~4:00, move to the Amherst Room on the 10th Floor (Room 1009, take a left when you exit the elevators)
Directed Self-Assembly of Block Polymers; From Academic Curiosity, to Production of Next-Generation Nanocircuits
Directed copolymer assembly (DCA) has emerged as a promising alternative for patterning at sub-lithographic length scales. Much progress has been made over the past decade, but a number of significant challenges remain. Our recent efforts at the University of Chicago have focused on development of a molecular based, multiscale computational modeling approach aimed at gaining a fundamental understanding of directed copolymer assembly on nanopatterned substrates. This presentation will begin with a brief overview of available theoretical and computational approaches, along with a discussion of their advantages and limitations. That overview will be followed with a description of recent modeling advances that have enabled quantitative descriptions of time-dependent, morphological evolution during solvent annealing processes. For such cases, the models allow for a description of the selective, time-dependent swelling (or de-swelling) of distinct domains of the copolymer resist material, and are therefore able to describe the path followed by particular blends of copolymers, homopolymers, and solvents, on their way to metastable or equilibrium assembly. Given the predictive nature of such models, some of our recent efforts have gradually focused on the coupling of molecular modeling and evolutionary optimization algorithms. Through that coupling, a new paradigm is emerging in which computations are used to identify surface patterns and block polymer formulations leading to target morphologies and layouts. This presentation will also describe recent efforts to include a description of charged copolymer systems, which are of interest for energy storage, and where the goal is to describe the morphology and the partitioning of charged species in different domains of the polymer, as well as the corresponding interfacial and transport characteristics.
Juan de Pablo Biography
Much of Juan de Pablo’s work entails conducting supercomputer simulations to understand and design new materials from scratch and to find applications for them.
de Pablo is a leader of simulations of polymeric materials, including DNA dynamics — how DNA molecules arrange and organize themselves and interact with other DNA molecules. He also studies protein aggregation and its poorly understood relationship to various diseases, including type II diabetes and neurodegenerative disorders.
In 2011, de Pablo joined The Institute for Molecular Engineering at the University of Chicago as a Liew Family Professor. Prior to that time, he was part of the University of Wisconsin faculty and served as the Howard Curler Distinguished Professor and Hilldale Professor of Chemical Engineering. He holds over 20 patents on multiple technologies and is the author or co-author of more than 400 publications. He currently serves as Co-Director of the Center for Hierarchical Materials Design.
The International Technology Roadmap for Semiconductors has identified one of de Pablo ‘s collaborative inventions for directed self-assembly as a technology critical to the semiconductor industry’s miniaturization goals. Directed self-assembly provides engineers a means of coaxing organic materials to form patterns that direct the deposition of metals on integrated circuits.
A food manufacturer has licensed another of de Pablo’s patents for stabilizing proteins in bacteria or cells for long periods of time without refrigeration, but the patent also has potential pharmaceutical and medical applications. He is a fellow of the American Academy of Arts and Sciences, the American Physical Society, the Mexican Academy of Sciences and the European Academy of Sciences.
de Pablo earned a bachelor’s degree in chemical engineering from Universidad Nacional Autónoma de México in 1985. After completing his doctorate in chemical engineering from the University of California, Berkeley, in 1990, he conducted postdoctoral research at the Swiss Federal Institute of Technology in Zurich, Switzerland.