Bottom-up computational design of hybrid 2D/3D nanostructures

混合 2D/3D 纳米结构的自下而上计算设计

• 批准号: RGPIN-2017-05187
• 负责人: Song, Jun
• 金额: $ 2.4万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=711425
• 关键词: Bottom; up; computational; design; hybrid

Thanks to their unique and remarkable physical and electronic properties, two-dimensional (2D) materials open up new categories of physics that are not available in conventional three-dimensional (3D) materials, promising unprecedented possibilities for nanotechnology and attracting enormous interests worldwide. However, the application of 2D materials is seriously bottlenecked by difficulties in large-scale high-quality fabrication and precise material manipulation. Aiming to tackle the above challenges, this NSERC Discovery Grants (DG) program proposes to explore novel design routes to directly transform 2D materials or to integrate them with 3D nanomaterials into hybrid 2D-3D nanostructures. Such hybrid nanostructures retain many unique properties of its 2D components while provide a bulk form to ease manipulation and incorporation in the device design. Meanwhile they also serve as an efficient means to ease the application of external fields, such as electric and strain fields, to engineer the properties of 2D materials, providing a path towards the design of tunable nanodevices. Employing a multi-scale computational approach that involves several simulation and modeling techniques, several representative hybrid 2D-3D nanostructures will be rigorously studied. Meanwhile, the physics-based materials modeling and simulations will be meshed with the machine learning framework to accelerate the exploration and design of hybrid 2D-3D nanostructures. The proposed NSERC DG program is firmly founded on my strong research activities on 2D nanomaterials, which are largely enabled by my current NSERC DG (2012-2017). The knowledge, understanding and computational tools I amassed in those activities are valuable assets that will be largely applicable to this DG program, putting me in a perfect position to tackle the proposed research. The expected research outcomes will provide unprecedented insights for the realization of bottom-up nanotechnology for next-generation nanodevices on base of 2DNMs. This NSERC DG program also represents a pioneering effort in Canada to apply the integrated computational materials engineering (ICME) to innovate nanotechnology. A number of high quality personnel (HQP) will be trained. Through the training, they will master a broad spectrum of ICME tools and become experts in the field of computational materials science, constituting an invaluable group of talents for employment by Canadian industries and academia.

由于其独特而卓越的物理和电子特性，二维（2D）材料开辟了传统三维（3D）材料所不具备的新的物理类别，为纳米技术带来了前所未有的可能性，并吸引了全世界的巨大兴趣。 然而，大规模高质量制造和精确材料操控的困难严重制约了二维材料的应用。 为了应对上述挑战，NSERC 发现补助金 (DG) 计划建议探索新颖的设计路线，以直接转变 2D 材料或将其与 3D 纳米材料整合成混合 2D-3D 纳米结构。这种混合纳米结构保留了其二维组件的许多独特特性，同时提供了块体形式以方便在设备设计中的操作和结合。 同时，它们还可以作为一种有效的手段来简化外部场（例如电场和应变场）的应用，以设计二维材料的特性，为可调谐纳米器件的设计提供一条途径。 采用涉及多种模拟和建模技术的多尺度计算方法，将严格研究几种具有代表性的混合 2D-3D 纳米结构。同时，基于物理的材料建模和模拟将与机器学习框架相结合，以加速混合2D-3D纳米结构的探索和设计。拟议的 NSERC DG 计划牢固地建立在我对 2D 纳米材料的强大研究活动的基础上，这些活动很大程度上是由我当前的 NSERC DG（2012-2017 年）促成的。 我在这些活动中积累的知识、理解和计算工具是宝贵的资产，将在很大程度上适用于这个 DG 项目，使我处于一个完美的位置来解决拟议的研究。 预期的研究成果将为基于 2DNM 的下一代纳米器件实现自下而上的纳米技术提供前所未有的见解。该 NSERC DG 项目也代表了加拿大应用综合计算材料工程 (ICME) 创新纳米技术的开创性努力。 培养一批高素质人才（HQP）。 通过培训，他们将掌握广泛的ICME工具，成为计算材料科学领域的专家，成为加拿大工业界和学术界就业的宝贵人才群体。