Theoretical and Computational Modeling of Soft Materials

软材料的理论和计算模型

• 批准号: 1106331
• 负责人: Alan Denton
• 金额: $ 20.8万
• 依托单位: North Dakota State University Fargo
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1106331&HistoricalAwards=false
• 关键词: Theoretical; Computational; Modeling; Soft; Materials

TECHNICAL SUMMARYThis award supports theoretical studies and educational activities in the interdisciplinary field of soft materials science. Soft materials, such as colloidal dispersions and polymer solutions and melts, display remarkable thermal, mechanical, and optical properties that emerge from self-assembly of macromolecules into diverse structures. Predicting and controlling the structure, phase behavior, and dynamics of such materials require a deep understanding of the forces and correlations between macromolecules. Recent experimental observations demonstrate that strong ion-ion coupling, incorporation of nanoparticles, and application of external fields can profoundly influence the self-assembly of colloidal and polymeric materials. Motivated by these experiments, this project addresses several technologically relevant issues regarding the behavior of colloid-nanoparticle suspensions and polymer-nanoparticle composites. Specifically, the research will address the following fundamental questions: (1) Through what mechanisms can nanoparticles affect the stability of colloidal suspensions? (2) By tuning interparticle interactions, can we predict and control how nanoparticles perturb polymer conformations and induce coils to swell or shrink? (3) How should external fields be configured to guide self-assembly of soft materials? These unresolved questions will be addressed through a coarse-grained modeling approach that combines a variety of statistical mechanical methods. Poisson-Boltzmann theory, effective-interaction theory, classical density-functional theory, and Monte Carlo simulations will be developed and applied to probe length and time scales that are inaccessible to ab initio simulations. The ultimate goal of this research is to advance fundamental understanding of soft matter to the point of facilitating discovery and fabrication of novel, multifunctional, and environmentally sustainable nanostructured materials.Guiding the self-assembly of colloids, nanoparticles, and polymers has many potential applications. For example, enhancing phase stability of colloidal suspensions can aid the design and fabrication of photonic band-gap materials for optical switching. Engineering nanoparticles with tailored properties holds promise for modifying morphology of soft materials and controlling drug delivery. Understanding crowding of proteins by macromolecules within the cytoplasm has profound implications for manipulating the functions of biological cells. Furthermore, since suspensions of colloids and nanoparticles evolve slowly and can be imaged in real space, they can yield insights into the behavior of hard materials. Finally, the methods developed for colloidal and polymeric systems can be adapted to biologically relevant systems, such as biopolymers, virus suspensions, and polyelectrolyte microgels and microcapsules.Educational impacts of this project include training of undergraduate students and a postdoctoral fellow in soft matter physics and computational modeling methods; development of courses for graduate students in physics and interdisciplinary materials science programs; and support of outreach programs for local schools and Native American students throughout the state of North Dakota.NONTECHNICAL SUMMARYThis award supports theoretical studies and educational activities in the interdisciplinary and technologically relevant field of soft materials science. Soft materials, which are composed of giant molecules called macromolecules, display remarkable physical properties that emerge from spontaneous organization of diverse structures. Common types of macromolecules are colloids, which are an ultra-divided form of matter consisting of particles some one-thousandth to one-millionth the size of the human hair, and polymers which are long chain-like molecules making up many natural and synthetic materials. Charge-stabilized colloids pervade industry and nature: familiar examples include aqueous paints, detergents, and clays, to name a few. Polymers are the building blocks of such ubiquitous materials as plastics and rubbers, and are key components of biomaterials including DNA and proteins.Predicting and controlling the behavior of soft materials requires a deep understanding of the highly tunable forces acting between macromolecules. Recent experimental observations demonstrate that incorporation of nanoparticles and application of external electric or magnetic fields can profoundly influence the self-assembly of colloidal and polymeric materials. Motivated by these experiments, this project applies an array of theoretical and computer modeling methods to address technologically relevant issues regarding the physical behavior of colloid-nanoparticle suspensions and polymer-nanoparticle composites. By clarifying several technologically important issues, outcomes of this work are expected to have broad significance for materials scientists and engineers by providing powerful tools to rationally design novel materials with potential applications to renewable energy and medicine. Furthermore, since suspensions of colloids and nanoparticles evolve slowly and can be imaged in real space, they can yield insights into the behavior of hard materials. Finally, the modeling methods developed will be broadly adaptable to a variety of macromolecular systems, including biological materials.Educational impacts of this project include training of undergraduate students and a postdoctoral fellow in soft matter physics and computational modeling methods; development of courses for graduate students in physics and interdisciplinary materials science programs; and support of outreach programs for local schools and Native American students throughout the state of North Dakota.

