Network for Computational Nanotechnology - Hierarchical nanoMFG Node
Network for Computational Nanotechnology - Hierarchical nanoMFG Node
批准号:
1720701
负责人:
Elif Ertekin
金额:
$400.0万
依托单位国家:
美国
项目类别:
Cooperative Agreement
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-09-01 至 2023-08-31
中文摘要
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英文摘要
To become economically viable and accessible at large scales, nanomanufacturing critically depends on achieving control over complex process parameters and a thorough understanding of the underlying driving scientific phenomena. The goal of this collaborative effort will be to establish a Hierarchical Nanomanufacturing Node for computational tools development aimed at creating smart, model- and data-driven nanomanufacturing. By leveraging emerging advances in computing and cyberinfrastructure, the vision of this node is to simulate every step of the manufacturing process of a nano-enabled product. Simulation tools developed will be optimized and tested for utility by stakeholders including researchers in nanotechnology and related industrial sectors. In addition, the impact of this 5-year activity on the nanomanufacturing industry will be critically assessed. The node will be part of the established Network for Computational Nanotechnology (NCN) Cyber Platform. The mission of the nanoMFG Node is to be the engine for design, simulation, planning, and optimization of highly relevant nano-manufacturing growth and patterning processes. Both working with the existing cyber framework (nanoHUB) and facilitating development of human resources that will broadly impact nanomanufacturing and nanotechnology are essential to this mission. To help achieve this mission, computational tools for nanomanufacturing aimed at multiscale theory, modeling, and simulation (TM&S) will be developed and broadly disseminated. The intellectual merit of this 5-year activity is the development of nanomanufacturing simulation tools, validated by experimental data, and integrated with data-driven uncertainty quantification. The framework for the effort is based on a layered computational tool infrastructure comprising the creation of the following: (1) nanoscale transport phenomena models, (2) process models, (3) uncertainty quantification framework, (4) application and empirical validation of process models, (5) tools for multiscale transport phenomena, and (6) tools for nanoscale self-assembly. Beyond nanomanufacturing, the burgeoning field of nanoscience will significantly benefit from free, open-source computational tools that have been validated by experiments. The collaboration will bring researchers, educators, industries, national labs, and high schools together to form a cohesive framework to advance nanoscience and resulting nanotechnologies, promote STEM education, and build the human resources necessary to make nanomanufacturing an economically viable engine for society. This will have several impacts on realizing the varied promises promulgated by nanotechnology as it pertains to: accelerating the high-tech economy, improving human health, and positively impacting an array of manufacturing industry domains including aviation, automotive, agricultural, construction machinery, and many others. Efforts to promote workforce diversification are tightly interwoven into this effort to both help increase participation from underrepresented groups and institutions and also to add to the richness of the tools being developed. Fellowships will be competitively awarded annually to help train the next generation workforce not only on simulation and modeling tool development but also on the value of community building and sharing of resources and expertise, thus building a nationwide innovation ecosystem for economic development of the U.S. and its leadership worldwide.
期刊论文(6)
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DOI:
10.1021/acsanm.2c02059
发表时间:
2022-07-21
期刊:
ACS APPLIED NANO MATERIALS
影响因子:
5.9
作者:
[Manjarrez, Adrian, Zhou, Kai, Cai, Lili]
通讯作者:
Cai, Lili
Crowd-Sourced Data and Analysis Tools for Advancing the Chemical Vapor Deposition of Graphene: Implications for Manufacturing
促进石墨烯化学气相沉积的众包数据和分析工具:对制造业的影响
DOI:
10.1021/acsanm.0c02018
发表时间:
2020
期刊:
ACS Applied Nano Materials
影响因子:
5.9
作者:
[Schiller, Joshua A., Toro, Ricardo, Shah, Aagam, Surana, Mitisha, Zhang, Kaihao, Robertson, Matthew, Miller, Kristina, Cruse, Kevin, Liu, Kevin, Seong, Bomsaerah]
通讯作者:
Seong, Bomsaerah
Optical reflectance imaging reveals interlayer coupling in mechanically stacked MoS 2 and WS 2 bilayers
光学反射成像揭示了机械堆叠的 MoS 2 和 WS 2 双层中的层间耦合
DOI:
10.1364/oe.473397
发表时间:
2023
期刊:
Optics Express
影响因子:
3.8
作者:
[Nguyen, Vu, Li, Wan, Ager, Joel, Xu, Ke, Taylor, Hayden]
通讯作者:
Taylor, Hayden
DOI:
10.1016/j.mattod.2019.08.013
发表时间:
2020-04-01
期刊:
MATERIALS TODAY
影响因子:
24.2
作者:
[Yong, Keong, De, Subhadeep, Nam, SungWoo]
通讯作者:
Nam, SungWoo
Automated image segmentation of scanning electron microscopy images of graphene using U-Net Neural Network
使用 U-Net 神经网络对石墨烯扫描电子显微镜图像进行自动图像分割
DOI:
10.1016/j.mtcomm.2023.106127
发表时间:
2023
期刊:
Materials Today Communications
影响因子:
3.8
作者:
[Shah, Aagam, Schiller, Joshua A., Ramos, Isiah, Serrano, James, Adams, Darren K., Tawfick, Sameh, Ertekin, Elif]
通讯作者:
Ertekin, Elif
共 6 条
Travel Support for Workshop on Best Practices in Modeling Across Scales from Materials Discovery to Manufacturing; Arlington, Virginia; Summer 2023
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批准号:2315913
-
项目类别:Standard Grant
-
资助金额:$4.69万
-
财政年份:2023
-
负责人:Elif Ertekin
-
依托单位:
DMREF: Collaborative Research: Accelerating Thermoelectric Materials Discovery via Dopability Predictions
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批准号:1729149
-
项目类别:Standard Grant
-
资助金额:$32.0万
-
财政年份:2017
-
负责人:Elif Ertekin
-
依托单位:
CAREER: Designing Functionality Into Two-Dimensional Materials Through Defects, Topology, and Disorder
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批准号:1555278
-
项目类别:Continuing Grant
-
资助金额:$47.26万
-
财政年份:2016
-
负责人:Elif Ertekin
-
依托单位:
DMREF: Discovery and Design of Magnetic Alloys by Simulation and Experiment
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批准号:1437106
-
项目类别:Standard Grant
-
资助金额:$67.38万
-
财政年份:2014
-
负责人:Elif Ertekin
-
依托单位:
国内基金
海外基金
Computational Methods for Analyzing Toponome Data
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批准号:60601030
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项目类别:青年科学基金项目
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资助金额:17.0万元
-
批准年份:2006
-
负责人:Axel Mosig
-
依托单位: