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CAREER: Scalable Manufacturing of Hierarchical Nanostructures by Acoustically Modulated Emulsion Technique for Next Generation Renewable Energy Applications

CAREER: Scalable Manufacturing of Hierarchical Nanostructures by Acoustically Modulated Emulsion Technique for Next Generation Renewable Energy Applications
职业:通过声学调制乳液技术大规模制造分层纳米结构,用于下一代可再生能源应用
批准号:
1752378
负责人:
Shan Hu
金额:
$50.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-03-01 至 2024-08-31

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中文摘要
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英文摘要
Assembling nano building blocks into hierarchical structures can produce novel materials with unprecedented performance and functionalities, especially for next-generation renewable energy applications, including high-capacity batteries and high-efficiency solar cells, thus securing the energy future and prosperity of the nation. Existing methods to manufacture hierarchical nanostructures with long-range order require the use of templates that are limited in terms of fabrication scalability, cost, and time. They also lag behind on generating controlled composition variations in three-dimensional structures. This award supports fundamental research to produce needed knowledge for the study of a facile process to generate scalable and reconfigurable three-dimensional templates for the directed assembly of hierarchical nanostructures with rationally designed structure, topology, composition, and long-range order. This research promotes scientific understanding of the self-assembly process and provides strategies to direct the assembly by engineering the environment. Since assembly process is common in nature, e.g., living cells assemble into functional organs following a hierarchical order, knowledge from this research contributes to the understanding of life and life's engineering, which impacts the NSF Big Idea of 'Understanding the Rules of Life'. The multi-disciplinary research, involving acoustics, fluid dynamics, materials science and manufacturing, provides unique training and research opportunities to undergraduate and graduate students. The project involves community college students, especially, those from under-represented minorities, in research and help achieve academic success in science and engineering.The assembly of hierarchical nanostructures directed by acoustically-modulated emulsion can overcome several limitations existing assembly methods have, including disordered structures in long range, high cost, lengthy time, low scalability, and limited control of composition and anisotropy. However, fundamental scientific barriers are yet to be overcome to fully exploit the application potential of hierarchical nanostructures. This research is to fill the knowledge gap on the dynamics of nanoparticles and nanoparticle-loaded droplets in the Pickering emulsion system when subjected to a standing acoustic field. The project performs multi-scale molecular dynamics and finite element simulation, coupled with experimental validation, to investigate the dynamics of nanoparticles and emulsion droplets and delineate the effects of key process variables. Based on the fundamental studies, acoustically-modulated emulsion systems are designed and developed to manufacture a set of rationally designed metal oxide hierarchical nanostructures with structural, topological and compositional anisotropy in both nano- and micro- scales. Using titanium dioxide-based dye sensitized solar cell as a model device, the correlation of nano- and micro- scale structural and compositional anisotropy with the macroscale material properties and device performances are established.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.
期刊论文(2)
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会议论文
Structuring electrodes via acoustic-field-assisted particle patterning for enhanced performance of lithium-ion batteries
通过声场辅助颗粒图案化构建电极以增强锂离子电池的性能
DOI: 10.1039/d3ta01180a
发表时间: 2023
期刊: Journal of Materials Chemistry A
影响因子: 11.9
作者: [Zhang, Yifan, Shahriar, M., Hu, Shan]
通讯作者: Hu, Shan
Physics-Based Probabilistic Prognostics for Battery Health Management
  • 批准号:
    2015710
  • 项目类别:
    Standard Grant
  • 资助金额:
    $38.48万
  • 财政年份:
    2020
  • 负责人:
    Shan Hu
  • 依托单位:
Collaborative Research: Multi-functional and Multi-Material Additive Nanomanufacturing: Acoustic Field-Assisted Stereolithography (AFS)
  • 批准号:
    1663509
  • 项目类别:
    Standard Grant
  • 资助金额:
    $14.89万
  • 财政年份:
    2017
  • 负责人:
    Shan Hu
  • 依托单位:
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis