CAREER: Global Quantum Modeling of Topological Nanosystems for Energy-Efficient Devices.

University Of Illinois At Urbana-Champaign, Urbana IL

Investigators

Abstract

The majority of information processing is done using Complementary Metal Oxide Semiconductor (CMOS), an architecture based on a series of interconnected Metal Oxide Semiconductor Field Effect Transistors (MOSFET). The MOSFET is a very simple semiconductor device in which an applied electric field controls electrical current flow between two electrical contacts allowing the definition of "on" states with current flowing and "off" states with no current flow. Using these characteristics of "on" and "off" states, it is possible to then define bits "1" and "0" which form the basis of digital information processing. Our society is becoming increasingly dependent on digital information processing systems used in, e.g., computers, smart phones, and televisions for every aspect of our personal and professional lives. The related societal demand for increased performance from ever-smaller electronic devices is driving the miniaturization of the MOSFET. However, future miniaturization of the MOSFET is predicted to result in not only diminishing returns in device performance, but also in devices that consume too much power. Thus, a grand challenge is to design and implement novel information processing devices that bypass the limitations of the MOSFET. The solution to this problem will require an orthogonal approach that utilizes new materials and new approaches to solve this power consumption problem. In the past several years, topological systems have been the focus of intense theoretical and experimental study. Topological states are unique in the sense that their existence is protected by an underlying symmetry present in the system, so the states cannot be removed unless the symmetry is broken. Topological materials have the potential to make a disruptive change to information processing due to their unique physical properties. Nonetheless, a key aspect missing from topological research is a path to move from basic physics to engineering real-world devices. This work will bridge the fundamental physics and engineering world to develop tools that serve to address the many open questions remain about the behavior of topological materials at the nanoscale, the answers to which, will ultimately dictate their role in future nanosystems that consume less power with minimal sacrifice of performance. This CAREER award sets forth a series of tasks designed to take advantage of the exciting opportunity to study topological nanosystems under a variety of different operating conditions with the stated goal of understanding their applicability in future information processing systems. In particular, the award aims to understand the light-matter interactions and high-frequency responses in topological nanosystems. Numerical results will be attained by, for the first time, coupling the time-dependent versions of the Kadanoff-Baym quantum transport equations to the full solution to Maxwell's electromagnetic curl equations in three spatial dimensions. We will use this quantum global modeling tool to gain a fundamental understanding of how Maxwell's equations are modified in 3D topological materials under electromagnetic illumination. Furthermore, we will apply this knowledge of fundamental responses to understand the role topological materials may play in future nanosystems. Additionally, in conjunction with the numerical approach, compact models for each of the devices considered will be derived based on the results of the detailed numerical simulations to provide a strong bridge between the physical principles of the topological nanodevices and simple models useful to researchers seeking to design circuit architectures utilizing such devices. Such compact models will be derived using a variety of analytical techniques ranging from basic field theory to semi-classical magnetism. The results of this work will not only increase theoretical understanding of topological materials and their ultimate applicability in future information processing systems, but will also help in the design and interpretation of experiments and circuits.