An Integrated Experimental and Computational Platform for Discovery and Processing of Functional Nano-Emulsions

合理设计新材料并通过控制加工历史来设计其性能的能力将使具有独特性能且易于制造的全新材料的合成成为可能。这项研究希望通过操纵一个由纳米颗粒和聚合物纳米乳液组成的简单系统来开发这些技术，使其具有各种各样的结构形式，并具有调谐的机械和相关性能。由聚合物、颗粒、乳液和表面活性剂制成的软材料被广泛应用于一系列新兴和社会相关的应用，包括医疗和能源技术，以及人体和电子领域之间的接口。因此，这可以打开新的制造模式，帮助推动经济的新领域，并提高我们在材料设计方面的知识。软材料的发现和加工是独特的。对于每种应用，都需要一组材料特性：弹性模量，屈服应力，屈服应变，渗透率，电导率等，并且材料的选择非常广泛。本研究旨在通过利用外场的结构组合设计和制造来减少可能材料的设计空间。该研究将开发生成材料设计空间的方法，以及从生成的数据中有效地推导结构的方法。在制造过程中，利用与聚合物复合材料组分密切相互作用的外场在微观尺度上排列组分，以产生新的机械结构。这种数据驱动的材料设计和加工为材料选择和结构开发提供了一种新的方法和范式。这项研究还将辅以一款视频游戏的开发，以扩大公众对软材料及其特性的了解，并将向公众开放。新的软材料和生物材料的发现很大程度上是由许多经验和一些理论结构-性质关系促成的试验和错误推动的。当这种关系已知时，可以通过针对适当的微观结构（例如晶体，玻璃，分形，各向异性）来合成具有所需功能的材料。此外，许多软物质材料在淬火后组装成非最低能态的结构，并且强烈依赖于加工历史。由于软材料是多功能的，应用广泛：生物医学研究和技术，石油和天然气勘探和操作，消费者护理产品，以及整个农业和食品工业，需要高度定制的材料来满足特定的应用需求。这项研究将开发实验和计算工具，用于设计由纳米乳液构建的多功能软材料，纳米级液滴由悬浮在水中的各种油组成。通过改变液滴的化学组成和悬浮溶剂中的添加剂，可以合成具有明确颗粒间相互作用的纳米乳液。通过改变温度、盐度、外加磁场和流场的时间，纳米乳液可以被诱导聚集成具有多种不同形态特征的凝胶结构。这项工作的一个具体目标是了解和控制如何利用加工历史对这些纳米复合材料的微观结构和最终性能进行精细控制。这将通过执行详细的模拟来实现，探索广阔的，实验可访问的参数空间，然后利用机器学习工具选择富有成效的纳米乳液和加工方法来产生新的软材料。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。

The ability to design new materials rationally and engineer their properties through control of processing history will enable the synthesis of whole new classes of materials with unique properties that are easily manufacturable. This research looks to develop those techniques through the manipulation of a simple system consisting of nanoparticles and polymer nano-emulsions into a wide variety of structural forms with tuned mechanical and related properties. Soft materials built from polymers, particles, emulsions, and surfactants are employed in a broad array of emerging and societally relevant applications including medical and energy technologies, and the interface between the human body and the electronic domain. As such, this could open new manufacturing paradigms assisting driving new areas in the economy and advancing our knowledge in materials design. The discovery and processing of soft materials is idiosyncratic. For each application, a set of material properties: elastic modulus, yield stress, yield strain, permeability, conductivity, among others is needed and the materials choices are vast. This research looks to reducing the design space of possible materials through the combined design and fabrication of structures utilizing external fields. The research will develop approaches to generating the materials design space and the means to efficiently derive structures from the generated data. The use of external fields which interact intimately with the components of the polymer composite to arrange the components at the microscale during fabrication to produce new mechanical structures. This data-driven material design and processing is a new approach and paradigm to materials choice and structure development. The research is complemented by the development of a video game broadening the public understanding of soft materials and their properties which will be made publicly available. The discovery of new soft and biomaterials is driven largely by trial and error facilitated by many empirical and a few theoretical structure-property relations. When such relations are known, materials with a desired functionality can be synthesized by targeting the appropriate microstructure (e.g. crystalline, glassy, fractal, anisotropic). Moreover, many soft matter materials are quenched to assemble into structures which are not the lowest energy state and depend strongly on processing history. Because soft materials are multifunctional and applied broadly: to biomedical research and technologies, for oil and gas exploration and operations, in consumer care products, and throughout agriculture and the food industry, highly tailored materials are required to meet application specific needs. This research will develop the experimental and computational tools needed for the design multifunctional soft materials built from nano-emulsions, nano-scale droplets composed of a diverse array of oils suspended in water. Through variation of chemical composition of the droplets and the additives in the suspending solvent, nano-emulsions with well defined inter-particle interactions can be synthesized. By varying in time the temperature, salinity, applied magnetic fields, and flow fields, the nano-emulsions can be induced to aggregate into a gelled structure with a wide range of different morphological characteristics. A specific aim of this work is to understand and control how processing history can be used to exert fine control over this micro-structure and resulting properties of these nano-composites. This will be achieved by performing detailed simulations that explore the vast, experimentally accessible parameter space, and then utilizing machine learning tools to select fruitful nano-emulsions and processing methods to yield novel soft materials.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.