ITR - (ASE) - (sim): New Models and Simulations to Facilitate Developing Novel Nanocomposite Materials

ITR - (ASE) - (sim)：促进新型纳米复合材料开发的新模型和模拟

• 批准号: 0427239
• 负责人: Francis Starr
• 金额: $ 51万
• 依托单位: Wesleyan University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-09-15 至 2010-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0427239&HistoricalAwards=false
• 关键词: ITR; ASE; sim; New; Models

This award was made on a proposal submitted to the Division of Materials Research under the Information Technology Research solicitation NSF-04-012. Research activities covered by this award fall under the National Priority Area, "Advances in Science and Engineering," and the Technical Focus Area, "Innovation in Computational Modeling or Simulation in Research." The Divisions of Materials Research and Chemistry jointly support this award for computational research and education. The research is being done in collaborations with groups at NIST, University of Chicago, and the University of Rome.New nanostructured materials offer properties unattainable by traditional approaches, impacting a broad range of fields from computer technology to health care. The growing field of polymer nanocomposites has demonstrated that the addition of a small fraction of nanoparticles to polymeric materials can lead to dramatic changes in modulus, strength, and other properties, which in turn has led to real-world applications. This research will address three fundamental issues: What is the underlying mechanism controlling nanoparticle clustering and cluster structure in a polymer matrix? How can knowledge of the clustering properties be used to improve the modeling of nanocomposite materials? How do design choices of the nanoparticles impact the overall materials properties? Computational molecular modeling is ideally suited to probe nanocomposite behavior at the molecular level. Hence the proposed research will utilize distributed Beowulf computing resources to carry out innovative modeling that both exploits existing methods and develops new approaches.Recently, it has become apparent that nanoparticle clustering in a polymer nanocomposite has, in many cases, a strong similarity to the phenomena of gelation. While traditional phase separation is well understood in the framework of statistical mechanics, the formation of gel phases is comparatively poorly understood. Hence, to understand and eventually control the formation and morphology of nanoparticle clusters, simple model systems are needed in which model parameters can be unambiguously related to the properties of the gel. The insights into the basic mechanisms of gelation will be folded into the design of new models that improve the length and time scales that can be computationally studied for nanocomposite materials. Relating the parameters of the largely homogeneous polymer matrix to general interactions leading to gel formation will enable the development of implicit models for bulk polymer interactions. Such implicit models would dramatically reduce the amount of computational resources that must be dedicated to simulating the molecular detail of polymer chains.The research will be integrated with educational activities via a new program on computational modeling at Wesleyan University. Connections will also be made with high school students.%%%This award was made on a proposal submitted to the Division of Materials Research under the Information Technology Research solicitation NSF-04-012. Research activities covered by this award fall under the National Priority Area, "Advances in Science and Engineering," and the Technical Focus Area, "Innovation in Computational Modeling or Simulation in Research." The Divisions of Materials Research and Chemistry jointly support this award for computational research and education. The research is being done in collaborations with groups at NIST, University of Chicago, and the University of Rome.New nanostructured materials offer properties unattainable by traditional approaches, impacting a broad range of fields from computer technology to health care. The growing field of polymer nanocomposites has demonstrated that the addition of a small fraction of nanoparticles to polymeric materials can lead to dramatic changes in modulus, strength, and other properties, which in turn has led to real-world applications.The computational research supported by this award will study the unique properties of polymers with nanoparticles dispersed in them in order to gain an understanding that may lead to the design of novel new materials. The research will be integrated with educational activities via a new program on computational modeling at Wesleyan University. Connections will also be made with high school students.***

该奖项是根据信息技术研究招标NSF-04-012提交给材料研究部的提案而颁发的。该奖项涵盖的研究活动属于国家优先领域，“科学与工程的进步”和技术重点领域，“计算建模或模拟研究的创新”。“材料研究和化学部门共同支持这个计算研究和教育奖项。 这项研究是与NIST、芝加哥大学和罗马大学的研究小组合作完成的。新的纳米结构材料提供了传统方法无法实现的特性，影响了从计算机技术到医疗保健的广泛领域。 聚合物纳米复合材料领域的不断发展已经证明，向聚合物材料中添加一小部分纳米颗粒可以导致模量、强度和其他性能的显著变化，这反过来又导致了实际应用。这项研究将解决三个基本问题：是什么基本机制控制纳米粒子簇和簇结构的聚合物基体？如何利用聚簇特性的知识来改进纳米复合材料的建模？纳米颗粒的设计选择如何影响整体材料性能？ 计算分子模拟非常适合在分子水平上探测纳米复合材料的行为。 因此，拟议的研究将利用分布式Beowulf计算资源进行创新的建模，既利用现有的方法，并开发新的approaches.Recently，它已成为显而易见的纳米粒子聚集在聚合物纳米复合材料，在许多情况下，凝胶化的现象有很强的相似性。 虽然传统的相分离在统计力学的框架中得到了很好的理解，但凝胶相的形成相对知之甚少。 因此，为了理解并最终控制纳米颗粒簇的形成和形态，需要简单的模型系统，其中模型参数可以明确地与凝胶的性质相关。 凝胶化的基本机制的见解将被折叠到新模型的设计中，这些模型可以改进纳米复合材料的计算研究的长度和时间尺度。 将大部分均匀的聚合物基质的参数与导致凝胶形成的一般相互作用联系起来，将使本体聚合物相互作用的隐式模型的发展成为可能。 这种隐式模型将大大减少必须专门用于模拟聚合物链的分子细节的计算资源量。这项研究将通过卫斯理大学的一个新的计算建模项目与教育活动相结合。 还将与高中生建立联系。%该奖项是根据信息技术研究招标NSF-04-012提交给材料研究部的提案而颁发的。该奖项涵盖的研究活动属于国家优先领域，“科学与工程的进步”和技术重点领域，“计算建模或模拟研究的创新”。“材料研究和化学部门共同支持这个计算研究和教育奖项。 这项研究是与NIST、芝加哥大学和罗马大学的研究小组合作完成的。新的纳米结构材料提供了传统方法无法实现的特性，影响了从计算机技术到医疗保健的广泛领域。 聚合物纳米复合材料领域的不断发展已经证明，向聚合物材料中添加一小部分纳米颗粒可以导致模量、强度和其他性能的显著变化，这反过来又导致了真实的-该奖项支持的计算研究将研究纳米颗粒分散在聚合物中的独特性能，以获得可能导致设计的理解。新材料的创新。 这项研究将通过卫斯理大学的一个新的计算建模项目与教育活动相结合。 还将与高中学生进行联系。**