CAREER: Designing Surface Patterns for Adaptive Shape Control of Soft-Matter-Based Nanoparticles

该职业奖支持一项综合计算和理论研究、教育和推广项目，以开发由软材料制成的纳米颗粒自适应形状控制的设计模式。我们在日常生活中使用的许多面霜、肥皂和凝胶，我们吃的食物，以及构成我们的生物物质都被归类为软质材料。软材料包括胶体分散体（油漆、牛奶）、聚合物（塑料、纤维）、生物物质（蛋白质、细胞）和液晶（电子显示器）等物质。PI特别受到生物软材料的启发，这些材料可以根据化学和机械线索动态改变形状。例如，蛋白质改变构象以响应离子浓度的变化，从而实现特定的生物过程，红细胞可逆变形以使其能够通过细毛细血管。长期以来，研究人员一直试图在设计合成物质时模仿生物材料的这种内在适应性。在这个项目中，PI将开发强大的计算方法，将软物质纳米颗粒的固有属性与它们的机械行为联系起来，包括稳定的形状、实时形状演变和自组织成更大的纳米结构。PI的研究团队将对带电软物质纳米颗粒（如病毒样纳米笼和聚合物纳米膜）的表面电荷和弹性模式进行编程，以实现可控的形状适应。建立表面模式和形状之间的联系将指导可变形纳米容器发展成为药物递送载体，使其形状适应不断变化的生理条件和生物屏障。这些发现还将阐明设计形状可重构纳米颗粒的原理，这些纳米颗粒可以作为下一代材料的基石，具有为特定应用量身定制的响应特性，例如可变形的微型机器人和具有自适应光学响应的功能涂层。该项目的教育和推广部分直接与研究调查相结合。PI将在印第安纳州布卢明顿为高中生主持一个模拟到3d打印的研讨会，在那里他们将熟悉计算工具和制造技术的应用，同时学习纳米级物质的设计。PI的团队将设计基于网络的科学门户，将该项目开发的计算方法引入印第安纳大学内外的课堂，并促进少数族裔服务机构中代表性不足的学生的学习。在设计和实施一个全新的专注于纳米工程的本科项目方面，PI处于一个独特的位置，将发挥关键作用，这将对印第安纳大学产生重大影响，因为它将培养多样化的本科生，以发展纳米技术的进步。该职业奖支持计算和理论研究和教育，以确定软物质基纳米颗粒工程自适应形状控制的基本机制。利用生物材料在合成物质中的适应性是材料工程中最大的挑战之一。PI深受生物学的启发，在生物学中，病毒的衣壳自组装成杆状和球形，表现出形状适应性，蛋白质选择性地与病毒结合，表现出独特的表面图案和形状组合。考虑到这些情况，在这个项目中，PI将把表面图案与由带电软材料制成的纳米颗粒的机械行为联系起来，如病毒状纳米容器、胶束囊泡和聚合物纳米膜。PI的研究小组将研究表面电荷和弹性模式如何影响这些纳米颗粒的整体形状，以及这些模式如何控制生理条件下纳米颗粒形状转换和聚集的时间尺度。分子动力学模拟将用于探测表面电荷和弹性模式，1)使纳米颗粒形状适应，2)控制实时形状切换和纳米颗粒组装成高阶纳米结构。PI将开发分子动力学方法，这种方法具有独特的能力，可以将纳米颗粒表面反离子凝聚的较小长度尺度效应与纳米颗粒的较大长度尺度聚集行为联系起来。基于这一多尺度信息，本研究将生成地图，将表面模式与病毒样纳米颗粒和聚合物纳米膜形状在各种环境条件下的平衡和动态特性联系起来。这些图谱将有助于指导可变形纳米颗粒的设计，这些纳米颗粒可以主动改变形状和相关功能，提高目前工程仿生纳米容器在靶向药物输送中的应用能力。这项研究还将通过可变形纳米级构建块的自组装来扩展设计可重构材料的合成能力。该项目将涉及研究生、本科生和多样化的在线用户社区，通过实践经验和基于研究的课程、研讨会和在线计算平台进行积极的研究。PI将开发一个模拟到3d打印的车间和基于网络的科学网关，这将提供一个复杂的、用户友好的环境来参与纳米颗粒的模拟。这些平台将促进广泛的学生和教育工作者，包括少数民族服务机构的学生和教育工作者，获得教育和研究材料。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

NONTECHNICAL SUMMARYThis CAREER award supports an integrated computational and theoretical research, education, and outreach project to develop design patterns for adaptive shape control of nanoparticles made from soft materials. Much of the cream, soap, and gel we use in everyday life, the food we eat, and the biological matter we are made of is classified as soft material. Soft materials include matter such as colloidal dispersions (paints, milk), polymers (plastics, fibers), biological matter (proteins, cells), and liquid crystals (electronic displays). The PI is particularly motivated by biological soft materials that dynamically change their shape in response to chemical and mechanical cues. For example, proteins change conformations in response to changes in ion concentration to enable specific biological processes, and red blood cells deform reversibly to enable their passage through thin capillaries. Researchers have long sought to mimic this intrinsic adaptability of biological materials in the design of synthetic matter. In this project, the PI will develop powerful computational methods to link the inherent attributes of soft-matter-based nanoparticles with their mechanistic behavior, including stable shapes, real-time shape evolution, and self-organization into larger nanostructures.The PI's research team will program the surface charge and elasticity patterns of charged soft-matter-based nanoparticles such as virus-like nanocages and polymeric nanomembranes to enable controlled shape adaptation. Establishing the links between surface pattern and shape will guide the development of deformable nanocontainers into drug-delivery carriers that adapt their shape to evolving physiological conditions and biological barriers. The findings will also elucidate the principles of designing shape-reconfigurable nanoparticles that can act as building blocks of next-generation materials with responsive properties tailored for specific applications, such as shape-shifting microrobots and functional coatings with adaptive optical response.The education and outreach