Statistical Thermodynamics & Molecular Simulations (STMS) Seminar Series: Prof. Gaurav Arya (Duke University) and Ms. Ziqiu Chen (University of Illinois, Urbana Champaign)
These seminar series are aimed at providing a virtual platform for sharing scientific research in the area of statistical mechanics, molecular simulations, and computational materials science. Since early 2020, the coronavirus pandemic has disrupted many large in-person scientific gatherings, including conferences and department seminars. STMS is aimed at filling this gap, and provide a venue for dissemination of research findings and exchange of ideas in the age of COVID. This model is being currently used by several other scientific communities, and can potentially continue even beyond the pandemic if successful.
Each seminar will be a 60-minute event and will comprise of a long-form (30-minute) talk by a principal investigator or a senior research scientists from academia or industry and a short-form (15-minute) presentation by a graduate student or a postdoc. The remainder of the event will be dedicated to Q&A (10 minutes for the PI, 5 minutes for the student/postdoc). Long-form speakers will be chosen by the STMS Organizing Committee, while we encourage suggestions from the community at large. Student and postdoctoral speakers can either be nominated by their advisors or can self-nominate themselves by sending a CV to the organizers. During 2022 we expect to hold two seminar per month, and the events will take place in the last two Fridays of each month, from 10:45 AM-12:00 PM Eastern Standard Time (EST):
This event's talks:
Interfacial assembly of ligand-functionalized nanoparticles into low-dimensional architectures
Prof. Gaurav Arya (Duke University)
Abstract: Self-assembly of nanoparticles (NPs) is a powerful approach for fabricating materials with unique architectures and properties. This is especially important for plasmonic, optical, and electronic applications where nanostructures need to be arranged in non-close packed clusters or periodic arrays to take advantage of the unique electromagnetic couplings that emerge from such arrangements. However, achieving unique and complex assemblies remains a challenging task. In this talk, I will demonstrate how fluid-fluid interfaces can be used to self-assemble ligand-functionalized NPs into exotic 1D and 2D architectures by harnessing the three-way competition between particle-particle interactions, particle-fluid surface energy, and fluid-fluid surface tension. I will begin by demonstrating viamolecular dynamics simulations the interfacial assembly of binary systems of spherical NPs into open clusters, quasi-linear strings and networks, and layered structures [1]. Next, I will show how Monte Carlo optimization combined with analytical modeling of interfacial interactions can be used to quickly map out the full repertoire of 2D NP superlattices achievable through this interfacial assembly approach [2]. I will also show how this approach can be extended to shaped NPs, where a range of periodic porous superlattices may be assembled from polymer-grafted nanocubes by controlling their orientation at the interface [3]. Lastly, I will discuss the development of multibody potential via a machine learning approach to elucidate the role of multibody effects in the self-assembly of polymer-grafted NPs [4]. Overall, our results suggest that the interfacial assembly approach could be a versatile platform for fabricating 1D and 2D colloidal assemblies of tunable structure and properties.
[1] T.-Y. Tang, Y. Zhou, and G. Arya. Interfacial Assembly of Tunable Anisotropic Nanoparticle Architectures. ACS Nano 2019, 13: 4111-4123.
[2] Y. Zhou and G. Arya. Discovery of two-dimensional binary nanoparticle superlattices using global Monte Carlo optimization. Nat. Commun. 2022, 13:7976.
[3] Y. Zhou, T.-Y. Tang, B.H.-J. Lee, and G. Arya. Tunable Orientation and Assembly of Polymer-Grafted Nanocubes at Fluid–Fluid Interfaces. ACS Nano 2022, 16: 7457-7470.
[4] Y. Zhou, S. Bore, A. Tao, F. Paesani, G. Arya. Many-body Potential for Simulating the Self-Assembly of Polymer-Grafted Nanoparticles in a Polymer Matrix. ChemRxiv 2023.
Speaker Bio: Gaurav Arya is a Professor of Mechanical Engineering and Material Science, Biomedical Engineering, and Chemistry at Duke University. Prior to joining Duke in Fall 2017, he was an Assistant Professor and then Associate Professor in the Department of NanoEngineering at UC San Diego. He obtained his B.Tech. degree in Chemical Engineering from IIT Bombay in 1998, and Ph.D. degree, also in Chemical Engineering, from the University of Notre Dame in 2003. He carried out his postdoctoral research at Princeton University and New York University. Professor Arya’s research focuses on molecular-scale modeling of biological and soft materials. Specifically, he uses molecular simulations to predict material properties and gain molecular-level understanding of material behavior, with the overarching aim of discovering new phenomena and developing new materials. His current research falls within the themes of nanoparticle-polymer composites, DNA nanotechnology, and DNA translocation motors, and is well-supported by grants from NSF, DOE, and NIH. His group has published over 90 peer-reviewed articles and book chapters, many in prestigious journals.
Polyethylene in dead-end silica nanopores: Forces and mobility from non-equilibrium statistical mechanics and ESXY NMR
Ms. Ziqiu Chen (University of Illinois, Urbana Champaign)
Abstract: Billions of tons of plastic have been produced and only a small fraction of this has been recycled. Tennakoon et al. [Nature Catalysis 3, 893 (2020)] developed a catalyst that repeatedly cleaves C10-C30 hydrocarbons from the end of a polyethylene chain. The reaction occurs at a Pt nanoparticle at the base of a cylindrical silica mesopore with a diameter of 2 nm and a length of 110 nm. Portions of the polymer situated inside the pore can be differentiated from those outside using 13C NMR, allowing the dynamics and extent of polymer threading to be monitored using 2D EXSY NMR. We construct a Fokker-Planck equation for the polymer dynamics by assuming a reptation diffusivity and a graduated adsorption free energy that depends linearly on the depth of polymer penetration in the pore. The solutions allow us to predict the intensities of the 2D NMR resonances as a function of time. We use the solutions to extract a polymer diffusivity at each temperature and estimate the per-segment desorption free energy, enthalpy, and entropy. Random and systematic errors are examined to test key assumptions in the theory and interpretation of the experiments.
Speaker Bio: Ziqiu Chen is a PhD candidate in chemical engineering from Prof. Baron Peters’ group. She acquired a bachelor’s degree in chemical engineering from Syracuse University in 2019. Her research of interests is reaction catalysis, multi-scale modeling and polymer upcycling.