该奖项支持软材料科学跨学科领域的理论研究和教育活动。 软材料，如胶体分散体和聚合物溶液和熔体，显示出显着的热，机械和光学性能，从大分子的自组装成不同的结构。 预测和控制这些材料的结构，相行为和动力学需要深入了解大分子之间的力和相互关系。 最近的实验观察表明，强烈的离子-离子耦合，纳米粒子的掺入，以及外场的应用可以深刻地影响胶体和聚合物材料的自组装。 受这些实验的启发，该项目解决了几个技术相关的问题，胶体纳米粒子悬浮液和聚合物纳米粒子复合材料的行为。 具体而言，本研究将解决以下基本问题：（1）纳米颗粒通过什么机制影响胶体悬浮液的稳定性？ (2)通过调整粒子间的相互作用，我们能否预测和控制纳米粒子如何扰乱聚合物构象，并诱导线圈膨胀或收缩？ (3)如何配置外部场来引导软材料的自组装？ 这些未解决的问题将通过结合各种统计力学方法的粗粒度建模方法来解决。 泊松-玻尔兹曼理论，有效相互作用理论，经典的密度泛函理论和蒙特卡罗模拟将被开发和应用于探针的长度和时间尺度是无法从头计算模拟。 本研究的最终目标是推进对软物质的基本理解，以促进发现和制造新颖的、多功能的和环境可持续的纳米结构材料。引导胶体、纳米颗粒和聚合物的自组装具有许多潜在的应用。 例如，提高胶体悬浮液的相位稳定性可以帮助设计和制造用于光开关的光子带隙材料。 具有定制特性的工程纳米颗粒有望改变软材料的形态和控制药物递送。 理解细胞质内大分子对蛋白质的拥挤对于操纵生物细胞的功能具有深远的意义。 此外，由于胶体和纳米颗粒的悬浮液演变缓慢，并且可以在真实的空间中成像，因此可以深入了解硬质材料的行为。最后，为胶体和聚合物系统开发的方法可以适用于生物相关系统，如生物聚合物、病毒悬浮液、微凝胶和微胶囊，该项目的教育影响包括培养软物质物理学和计算建模方法的本科生和博士后研究员，为物理学和跨学科材料科学项目的研究生开发课程，并支持整个北达科他州当地学校和美洲原住民学生的推广计划。非技术性总结该奖项支持软材料科学跨学科和技术相关领域的理论研究和教育活动。 软材料由称为大分子的巨分子组成，显示出从不同结构的自发组织中产生的显着物理特性。 大分子的常见类型是胶体，这是一种超分割形式的物质，由人类头发大小的千分之一到百万分之一的颗粒组成，以及聚合物，它们是构成许多天然和合成材料的长链状分子。 电荷稳定的胶体遍布工业和自然界：常见的例子包括水性涂料，洗涤剂和粘土，仅举几例。 聚合物是塑料和橡胶等普遍存在的材料的基础，也是DNA和蛋白质等生物材料的关键组成部分。预测和控制软材料的行为需要深入了解大分子之间作用的高度可调力。 最近的实验观察表明，纳米粒子的掺入和外部电场或磁场的应用可以深刻地影响胶体和聚合物材料的自组装。 受这些实验的启发，该项目应用一系列理论和计算机建模方法来解决有关胶体纳米颗粒悬浮液和聚合物纳米颗粒复合材料的物理行为的技术相关问题。通过澄清几个技术上重要的问题，这项工作的成果预计将具有广泛的意义，材料科学家和工程师提供强大的工具，合理设计新材料，可再生能源和医药的潜在应用。 此外，由于胶体和纳米颗粒的悬浮液演变缓慢，并且可以在真实的空间中成像，因此可以深入了解硬质材料的行为。 最后，开发的建模方法将广泛适用于各种大分子系统，包括生物材料。该项目的教育影响包括培养软物质物理学和计算建模方法的本科生和博士后研究员;为物理学和跨学科材料科学课程的研究生开发课程;并支持整个北达科他州的当地学校和美洲原住民学生的外展计划。