RII Track 1: Materials Assembly and Design Excellence in South Carolina: MADE in SC

南卡罗来纳州材料组装和设计卓越倡议(Made In SC)承诺在先进材料设计方面开辟新天地。该项目将结合计算和实验方法来设计具有特定理想性能的材料。该项目将促进复杂材料的基础知识，同时致力于开发具有有价值的商业应用的产品，如改进的激光、水处理和再生医学。该项目将对南卡罗来纳州的S研究能力进行重大投资，获得最先进的仪器和计算能力，并在全州各地的机构招聘17名新的教职研究人员。在其研究议程的同时，Made in SC还将致力于通过大学课程改进和高中教师专业发展活动来提高南卡罗来纳州的科学、技术、工程和数学(STEM)教育能力。在SC材料开发过程中所做的技术描述将使用材料基因组倡议(MGI)框架，其中包含迭代设计循环，其中基于初始设计约束的建模和计算提供将为实验设计提供信息的数据。实验结果的成像和数据可视化将产生洞察力，然后可以推动额外的建模工作，这个循环将继续下去，直到获得最优解决方案。这一以MGI为基础的框架将依赖多尺度建模和计算核心(MCC)的资源，该核心将作为项目的一部分而建立。MCC将开发适当的跨长度尺度(微观、介观和连续)的建模能力，并将支持这些工具在该项目中的应用？S的主要研究重点是：1)具有受控光学和磁性的分层结构；2)对刺激响应的聚合物材料；以及3)交互生物材料的合理设计。这些研究工作将促进对观察到的材料性能的化学和物理驱动因素的基本理解，同时还将实现具有理想性能的商业应用的新材料。

Non-technical DescriptionThe initiative for Materials Assembly and Design Excellence in South Carolina (MADE in SC) promises to break new ground in advanced materials design. The project will combine computational and experimental methods to design materials with specific desirable properties. The project will advance fundamental knowledge of complex materials while simultaneously working toward the development of products with valuable commercial applications, such as improved lasers, water treatment, and regenerative medicine. The project will make major investments in South Carolina?s research capacity, acquiring state-of-the art instrumentation and computing capabilities and hiring seventeen new faculty researchers at institutions across the state. In parallel with its research agenda, MADE in SC will also work to improve Science, Technology, Engineering, and Mathematics (STEM) education capacity in South Carolina through college curriculum improvements and professional development activities for high school teachers.Technical Description MADE in SC materials development process will use a Materials Genome Initiative (MGI) framework, incorporating an iterative design loop wherein modeling and computation based on initial design constraints provide data that will inform experimental design. Imaging and data visualization of experimental results will lead to insights that can then drive additional modeling work, with the cycle continuing until an optimal solution is achieved. This MGI-based framework will depend on the resources of the Multiscale Modeling and Computational Core (MCC), which will be established as part of the project. The MCC will develop modeling capabilities appropriate across length scales (microscopic, mesoscopic, and continuum), and will support the application of these tools to the project?s major research thrusts: 1) hierarchical structures with controlled optical and magnetic properties; 2) stimuli-responsive polymeric materials; and 3) rational design of interactive biomaterials. These research efforts will advance fundamental understanding of the chemical and physical drivers of observed material properties while also realizing new materials with desirable properties for commercial applications.