Collaborative Research: NanoMine: Data Driven Discovery for Nanocomposites
合作研究:NanoMine:数据驱动的纳米复合材料发现
基本信息
- 批准号:1310292
- 负责人:
- 金额:$ 24万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2013
- 资助国家:美国
- 起止时间:2013-09-15 至 2017-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Technical AbstractIn the past 15 years, research into nanoreinforced polymers has exploded, providing numerous examples of property enhancements ranging from altered thermal, mechanical, electrical, diffusion, optical and other properties. The amount of experimental data and simulation data, compounded with the data on the individual constituent phase materials is staggering. At the same time, while some mechanistic principles underlying property changes have been slowly uncovered, our ability to both deeply understand the underlying principles and to design new nanostructured polymers with desired properties from known processing steps is severely limited by the lack of integration of the information. To determine the type of property changes that have been observed requires manual searching of online journal databases, full reading of the articles, and manual accumulation and then synthesis of the information. This approach ensures that many relevant papers and articles are overlooked and allows only rudimentary synthesis of data and understanding of the processing-structure-property relationships. The birth of the materials genome concept provides a new paradigm for developing understanding of materials and designing new material concepts. In this research project, we tackle this challenge in the domain of polymer nanocomposites. While the materials genome approach has had some success in the metals field, the polymers area is considerably less developed and no resources exist for nanocomposite systems. Yet with the infinite design space available to polymer nanocomposites, it is a prime system for a new data driven approach. The Intellectual Merit of the work is application of materials genome concepts to the complex material system of polymer nanocomposites, with the goal of uncovering the processing-structure-property relationships. The overarching framework is to consider the material response as a function of processing conditions, constituents, interactions and morphology. Specific accomplishments include 1) development of a data resource (NanoMine) for housing and exchange of polymer nanocomposite data, 2) development of reduced descriptor sets to characterize data and quantify structure, and development of new data mining methods to enable discovery of underlying material physics, 3) integration of simulation tools to augment experimental data and enable exploration of design concepts. The Broader Impacts of the work are the NanoMine data resource itself, the new data-driven approach for materials understanding and discovery, and through use of these tools the ability to make deeper connections between processing, resulting material morphology and properties. The creation of an open-source, freely accessible data resource will provide not only a fast and easy source of information, but will also link researchers together in new ways. The data driven approach applied to this one system of nanocomposites, will provide strategies that can be extended to other material systems, greatly extending its influence. We will also integrate research and education through interdisciplinary graduate education including a special project based course. We will include undergraduates in our research program. This cadre of graduate and undergraduate students will have an interdisciplinary approach to materials discovery. We will also reach out to the broader community through NU and RPI High School outreach days (such as Design Your Future Day and Career Day for Girls) and teach them about Materials Design and data driven research.Non-technicalAbstractDevelopment of nanoparticle reinforced polymers in the past 15 years has created new materials with extraordinary properties - such as conducting yet transparent plastics, tennis balls that retain their bounce longer, and stiffer, stronger structural plastics for cars and airplanes. Yet the development of these advanced new materials has been very slow due to lack of integrated information, both experimental data and simulation tools. Currently, understanding the state of the field requires manual searching of online journal databases, full reading of the articles, and manual accumulation and then synthesis of the information. No resources yet exist for assembling the data, nor do tools exist to allow assembled data to be effectively mined for correlations, much less to enable rapid design of new materials. In this research, we will develop a data resource (NanoMine) for housing and exchange of polymer nanocomposite data and development of new data mining methods to enable discovery of underlying material physics. We will integrate of simulation tools to augment experimental data and enable exploration of design concepts. The creation of an open-source, freely accessible data resource will provide a fast and easy source of information, and will enable both fundamental new understanding of materials as well as much more efficient material design. The data driven approach applied to this one system of nanocomposites, will provide strategies that can be extended to other material systems, greatly extending its influence. We will also integrate research and education in several ways from K-12 through to practicing engineers.
