Collaborative Research: NanoMine: Data Driven Discovery for Nanocomposites
Collaborative Research: NanoMine: Data Driven Discovery for Nanocomposites
批准号:
1310318
负责人:
Linda Schadler
金额:
$12.0万
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
项目状态:
已结题
起止时间:
2013-09-15 至 2016-08-31
中文摘要
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英文摘要
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.
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Residual Stress in Thermal Spray Coatings
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