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

• 批准号: 1310318
• 负责人: Linda Schadler
• 金额: $ 12万
• 依托单位: Rensselaer Polytechnic Institute
• 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: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1310318&HistoricalAwards=false
• 关键词: Collaborative; Research; NanoMine; Data; Driven

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 15 年中，对纳米增强聚合物的研究呈爆炸式增长，提供了许多性能增强的例子，包括改变热性能、机械性能、电性能、扩散性能、光学性能和其他性能。实验数据和模拟数据的数量，加上各个组成相材料的数据是惊人的。与此同时，虽然特性变化背后的一些机械原理已经慢慢被揭示，但由于缺乏信息整合，我们深刻理解基本原理并从已知加工步骤设计具有所需特性的新型纳米结构聚合物的能力受到严重限制。 。要确定观察到的属性变化类型，需要手动搜索在线期刊数据库、充分阅读文章、手动积累然后综合信息。这种方法确保了许多相关论文和文章被忽视，并且只允许对数据进行基本的综合和对处理-结构-属性关系的理解。材料基因组概念的诞生为发展对材料的理解和设计新材料概念提供了新的范式。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，并且不存在用于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，它是新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，目的是揭示加工-结构-性能之间的关系。总体框架是将材料响应视为加工条件、成分、相互作用和形态的函数。具体成就包括 1) 开发用于存储和交换聚合物纳米复合材料数据的数据资源 (NanoMine)，2) 开发简化描述符集以表征数据和量化结构，以及开发新的数据挖掘方法以发现基础材料物理, 3) 集成仿真工具以增强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、用于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处理、所得材料形态和性能之间建立更深入联系的能力。创建开源、可免费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，从而大大扩展其影响力。我们还将通过跨学科研究生教育（包括基于特殊项目的课程）将研究和教育结合起来。我们将把本科生纳入我们的研究计划。这支研究生和本科生队伍将采用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（例如“设计你的未来日”和“女孩职业日”）接触更广泛的社区，并向他们传授材料设计和数据驱动的研究知识。过去 15 年纳米颗粒增强聚合物的发展多年来，人们创造出了具有非凡性能的新材料，例如导电透明塑料、弹跳时间更长的网球，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，了解该领域的现状需要手动检索在线期刊数据库、充分阅读文章、手动积累并综合信息。目前还没有用于组装数据的资源，也没有工具可以有效地挖掘组装数据的相关性，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（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，以发现基础材料物理。我们将集成模拟工具来增强实验数据并探索设计概念。 创建开源、可免费访问的数据资源将提供快速、简单的信​​息源，并将实现对材料的基本新理解以及更高效的材料设计。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，从而大大扩展其影响力。我们还将通过多种方式整合研究和教育，从 K-12 一直到执业工程师。