the ability of random copolymers, which mimic intrinsically disordered proteins in living cells, to encapsulate and protect numerous proteins in non-native media. The assembled polymer-protein complexes are designed so that they function as nanoreactors where the proteins inside retain their activities. Also presented are the algorithms and methods I have been developing to improve the efficiency of simulation studies in general, and for my studies in particular, ranging from massively parallel simulation codes to enhanced sampling techniques, which are now available to the public through the software packages LAMMPS and HOOMD-Blue. Overall, the goal of my studies is to accelerate the design of adaptive, programmable nanomaterials for a broad range of applications including, but not limited to, drug delivery and release, biosensing, bioremediation, energy storage and conversion.