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

合作研究：DMREF：用于自组装量子光电子学的深度学习引导双电子学

• 批准号: 2323470
• 负责人: Song Jin
• 金额: $ 48.5万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2027-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2323470&HistoricalAwards=false
• 关键词: Collaborative; Research; DMREF; Deep; learning

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.

非技术描述：原子薄的二维 (2D) 材料可以具有其块状单元中所没有的有趣的量子特性。此外，通过控制相邻层之间的扭转角来堆叠 2D 材料提供了一种获得新型量子材料的通用方法。这种“双电子”材料可以在电子、光子学和量子信息科学和技术中得到应用，然而，随着新的自由度，材料设计参数空间变得非常大，对可预测的设计和精确的设计提出了重大挑战。在这个 DMREF 项目中，来自宾夕法尼亚大学、威斯康星大学麦迪逊分校和东北大学的合作团队将使用计算机辅助深度学习模型和理论工具来预测在特定州和地区制备的设计师扭曲电子材料。指导独特的自组装晶体生长来设计不同二维材料的扭转角，该团队将进行属性测量来表征这些系统，并将这一想法扩展到量子光子学以组装片上器件的合成、表征和器件测量结果。将反馈到模型理论，以建立自洽且紧密集成的研究，以进一步发现具有精确控制响应的新设计双电子材料，从而为量子材料研究及其在计算、通信、成像和传感领域的应用提供新范式跨学科研究活动将与教育和推广活动相结合，让来自不同背景的各级学生参与合作研究项目，重点是量子材料和光子学。 技术描述：现代量子材料通常是通过工程对称性与强自旋相结合来设计的。原子轨道耦合在具有手性对称性并辅以层间耦合等多体相互作用的二维 (2D) 材料中，控制层间扭转角提供了一种有前景的策略来实现新的量子特性，例如平带、拓扑相和量子力学。然而，两个主要挑战阻碍了“双电子”材料的进展：1）系统自由度的急剧增加使得预测材料成分、晶相和中间层变得异常困难。实现特定量子相所需的扭曲；2) 当前的材料制造方法包括剥离和重新组装 2D 材料层并手动控制层间扭曲角度，这是一个费力且产量低的过程。通过基于深度学习的材料和超材料的对称性和拓扑工程，将打破设计双电子材料的基本限制。从量子范式出发，二维材料中的原子尺度对称性和拓扑结构将被打破。在理论指导下，通过合理控制层间扭曲角度、成分和晶相来合成多层扭曲二维材料，以实现新颖且可预测的量子特性，从而产生新的知识，从而实现量子的合理设计。具有高度预测能力的双电子材料可以展示新颖的手性光电响应，这也将扩展到量子光子系统。这些进步可以实现下一代电子和光学设备，例如片上相干手性发射器、纠缠。该跨学科项目将为研究生、本科生和 K-12 学生提供极好的教育机会，让他们了解几何、晶体结构和量子物理学的重要概念，重点是增加代表性不足的群体的参与。该奖项的资金来自数学和物理科学 (MPS) 材料研究 (DMR) 和化学 (CHE) 部门，通过设计材料以彻底改变和设计我们的未来 (DMREF) 计划。该奖项反映了通过使用基金会的智力价值和更广泛的影响审查标准进行评估，NSF 的法定使命被认为值得支持。