Collaborative Research: DMREF: Deep learning guided twistronics for self-assembled quantum optoelectronics

University Of Pennsylvania, Philadelphia PA

Investigators

Abstract

Non-technical Description: Atomically thin two-dimensional (2D) materials can host intriguing quantum properties not found in their bulk counterparts. Furthermore, stacking 2D materials with control over the twist angles between adjacent layers provides a versatile way to obtain novel quantum materials with unprecedented properties. Such “twistronic” materials can have applications in electronics, photonics and quantum information science and technologies. However, with the new degrees of freedom, the materials design parameter space becomes exceedingly large, posing a significant challenge to predictably design and precisely make materials to enable such unique properties. In this DMREF project, the collaborative team from University of Pennsylvania, University of Wisconsin-Madison, and Northeastern University will use computer aided deep learning models and theoretical tools to predict designer twistronic materials prepared in specific states and guide the unique self-assembled crystal growth to engineer twist angles in different 2D materials. The team will perform property measurements to characterize these systems and also extend the ideas to quantum photonics to assemble on-chip devices. Results from synthesis, characterization and device measurements will be fed back to the theoretical models for establishing a self-consistent and tightly integrated research for further discovery of new designer twistronic materials with precisely controlled responses that can enable a new paradigm for quantum materials research with applications in computing, communications, imaging and sensing. Interdisciplinary research activities will be integrated with educational and outreach initiatives by involving students at all levels from diverse backgrounds in the collaborative research project with emphasis on quantum materials and photonics. Technical Description: Modern quantum materials are typically designed by engineering symmetries combined with strong spin-orbit coupling at the atomic and lattice length scales. In two-dimensional (2D) materials with chiral symmetry complemented by many-body interactions such as interlayer coupling, controlling the interlayer twist angle offers a promising strategy to achieve novel quantum properties such as flat bands, topological phases, and large nonlinear optical responses. However, two major challenges impede the progress in “twistronic” materials: 1) the dramatic increase in the degrees of freedom of the systems makes it prohibitively difficult to predict the material compositions, crystal phases and interlayer twists needed to achieve a particular quantum phase; and 2) the current material fabrication method consisting of exfoliating and reassembling 2D material layers with manual control over the interlayer twist angles is a laborious process with low yields. In this DMREF project, a highly interdisciplinary team will break the fundamental limitation of designing twistronic materials via deep learning-based symmetry and topological engineering of materials and metamaterials. Starting from a quantum paradigm, the atomic scale symmetry and topology in 2D materials will be optimized for targeted chiral responses. Guided by theory, multilayer twisted 2D materials will be synthesized with rational control over interlayer twist angles, compositions, and crystal phases to realize novel and predictable quantum properties. New knowledge will be generated to enable the rational design of quantum twistronic materials with highly predictive power to demonstrate novel chiral optoelectronic responses, which will also be extended to quantum photonic systems. These advances can enable the next generation of electronics and optical devices such as on-chip coherent chiral emitters, entangled photon emission and detection with precisely controlled responses. The interdisciplinary project will provide an excellent educational opportunity for training graduate, undergraduate and K-12 students on the important concepts of geometry, crystal structures and quantum physics with an emphasis on increasing the participation of underrepresented groups. Funding for the award is from the Mathematical and Physical Sciences (MPS) Divisions of Materials Research (DMR) and Chemistry (CHE) through the Designing Materials to Revolutionize and Engineer our Future (DMREF) program. 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.