Electric Field Tuning of 2D Quantum Materials via III-Nitride Ferroelectrics

Abstract

Approved for Public ReleaseOver the past decade, the emergence of 2D materials, along with the development of field effect gating and various doping techniques, has created opportunities to further the exploration of quantum phenomena in the 2D limit, ushering inthe possibility of quantum phase transitions such as superconductivity and topological band inversion in solid-state electronics. Such advancements could have a profound and immediate impact on traditional computing; for example, field-induced switching of quantum state could lead to opportunities such as logic or memory applications spanning large-scale data computation, pattern matching, machine learning, and deep learning through innovative computations and algorithms pushing the boundaries of Moore s Law. On the otherhand, from a physical perspective, the electrostatic carrier doping opens doors to the control of superconducting properties, quantum phases, and bandgap, by means of the introduction of high carrier densities into the 2D channel. Therefore, exploring the degreesof freedom in 2D quantum materials through field-effect gating and doping, while seeking effective control methods, holds the potential to establish a novel paradigm for the next generation of classical and quantum devices. The overall objective of the proposed research is to gain a fundamental understanding of topological and strongly correlated quantum phenomena at the interfaces of van derWaals 2D semiconductors and 3D nitride ferroelectrics interfaces. In particular, the emphasis is on understanding and realizing of these phenomena can be electrically tuned or switched using the switchable property of ferroelectric polarization, which is also non-volatile in nature. The grand objective is to identify the right combination and composition of 2D materials + 3D nitride ferroelectric for understanding and realization of (i) superconductivity, (ii) topological band inversion and (iii) multiferroicity in 2D materials at ultra-highsheet carrier densities when coupled to high-polarization III-Nitride ferroelectrics. We propose Ferroelectric Field-Effect Transistors (FE-FETs) as the basic experimental unit that will be used to explore the above proposed overarching goal. We propose to investigate various material combinations for each category of phenomena well as propose tuning of physical parameters such as single gate vs dual gate FET structures. Accompanying this, we will conduct a suite of variable temperature charge and magneto transport in direct current (DC), alternating current (AC) and pulsed modes, scanning probe measurements, variable temperature optical spectroscopy to arrive at an in-depth understanding of what electronic phase transformation occurs 2D materials when interfaced with high polarization ferroelectrics at high carrier densities and high electric fields. One targeted outcome of this project is to attain a fundamental understanding of the limits of 2D charge carrier densities and electricfields that can be supported in 2D layers in the solid-state. On the more applied side, a noteworthy outcome would be experimental demonstration of field tunable superconductivity, magnetism, topological band inversion or other quantum phase transitions. These developments will be particularly critical for low-power computing devices as well as novel computing devices that need to operate in either resource scare or extreme environments or both which are relevant for many research programs and technologies in the US Navy.

Document Details

Document Type
DoD Grant Award
Publication Date
Mar 08, 2024
Source ID
N000142412131

Entities

People

  • Deep Jariwala

Organizations

  • Office of Naval Research
  • United States Navy
  • University of Pennsylvania

Tags

Fields of Study

  • Physics

Readers

  • Materials Science and Engineering.
  • Quantum Dot Semiconductor Device Photonics and Graphene Optoelectronic Materials and THz Physics.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • Microelectronics
  • Microelectronics - Graphene
  • Quantum Computing