Materials Science Research Lecture
First Principles Simulations of Hybrid Inorganic Interfaces
Webinar ID: 832 7665 2110
Inorganic interfaces lie at the heart of semiconductor, spintronic, and quantum devices. At a hybrid interface between two dissimilar materials (e.g., a ferromagnet and a semiconductor) physical properties and functionalities may arise, which do not exist in any of the isolated components in the bulk. The resulting device performance hinges on the electronic and magnetic properties of the interface, as well as on its quality. As devices become increasingly smaller, precise control over interface structure becomes increasingly critical. At the same time, the configuration space of possible inorganic interfaces is vast and largely underexplored, owing to the almost infinite number of ways different materials can be combined to form interfaces. The experiments required to fabricate high-quality defect-free interfaces and devices are costly and time consuming. Therefore, it is unfeasible to explore the space of possible structures and compositions by experimental means alone. Computer simulations may significantly accelerate the discovery and design of new inorganic interfaces with desirable properties.
To predict the structure of domain-matched epitaxial interfaces we use a combination of lattice matching and surface matching algorithms . To study the electronic properties of interfaces we use density functional theory (DFT). Within DFT, the many-body interactions between electrons are described by approximate exchange-correlation functionals. The accuracy of the results hinges on an appropriate choice of functional. We have developed a method of machine learning the Hubbard U correction added to a DFT functional by Bayesian optimization (BO) . The DFT+U(BO) method balances accuracy with computational cost, enabling unprecedented simulations of large surface and interface models of interest for applications in quantum computing. These include InAs and InSb surfaces , which are the substrates of choice for superconductor/semiconductor Majorana devices; the HgTe/CdTe and InAs/GaSb interfaces , in which a 2D topological insulator phase may arise, and the EuS/InAs interface , which is considered as a promising candidate for the realization of a ferromagnet-semiconductor-superconductor Majorana device, which does not require an external magnetic field.
 S. Moayedpour, D. Dardzinski, S. Yang, A. Hwang, N. Marom "Structure Prediction of Epitaxial Inorganic Interfaces by Lattice and Surface Matching with Ogre", J. Chem. Phys., 155, 034111 (2021)
 M. Yu, S. Yang, C. Wu, and N. Marom "Machine Learning the Hubbard U Parameter in DFT+U Using Bayesian Optimization", npj Computational Materials 6, 180 (2020)
 S. Yang, N. Schröter, S. Schuwalow, M. Rajpalk, K. Ohtani, P. Krogstrup, G. W. Winkler, J. Gukelberger, D. Gresch, G. Aeppli, V. N. Strocov, R. M. Lutchyn, N. Marom "Electronic Structure of InAs and InSb Surfaces: Density Functional Theory and Angle-Resolved Photoemission Spectroscopy" arXiv:2012.14935 (2020)
 S. Yang, D. Dardzinski, A. Hwang, D. I. Pikulin, G. W. Winkler, N. Marom "First Principles Feasibility Assessment of a Topological Insulator at the InAs/GaSb Interface", Phys. Rev. Mater. 5, 084204 (2021)
 M. Yu, S. Moayedpour, S. Yang, D. Dardzinski, C. Wu, V. S. Pribiag, N. Marom "Dependence of the Electronic Structure of the EuS/InAs Interface on the Bonding Configuration", Phys. Rev. Mater. 5, 064606 (2021)
More about the Speaker:
Noa Marom received a B.A. in Physics and a B.S. in Materials Engineering, both Cum Laude, from the Technion- Israel Institute of Technology in 2003. From 2002 to 2004 she worked as an Application Engineer in the Process Development and Control Division of Applied Materials. In 2010 she received a Ph.D. in Chemistry from the Weizmann Institute of Science. She was awarded the Shimon Reich Memorial Prize of Excellence for her thesis. She then pursued postdoctoral research at the Institute for Computational Engineering and Sciences (ICES) at the University of Texas at Austin. From 2013 to 2016 she was an Assistant Professor in the Physics and Engineering Physics (PEP) Department at Tulane University. In 2016 she joined the Materials Science and Engineering Department at Carnegie Mellon University as an Assistant Professor. In 2021 she was promoted to Associated Professor. She holds courtesy appointments in the Department of Chemistry and the Department of Physics. She is a member of the Pittsburgh Quantum Institute (PQI) and an affiliate of the Scott Institute for Energy Innovation. Her achievements in research and in large-scale computing have been recognized by several awards, including the Sanibel Symposium Young Investigator Award (2016), NSF CAREER (2016), the DOE Innovative and Novel Computational Impact on Theory and Experiment (INCITE) Award (2017, 2018, 2019), the Charles E. Kaufman Young Investigator Award (2017), the IUPAP Young Scientist Prize in Computational Physics (2018), The George Tallman Ladd Award of the CMU College of Engineering (2020), the ACS COMP OpenEye Outstanding Junior Faculty Award (2021), and the CMU College of Engineering Dean's Early Career Fellowship (2021).
Contact: Jennifer Blankenship email@example.com