First-principles identification of localized trap states in polymer nanocomposite interfaces

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First-principles identification of localized trap states in polymer nanocomposite interfaces Abhishek Shandilya1

, Linda S. Schadler2, Ravishankar Sundararaman1,a)


Department of Materials Science and Engineering, Rensselaer Polytechnic Institute, Troy, New York 12180, USA Department of Mechanical Engineering, University of Vermont, Burlington, Vermont 05405, USA a) Address all correspondence to this author. e-mail: [email protected] This paper has been selected as an Invited Feature Paper. 2

Received: 14 October 2019; accepted: 3 January 2020

Ab initio design of polymer nanocomposite materials for high breakdown strength requires prediction of localized trap states at the polymer–filler interface. Systematic first-principles calculations of realistic interfaces can be challenging, particularly for amorphous polymers and fillers that necessitate the calculation of ensembles of large unit cells with hundreds of atoms. We present a computational approach for automatically generating reasonable structures for amorphous polymer–filler interfaces, combining classical molecular dynamics and Monte Carlo simulations. We identify trap states by analyzing the localization of electronic eigenstates calculated using density functional theory on ensembles of interface structures, clearly distinguishing shallow trap states from delocalized band-edge states. Applying this approach to silica– polyethylene interfaces as an initial example, we find under-coordination and distorted coordination structures at amorphous silica surfaces contribute a combination of deep and shallow traps at these interfaces, whereas polyethylene does not generate localized interfacial states.

Ravishankar Sundararaman

Ravishankar Sundararaman is an assistant professor in the Department of Materials Science and Engineering at Rensselaer Polytechnic Institute since 2016. He was previously a postdoctoral fellow in the Joint Center for Artificial Photosynthesis at Caltech, with a Ph.D. in Physics from Cornell University in 2013 and an MS in Physics from IIT Kanpur in 2007. His research group specializes in ab initio multiphysics: techniques that bring together quantum electronic structure calculations with coarsegrained classical simulations for computational prediction of material properties and phenomena that are inaccessible with electronic structure calculations alone. He has developed continuum solvation methods to accurately simulate structure, dynamics, and chemical reactions at solid–liquid and electrochemical interfaces for designing improved electrocatalyst and battery electrode materials for energy conversion and storage. His work in first-principles calculations of plasmonic hot carrier dynamics reveals the important role and strong material dependence of carrier energy relaxation and highlights the need for material advances to efficiently capture light in metal nanostructures. Ravishankar leads the development of open-source software, JDFTx, designed for rapid implementation and wide adoption

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