CAREER: Quantum defects in two-dimensional materials by local-symmetry-guided data-driven design

This award is funded in part under the American Rescue Plan Act of 2021 (Public Law 117-2). NONTECHNICAL SUMMARY

This CAREER award supports theoretical and computational research integrated with education activities to advance the fundamental understanding of quantum defects and discover novel functional material systems for quantum information science and technologies. Qubits and novel quantum devices such as quantum emitters lie at the center of the ongoing quantum information revolution that is expected to transform science and society in previously unimaginable ways.

Quantum defects, such as missing atoms or impurities, in two-dimensional materials offer a new paradigm for the realization of patterned fabrication and operation of quantum functionality components. By incorporating symmetry-guided design principles and data-driven approaches, the PI and his team will facilitate breakthroughs for the discovery and design of novel quantum defects with unique electronic structures for quantum information science and technologies. The research will pave the path toward the creation of a quantum defect design platform.

The research project will be integrated with educational activities through the incorporation of numerical simulations and machine learning modules, as well as outreach activities to K-12 students. Quantum materials, machine learning, and numerical simulation modules will be incorporated in undergraduate and graduate courses. The construction of an interdisciplinary research environment will allow multi-level students to acquire a complete set of skills and grasp a big picture of quantum information science.

The PI will participate in scientific outreach by developing activity kits and demos in collaboration with local science museums including the Franklin Institute. Educational modules for middle school and high school students will be developed to introduce quantum physics and artificial intelligence.

TECHNICAL SUMMARY

This CAREER award supports theoretical and computational research activities to develop and utilize first-principles computations and data-driven approaches to provide insights into the quantum phenomena in technologically important defect-based two-dimensional (2D) quantum systems. Quantum defects are characterized by local symmetries and complex interactions with their host materials.

The research will advance fundamental understanding of quantum defects in 2D materials as spin qubits and quantum emitters by revealing the interplay of local symmetry and host environment. By harnessing symmetry information and adopting state-of-the-art learning architectures, the PI and his team will develop a novel machine learning framework to enable the use of deep learning for defect property predictions.

The ultimate outcome of this project will be to provide fundamental understanding and symmetry-based design principles for targeted quantum defect functionalities in 2D materials and beyond. This will open a new data-driven pathway for quantum information science and technologies based on quantum defects in 2D solid-state systems.

The research project will be integrated with educational activities through the incorporation of numerical simulations and machine learning modules, as well as outreach activities to K-12 students. Quantum materials, machine learning, and numerical simulation modules will be incorporated in undergraduate and graduate courses. The construction of an interdisciplinary research environment will allow multi-level students to acquire a complete set of skills and grasp a big picture of quantum information science.

The PI will participate in scientific outreach by developing activity kits and demos in collaboration with local science museums including the Franklin Institute. Educational modules for middle school and high school students will be developed to introduce quantum physics and artificial intelligence.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.