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NSF Convergence Accelerator Track D: A Community Resource for Innovation in Polymer Technology (CRIPT)

NSF Convergence Accelerator Track D: A Community Resource for Innovation in Polymer Technology (CRIPT)
NSF 融合加速器轨道 D:聚合物技术创新社区资源 (CRIPT)
批准号:
2134795
负责人:
Bradley Olsen
金额:
$500.0万
依托单位国家:
美国
项目类别:
Cooperative Agreement
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-10-01 至 2024-09-30

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中文摘要
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英文摘要
Polymer materials, ranging from clothing and personal protective equipment to construction materials and food packaging, are fundamental to providing for our basic needs for food, shelter, health, and transportation. However, developing new polymers for next-generation products takes decades, and we must move faster to remain competitive. To accelerate this process, this project is developing CRIPT, a polymer data ecosystem consisting of a web-based application and cloud database that allow polymer scientists to easily find, archive, and interact with complex polymer data. AI-driven chemistry tools and data-driven workflows within CRIPT will reduce the development time for polymer materials by an order of magnitude, creating a transformative impact on both the producers and buyers of the nearly $600 billion of polymers sold each year.Currently, searching among existing polymers is a daunting task because polymer data exists as small, disparate sets, making the navigation a complex process combining the harmonization of different data formats and the reconciliation of metadata, both of which currently require expert intervention. CRIPT offers a cloud database based on a new polymer-specific data model that simultaneously provides interoperability across different domains of polymer science and engineering, while retaining critical metadata that allows domain experts to correlate information across many independent records. A series of chemically-inspired AI innovations, including a chemistry-based query language, a graph-based schema preserving temporal structure in data, algorithms for automatic data validation, AI-human cooperative tools for data ingestion, and the integration of machines into the data ecosystem are also provided to add FAIR principles, trust in data, and ease of use to the system.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(6)
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科研奖励(0)
会议论文
DOI: 10.1039/d3dd00147d
发表时间: 2023
期刊: Digital Discovery
影响因子: --
作者: [Ludwig Schneider;Dylan Walsh;Bradley Olsen;J. D. de Pablo]
通讯作者: Ludwig Schneider;Dylan Walsh;Bradley Olsen;J. D. de Pablo
DOI: 10.1016/j.xcrp.2022.101126
发表时间: 2022-11-16
期刊: CELL REPORTS PHYSICAL SCIENCE
影响因子: 8.9
作者: [Deagen, Michael E., Walsh, Dylan J., Olsen, Bradley D.]
通讯作者: Olsen, Bradley D.
DOI: 10.1021/acs.macromol.3c00761
发表时间: 2023-09-06
期刊: MACROMOLECULES
影响因子: 5.5
作者: [Shi,Jiale, Rebello,Nathan J., Olsen,Bradley D.]
通讯作者: Olsen,Bradley D.
BigSMARTS: A Topologically Aware Query Language and Substructure Search Algorithm for Polymer Chemical Structures
BigSMARTS:一种用于聚合物化学结构的拓扑感知查询语言和子结构搜索算法
DOI: 10.1021/acs.jcim.3c00978
发表时间: 2023
期刊: Journal of Chemical Information and Modeling
影响因子: 5.6
作者: [Rebello, Nathan J., Lin, Tzyy-Shyang, Nazeer, Heeba, Olsen, Bradley D.]
通讯作者: Olsen, Bradley D.
RAPID: Collaborative Research: Augmenting Mucosal Gels with Associating Brush Polymers to Prevent COVID-19 Infection
NSF Convergence Accelerator Track D: A Community Resource for Innovation in Polymer Materials
Engineering a new family of consensus repeat proteins based on nucleoporins
Dynamics of Associative Polymers Revealed by Self-Diffusion
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