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Collaborative Research: Framework: Data: HDR: Nanocomposites to Metamaterials: A Knowledge Graph Framework

Collaborative Research: Framework: Data: HDR: Nanocomposites to Metamaterials: A Knowledge Graph Framework
合作研究:框架:数据:HDR:纳米复合材料到超材料:知识图框架
批准号:
1835782
负责人:
Wei Chen
金额:
$59.98万
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:
2018-11-01 至 2024-09-30

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中文摘要
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英文摘要
A team of experts from four universities (Duke, RPI, Caltech and Northwestern) creates an open source data resource for the polymer nanocomposites and metamaterials communities. A broad spectrum of users will be able to query the system, identify materials that may have certain characteristics, and automatically produce information about these materials. The new capability (MetaMine) is based on previous work by the research team in nanomaterials (NanoMine). The effort focuses upon two significant domain problems: discovery of factors controlling the dissipation peak in nanocomposites, and tailored mechanical response in metamaterials motivated by an application to personalize running shoes. The project will significantly improve the representation of data and the robustness with which user communities can identify promising materials applications. By expanding interaction of the nanocomposite and metamaterials communities with curated data resources, the project enables new collaborations in materials discovery and design. Strong connections with the National Institute of Standards and Technology (NIST), the Air Force Research Laboratory (AFRL), and Lockheed Martin facilitate industry and government use of the resulting knowledge base. The project develops an open source Materials Knowledge Graph (MKG) framework. The framework for materials includes extensible semantic infrastructure, customizable user templates, semi-automatic curation tools, ontology-enabled design tools and custom user dashboards. The work generalizes a prototype data resource (NanoMine) previously developed by the researchers, and demonstrates the extensibility of this framework to metamaterials. NanoMine enables annotation, organization and data storage on a wide variety of nanocomposite samples, including information on composition, processing, microstructure and properties. The extensibility will be demonstrated through creation of a MetaMine module for metamaterials, parallel to the NanoMine module for nanocomposites. The frameworks will allow for curation of data sets and end-user discovery of processing-structure-property relationships. The work supports the Materials Genome Initiative by creating an extensible data ecosystem to share and re-use materials data, enabling faster development of materials via robust testing of models and application of analysis tools. The capability will be compatible with the NIST Material Data Curator System, and the team also engages both AFRL and Lockheed Martin to facilitate industry and government use of the resulting knowledge base. This award by the Office of Advanced Cyberinfrastructure is jointly supported by the Division of Materials Research within the NSF Directorate for Mathematical and Physical 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.
期刊论文(15)
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会议论文
DOI: 10.1115/1.4044257
发表时间: 2019-09
期刊: Journal of Mechanical Design
影响因子: 3.3
作者: [R. Bostanabad;Yu-Chin Chan;Liwei Wang;P. Zhu;Wei Chen]
通讯作者: R. Bostanabad;Yu-Chin Chan;Liwei Wang;P. Zhu;Wei Chen
DOI: 10.1115/1.4048629
发表时间: 2020-06
期刊: ArXiv
影响因子: --
作者: [Yu-Chin Chan;Faez Ahmed;Liwei Wang;Wei Chen]
通讯作者: Yu-Chin Chan;Faez Ahmed;Liwei Wang;Wei Chen
DOI: 10.1088/1361-6463/ab8b01
发表时间: 2020-04
期刊: Journal of Physics D: Applied Physics
影响因子: --
作者: [L. Schadler;L. Brinson;Wei Chen;R. Sundararaman;P. Gupta;Prajakta Prabhune;Akshay Iyer;Yixing Wang;Abhishek Shandilya]
通讯作者: L. Schadler;L. Brinson;Wei Chen;R. Sundararaman;P. Gupta;Prajakta Prabhune;Akshay Iyer;Yixing Wang;Abhishek Shandilya
t-METASET: Task-Aware Generation of Metamaterial Datasets by Diversity-Based Active Learning
t-METASET:通过基于多样性的主动学习生成超材料数据集的任务感知型
DOI: 10.1115/detc2022-87653
发表时间: 2022
期刊: American Society of Mechanical Engineers
影响因子: --
作者: [Lee, Doksoo, Chan, Yu-Chin, Chen, Wei, Wang, Liwei, Chen, Wei]
通讯作者: Chen, Wei
11
    CAREER: First-principles Predictive Understanding of Chemical Order in Complex Concentrated Alloys: Structures, Dynamics, and Defect Characteristics
    • 批准号:
      2415119
    • 项目类别:
      Continuing Grant
    • 资助金额:
      $50.0万
    • 财政年份:
      2024
    • 负责人:
      Wei Chen
    • 依托单位:
    Collaborative Research: EAGER: SSMCDAT2023: Data-driven Predictive Understanding of Oxidation Resistance in High-Entropy Alloy Nanoparticles
    • 批准号:
      2334385
    • 项目类别:
      Standard Grant
    • 资助金额:
      $10.8万
    • 财政年份:
      2023
    • 负责人:
      Wei Chen
    • 依托单位:
    BRITE Fellow: AI-Enabled Discovery and Design of Programmable Material Systems
    • 批准号:
      2227641
    • 项目类别:
      Standard Grant
    • 资助金额:
      $99.98万
    • 财政年份:
      2023
    • 负责人:
      Wei Chen
    • 依托单位:
    Collaborative Research: I-AIM: Interpretable Augmented Intelligence for Multiscale Material Discovery
    • 批准号:
      2404816
    • 项目类别:
      Standard Grant
    • 资助金额:
      $38.79万
    • 财政年份:
      2023
    • 负责人:
      Wei Chen
    • 依托单位:
    国内基金
    海外基金
    Research on Quantum Field Theory without a Lagrangian Description
    • 批准号:
      24ZR1403900
    • 项目类别:
      省市级项目
    • 资助金额:
      --
    • 批准年份:
      2024
    • 负责人:
      SATOSHI NAWATA
    • 依托单位:
    Cell Research
    Cell Research
    Cell Research (细胞研究)