FMRG: Artificial Intelligence Driven Cybermanufacturing of Quantum Material Architectures
FMRG:人工智能驱动的量子材料架构网络制造
基本信息
- 批准号:2036359
- 负责人:
- 金额:$ 375万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2020
- 资助国家:美国
- 起止时间:2020-09-01 至 2022-09-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Quantum material architectures consist of graphene and other two-dimensional materials, which, when stacked in precise three-dimensional architectures, exhibit unique and tunable mechanical, electrical, optical, and magnetic properties. These three-dimensional architectures have broad potential applications and are highly promising components for microchips, batteries, antennas, chemical and biological sensors, solar-cells and neural interfaces. However, currently, due to the lack of fundamental understanding of the physical and chemical processes, it has been difficult to control or scale the manufacturing of these three-dimensional structures. This Future Manufacturing (FM) grant is to develop a transformative Future Manufacturing platform for quantum material architectures using a cybermanufacturing approach, which combines artificial intelligence, robotics, multiscale modeling, and predictive simulation for the automated and parallel assembly of multiple two-dimensional materials into complex three-dimensional structures. This platform enables future production of high-quality, custom quantum material architectures for broad and critical applications, supporting continued U.S. leadership in technology development. The research in cybermanufacturing is integrated with innovative educational programs for cross-disciplinary training of scientists and engineers, especially, women and underrepresented minorities, in advanced manufacturing, artificial intelligence and quantum structures, as well as engaging the public in future manufacturing concepts. This grant research focuses on a fundamentally new method for scalable manufacturing of 3D quantum material architectures or van der Waals heterostructures (vdWHs) using microfluidic assembly. vdWHs are composed of unlimited combinations of atomically thin layers and exhibit interesting emerging functionalities. The key process innovation is precision microfluidic folding of 2D materials, which has been demonstrated at a small-scale. This method has promising potential to scale up to wafer scale, with no fundamental limit on scaling. A second key innovation is embedding artificial intelligence (AI) across all aspects of the manufacturing process flow, from low-level precision control, to automated characterization, to high-level structure predictions. Predictive simulation and visualization tools combined with in situ spectroscopy allow real-time analysis of atomic-scale physical and chemical processes and their control. Moreover, parallel self-assembly in microfluidic environments is investigated as a pathway toward truly scalable manufacturing. The expected outcome of the award is to produce superlattices consisting of tens of atomic layers with precisely engineered stacking order and alignment, leading to fundamentally new custom quantum material architectures with electronic and photonic properties impossible to obtain from conventional material architectures. This research advances fundamental knowledge in material physics, nanoscale electronics and photonic science leading the way to manufacturing of future devices, such as twistronics. A key outcome is an AI-driven, robotics-controlled cybermanufacturing microfluidic platform that is capable of manufacturing complex structures for emerging quantum and other device applications.This Future Manufacturing research grant is supported by the following Divisions in the Engineering Directorate: Civil, Mechanical and Manufacturing Innovation; Electrical, Communications and Cyber Systems; and Engineering Education and Centers; and the following Divisions in the Mathematical and Physical Sciences: Materials Research; Chemistry; and Mathematical Sciences.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.
量子材料架构由石墨烯和其他二维材料组成,当堆叠在精确的三维架构中时,表现出独特的可调机械,电学,光学和磁性。这些三维结构具有广泛的潜在应用,并且是微芯片、电池、天线、化学和生物传感器、太阳能电池和神经接口的非常有前途的组件。然而,目前,由于缺乏对物理和化学过程的基本理解,难以控制或规模化制造这些三维结构。这项未来制造(FM)拨款将使用网络制造方法为量子材料架构开发一个变革性的未来制造平台,该方法将人工智能,机器人技术,多尺度建模和预测模拟相结合,用于自动化和并行组装多种二维材料到复杂的三维结构中。该平台使未来能够为广泛和关键的应用生产高质量的定制量子材料架构,支持美国在技术开发方面的持续领导地位。网络制造的研究与创新的教育计划相结合,对科学家和工程师进行跨学科培训,特别是女性和代表性不足的少数民族,在先进制造,人工智能和量子结构方面,以及让公众参与未来的制造概念。这项研究的重点是一种全新的方法,用于使用微流体组装可规模化制造3D量子材料架构或货车德瓦尔斯异质结构(vdWHs)。vdWHs由原子级薄层的无限组合组成,并表现出有趣的新兴功能。 关键的工艺创新是2D材料的精密微流体折叠,这已经在小规模上得到了证明。这种方法具有扩大到晶片规模的潜力,对缩放没有根本限制。第二个关键创新是将人工智能(AI)嵌入制造工艺流程的各个方面,从低精度控制到自动表征,再到高级结构预测。预测模拟和可视化工具与原位光谱相结合,可以实时分析原子级物理和化学过程及其控制。 此外,研究了微流体环境中的并行自组装作为实现真正可扩展制造的途径。该奖项的预期成果是生产由数十个原子层组成的超晶格,这些原子层具有精确设计的堆叠顺序和排列,从而产生全新的定制量子材料架构,具有传统材料架构无法获得的电子和光子特性。这项研究推进了材料物理学,纳米电子学和光子科学的基础知识,引领了未来器件的制造,如双电子学。一个关键的成果是一个人工智能驱动的,机器人控制的网络制造微流体平台,能够为新兴的量子和其他设备应用制造复杂的结构。这个未来制造研究基金由工程局的以下部门支持:土木,机械和制造创新;电气,通信和网络系统;和工程教育和中心;该奖项反映了NSF的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
项目成果
期刊论文数量(10)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Thickness dependence of dielectric constant of alumina films based on first-principles calculations
基于第一性原理计算的氧化铝薄膜介电常数的厚度依赖性
- DOI:10.1063/5.0106721
- 发表时间:2022
- 期刊:
- 影响因子:4
- 作者:Fukushima, Shogo;Kalia, Rajiv K.;Nakano, Aiichiro;Shimojo, Fuyuki;Vashishta, Priya
- 通讯作者:Vashishta, Priya
Recent Advances in Artificial Intelligence for Wireless Internet of Things and Cyber–Physical Systems: A Comprehensive Survey
- DOI:10.1109/jiot.2022.3170449
- 发表时间:2022-08
- 期刊:
- 影响因子:10.6
- 作者:Babajide A. Salau;A. Rawal;D. Rawat
- 通讯作者:Babajide A. Salau;A. Rawal;D. Rawat
Mechanical behavior of ultralight nickel metamaterial
- DOI:10.1063/5.0031806
- 发表时间:2021-02
- 期刊:
- 影响因子:4
- 作者:P. Rajak;A. Nakano;P. Vashishta;R. Kalia
- 通讯作者:P. Rajak;A. Nakano;P. Vashishta;R. Kalia
EZFF: Python library for multi-objective parameterization and uncertainty quantification of interatomic forcefields for molecular dynamics
EZFF:用于分子动力学原子间力场的多目标参数化和不确定性量化的 Python 库
- DOI:10.1016/j.softx.2021.100663
- 发表时间:2021
- 期刊:
- 影响因子:3.4
- 作者:Krishnamoorthy, Aravind;Mishra, Ankit;Kamal, Deepak;Hong, Sungwook;Nomura, Ken-ichi;Tiwari, Subodh;Nakano, Aiichiro;Kalia, Rajiv;Ramprasad, Rampi;Vashishta, Priya
- 通讯作者:Vashishta, Priya
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Radhika Nagpal其他文献
Harvard School of Engineering and Applied Sciences
哈佛大学工程与应用科学学院
- DOI:
- 发表时间:
2007 - 期刊:
- 影响因子:0
- 作者:
Radhika Nagpal;Salil P. Vadhan;Ravin Bhatt - 通讯作者:
Ravin Bhatt
Collective Bayesian Decision-Making in a Swarm of Miniaturized Robots for Surface Inspection
用于表面检测的微型机器人群中的集体贝叶斯决策
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Thiemen Siemensma;Darren Chiu;Sneha Ramshanker;Radhika Nagpal;Bahar Haghighat - 通讯作者:
Bahar Haghighat
Optimization and Evaluation of a Multi Robot Surface Inspection Task Through Particle Swarm Optimization
通过粒子群优化的多机器人表面检测任务的优化和评估
- DOI:
- 发表时间:
- 期刊:
- 影响因子:0
- 作者:
Darren Chiu;Radhika Nagpal;Bahar Haghighat - 通讯作者:
Bahar Haghighat
Self-Organizing Shape and Pattern: From Cells to Robots
- DOI:
- 发表时间:
2006 - 期刊:
- 影响因子:0
- 作者:
Radhika Nagpal - 通讯作者:
Radhika Nagpal
Optimization and Evaluation of Multi Robot Surface Inspection Through Particle Swarm Optimization
通过粒子群优化的多机器人表面检测优化与评估
- DOI:
- 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Darren Chiu;Radhika Nagpal;Bahar Haghighat - 通讯作者:
Bahar Haghighat
Radhika Nagpal的其他文献
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{{ truncateString('Radhika Nagpal', 18)}}的其他基金
FMRG: Artificial Intelligence Driven Cybermanufacturing of Quantum Material Architectures
FMRG:人工智能驱动的量子材料架构网络制造
- 批准号:
2240407 - 财政年份:2022
- 资助金额:
$ 375万 - 项目类别:
Standard Grant
Collective Robotics for Life Scientists
生命科学家的集体机器人
- 批准号:
1353236 - 财政年份:2014
- 资助金额:
$ 375万 - 项目类别:
Standard Grant
EMT/BSSE Programmable Self-Adaptation: A Bio-inspired Approach To Multi-agent Robotic Systems
EMT/BSSE 可编程自适应:多智能体机器人系统的仿生方法
- 批准号:
0829745 - 财政年份:2008
- 资助金额:
$ 375万 - 项目类别:
Standard Grant
CAREER: Self-Organizing Systems: Engineering and Understanding Robust Collective Behavior
职业:自组织系统:工程和理解鲁棒的集体行为
- 批准号:
0643898 - 财政年份:2007
- 资助金额:
$ 375万 - 项目类别:
Continuing Grant
BIC: Programmable Myriads: self-assembling cellular robots, inspired by tissue morphogenesis
BIC:Programmable Myriads:受组织形态发生启发的自组装细胞机器人
- 批准号:
0523676 - 财政年份:2005
- 资助金额:
$ 375万 - 项目类别:
Continuing Grant
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