技术摘要在过去的15年里,对纳米增强聚合物的研究已经爆炸,提供了许多性能增强的例子,从改变热,机械,电,扩散,光学和其他性能。实验数据和模拟数据的数量,以及各个组成相材料的数据是惊人的。与此同时,虽然一些机械原理的基本性质的变化已经慢慢发现,我们的能力,既深刻理解的基本原则,并设计新的纳米结构的聚合物与所需的性能从已知的加工步骤是严重限制了缺乏整合的信息。为了确定已经观察到的性质变化的类型,需要手动搜索在线期刊数据库,充分阅读文章,以及手动积累然后综合信息。这种方法确保了许多相关的论文和文章被忽略,只允许对数据进行初步的综合和对加工-结构-性质关系的理解。材料基因组概念的诞生为发展对材料的理解和设计新的材料概念提供了一个新的范例。在这个研究项目中,我们在聚合物纳米复合材料领域解决了这一挑战。虽然材料基因组方法在金属领域取得了一些成功,但聚合物领域的开发程度相当低,并且没有纳米复合材料系统的资源。然而,由于聚合物纳米复合材料具有无限的设计空间,它是一种新的数据驱动方法的主要系统。这项工作的智力价值是将材料基因组概念应用于聚合物纳米复合材料的复杂材料系统,其目标是揭示加工-结构-性能关系。总体框架是考虑材料响应作为加工条件,成分,相互作用和形态的函数。具体成果包括:1)开发数据资源(NanoMine),用于存储和交换聚合物纳米复合材料数据; 2)开发简化描述符集,用于表征数据和量化结构;以及开发新的数据挖掘方法,以发现潜在的材料物理学; 3)集成模拟工具,以增加实验数据并探索设计概念。这项工作的更广泛影响是NanoMine数据资源本身,材料理解和发现的新数据驱动方法,以及通过使用这些工具在加工、所得材料形态和性质之间建立更深层次联系的能力。创建一个开放源代码、可免费获取的数据资源不仅将提供一个快速、方便的信息来源,而且还将以新的方式将研究人员联系在一起。应用于这一纳米复合材料系统的数据驱动方法将提供可扩展到其他材料系统的策略,大大扩展其影响力。我们还将通过跨学科的研究生教育,包括一个特殊的项目为基础的课程整合研究和教育。我们的研究计划将包括本科生。这个研究生和本科生的干部将有一个跨学科的方法来发现材料。我们还将通过NU和RPI高中外展日接触更广泛的社区(如设计你的未来日和女孩的职业日),并教他们材料设计和数据驱动的研究。非技术摘要在过去的15年里,纳米颗粒增强聚合物的发展创造了具有非凡性能的新材料-如导电但透明的塑料,保持更长反弹时间的网球,以及用于汽车和飞机的更硬、更强的结构塑料。然而,由于缺乏实验数据和模拟工具等综合信息,这些先进新材料的开发一直非常缓慢。目前,了解该领域的状态需要手动搜索在线期刊数据库,充分阅读的文章,并手动积累,然后综合的信息。目前还不存在用于组装数据的资源,也不存在允许有效挖掘组装数据的相关性的工具,更不用说快速设计新材料了。在这项研究中,我们将开发一个数据资源(NanoMine),用于存储和交换聚合物纳米复合材料数据,并开发新的数据挖掘方法,以发现潜在的材料物理学。我们将整合模拟工具,以增加实验数据,并使设计概念的探索。 创建一个开源的、可免费访问的数据资源将提供一个快速、简单的信息来源,并将使人们对材料有新的基本理解,以及更有效的材料设计。应用于这一纳米复合材料系统的数据驱动方法将提供可扩展到其他材料系统的策略,大大扩展其影响力。我们还将以多种方式整合研究和教育,从K-12到实践工程师。
项目成果
期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Whyis 2: An Open Source Framework for Knowledge Graph Development and Research
Whyis 2:知识图开发和研究的开源框架
- DOI:10.1007/978-3-031-33455-9_32
- 发表时间:2023
- 期刊:
- 影响因子:0
- 作者:McCusker, Jamie;McGuinness, Deborah L
- 通讯作者:McGuinness, Deborah L
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Lynda Brinson其他文献
Lynda Brinson的其他文献
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{{ truncateString('Lynda Brinson', 18)}}的其他基金
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DMREF/协作研究:加速未来纳米结构聚合物和复合材料系统设计的以数据为中心的方法
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