LDRD seminar: June 12
Three Argonne researchers will discuss their Laboratory-Directed Research and Development (LDRD) sponsored work at the LDRD Seminar Series presentation Tuesday, June 12, 2018, at 12:30 p.m. in the Building 203 Auditorium. All are welcome to attend.
Visit the LDRD website to view upcoming seminars.
“Gating Superconductivity for Qubits”
By Physicist Anand Bhattacharya (MSD)
Josephson junctions are used extensively in superconducting circuits for quantum information processing, for example in tunable coupled oscillators. Typically their properties can be controlled by applying magnetic fields. While this has been a successful approach, it has inherent limitations. I will talk about our efforts to realize Josephson junctions that can be tuned using gate electric fields, like those in conventional transistors. I will discuss the challenges that need to be addressed, mostly from a materials perspective.
Anand Bhattacharya works in the Materials Science Division. He likes to make and study thin films and heterostructures of materials with interesting electronic and magnetic properties.
“Tomographic Reconstruction with Simultaneous
By Assistant Computational Scientist Zichao (Wendy) Di (MCS)
The advanced imaging technique, which leads to unquestionable improved clarity of sample structure, is highly vulnerable to systematic and random errors. These errors are fundamental obstacles to a full realization of the next-generation photon science since they can lead to reduced spatial resolution and even misinterpretation of the underlying sample structures. In this work, we formulate new physical models to capture these experimental errors and we devise new mathematical optimization formulations for robust inversion of complex sample. The numerical results are demonstrated on both synthetic and real data.
Zichao (Wendy) Di is an assistant computational scientist. She received her Ph.D. in applied mathematics from George Mason University in 2013. She is interested in the mathematical modeling and nonlinear optimization aspect of imaging and inverse problems.
“New Materials for Energy-Efficient Neuromorphic Computing”
By Principal Agronomist/Environmental Engineer
Jianqiang (Jerome) Lin (NST)
In this talk, I will introduce the use of oxide electronics for neuromorphic information processing. Using the insulator-metal transition (IMT) effect in transition-metal oxides as an example, I will discuss the construction of an artificial integrate-and-fire neuron through feedback-engineering of the intrinsic properties of IMT materials. I will also describe the development of a complete electro-thermal device model for devices based upon the metal-to-insulator effect that accurately predicts the experimental performance of emerging devices such as artificial neurons and threshold selector switches (for emerging memory), and establishes the performance limits as well as design guidelines for such devices.
Jerome Lin is a postdoctoral fellow at Argonne National Laboratory and the University of Chicago. He received a Ph.D. degree in electrical engineering from MIT (2015); and the M.Eng. (2009) and B.Eng. (2007) degrees in electrical engineering from National University of Singapore. His research focuses on the application of new materials and devices for future energy-efficient computing. His postdoctoral research focuses on nanoscale oxide electronic devices for new memory technology and neuromorphic computing applications. In 2012 and 2013, he was a summer research intern at the IBM T.J. Watson Research Center.