components of this project are directly integrated with its research investigations. The PI will lead a simulation-to-3D-printing workshop for high-school students in Bloomington, Indiana, where they will become familiar with applications of computing tools and fabrication techniques while learning about the design of matter at the nanoscale. The PI's team will design web-based science gateways to bring the computational methods developed in this project to classrooms in and outside of Indiana University, and facilitate the learning of underrepresented students at Minority-Serving Institutions. The PI is in a unique position to play a pivotal role in the design and implementation of a brand-new undergraduate program focused on nanoscale engineering that will significantly impact Indiana University, as it will train a diverse pool of undergraduate students to develop advances in nanotechnology.TECHNICAL SUMMARYThis CAREER award supports computational and theoretical research and education to identify the fundamental mechanisms of engineering adaptive shape control in soft-matter-based nanoparticles. Harnessing the adaptability of biological materials in synthetic matter is one of the biggest challenges in materials engineering. The PI is deeply inspired by biology, where viral capsomeres self-assemble into rods and spheres which display shape adaptation, and where proteins selectively bind to viruses that exhibit unique combinations of surface pattern and shape. With such instances in mind, in this project, the PI will connect the surface patterning to mechanistic behavior for nanoparticles made from charged soft materials, such as virus-like nanocontainers, micellar vesicles, and polymeric nanomembranes. The PI's research team will investigate how surface charge and elasticity patterns affect the overall shape of these nanoparticles, and how these patterns control the timescales of shape-switching and aggregation of nanoparticles in physiological conditions. Molecular dynamics simulations will be used to probe surface charge and elasticity patterns that 1) enable nanoparticle shape adaptation, and 2) control real-time shape-switching and assembly of nanoparticles into higher-order nanostructures.The PI will develop molecular dynamics methods that are uniquely capable of connecting the smaller length-scale effects of counterion condensation on nanoparticle surfaces to the larger length-scale aggregation behavior of nanoparticles. Based on this multiscale information, this research will produce maps that link surface patterns to equilibrium and dynamical properties of the shapes of virus-like nanoparticles and polymeric nanomembranes for a wide range of environmental conditions. These maps will help guide the design of deformable nanoparticles that can actively change shape and associated functionalities, advancing the current capabilities for engineering biomimetic nanocontainers for applications in targeted drug-delivery. This research will also expand the synthetic capabilities of designing reconfigurable materials via the self-assembly of deformable nanoscale building blocks.This project will involve graduate students, undergraduate students, and a diverse online community of users in active research via hands-on experiences and research-based courses, workshops, and online computing platforms. The PI will develop a simulation-to-3D-printing workshop and web-based science gateways that will provide a sophisticated, user-friendly environment to engage with the simulations of nanoparticles. These platforms will facilitate access of the educational and research materials to a broad group of students and educators, including those at Minority-Serving Institutions.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.