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:1310318
- 负责人:
- 金额:$ 12万
- 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 2016-08-31
- 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 alsointegrate 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 tomaterials 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.Development 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 andairplanes. 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 ofan 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年中,对纳米素有助的聚合物的研究爆炸了,提供了许多属性增强的例子,包括改变的热,机械,电气,扩散,光学,光学和其他特性。实验数据和仿真数据的量与单个组成相材料的数据相复杂化。同时,虽然已经逐渐发现了属性变化的一些机械原理,但我们既深入了解潜在的原理又有能力,并设计了具有已知处理步骤所需属性的新纳米结构聚合物,这受到信息的不足而受到信息的整合,这受到了严格的限制。 。为了确定已观察到的属性变化的类型,需要手动搜索在线期刊数据库,全面阅读文章以及手动积累,然后综合信息。这种方法可确保许多相关的论文和文章被忽略,并且只允许对数据的基本综合以及对处理结构 - 统治关系的理解。材料基因组概念的诞生为发展材料的理解和设计新材料概念提供了新的范式。在该研究项目中,我们在聚合物纳米复合材料的领域中应对这一挑战。尽管材料基因组方法在金属领域取得了一定的成功,但聚合物区域的发达幅度大大降低,纳米复合材料系统不存在资源。然而,借助可用于聚合物纳米复合材料的无限设计空间,它是一种新的数据驱动方法的主要系统。这项工作的智力优点是将材料基因组概念的应用到聚合物纳米复合材料的复杂材料系统中,目的是揭示加工结构 - 培训关系。总体框架是将材料响应视为处理条件,成分,相互作用和形态的函数。具体成就包括1)开发用于外壳和聚合物纳米复合数据的数据资源(纳米胺),2)开发减少的描述符集以表征数据和量化结构,并开发新的数据挖掘方法,以启用潜在的材料物理学,3)模拟工具的集成以增强实验数据并实现设计概念的探索。工作的更广泛的影响是纳米胺数据资源本身,新的数据驱动的材料理解和发现方法,以及使用这些工具,能够在处理之间建立更深的连接,产生的材料形态和属性。创建开源,可自由访问的数据资源不仅将提供快速,简单的信息来源,而且还将以新的方式将研究人员链接在一起。数据驱动的方法应用于该纳米复合材料系统,将提供可以扩展到其他材料系统的策略,从而大大扩展其影响力。我们还将通过跨学科的研究生教育(包括基于特殊项目的课程)来融合研究和教育。我们将在我们的研究计划中包括本科生。这位研究生和本科生的干部将有一种跨学科的方法。我们还将通过NU和RPI高中宣传日(例如,为女孩设计您的未来日和职业日)与更广泛的社区联系,并向他们传授有关材料设计和数据驱动研究的知识。多年来,已经创造了具有非凡特性的新材料 - 例如进行透明塑料,网球可以保持更长的弹跳,并为汽车和空气板上的更坚固,更坚固的结构性塑料。然而,由于缺乏实验数据和仿真工具的集成信息,这些高级新材料的开发非常慢。当前,了解该领域的状态需要手动搜索在线期刊数据库,对文章的完整阅读以及手动积累,然后综合信息。目前尚无资源来组装数据,也不存在工具可以有效地开采组装数据以进行相关性,更不用说能够快速设计新材料了。在这项研究中,我们将开发一种数据资源(纳米胺),用于外壳和聚合物纳米复合数据的交换以及开发新的数据挖掘方法,以便发现潜在的材料物理学。我们将集成模拟工具,以增强实验数据并能够探索设计概念。 自由访问的数据资源创建的开源,将提供快速简便的信息来源,并可以使对材料的基本了解以及更有效的材料设计。数据驱动的方法应用于该纳米复合材料系统,将提供可以扩展到其他材料系统的策略,从而大大扩展其影响力。我们还将通过从K-12到执业工程师的几种方式整合研究和教育。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Linda Schadler其他文献
Linda Schadler的其他文献
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{{ truncateString('Linda Schadler', 18)}}的其他基金
DMREF/Collaborative Research: Accelerated Discovery of Sustainable Bioplastics: Automated, Tunable, Integrated Design, Processing and Modeling
DMREF/合作研究:加速可持续生物塑料的发现:自动化、可调、集成设计、加工和建模
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2323977 - 财政年份:2023
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0218716 - 财政年份:2003
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$ 12万 - 项目类别:
Standard Grant
Support for a Joint TMS The Minerals, Metals, and Materials Society/Society of Plastics Engineers Conference on Polymer Materials
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0107879 - 财政年份:2001
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9800128 - 财政年份:1998
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9850825 - 财政年份:1998
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GOALI: Mechanical and Molecular Behavior of Nanoparticulate/Polymer Composites
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9871894 - 财政年份:1998
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$ 12万 - 项目类别:
Standard Grant
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