HDR Institute: Institute for Data Driven Dynamical Design

从分子到机器人，尽管在长度和时间尺度上存在差异，但动力学设计具有共同的理论基础。然而，这样的研究往往被高维的设计空间所淹没。数据驱动动力设计研究所解决了预测材料动力学过程的挑战，包括离子和分子运输，催化途径和超材料中的相变，重点是发现新的机制和途径。这项研究代表了一种范式的转变，从传统材料的努力，涉及基态和稳态性能的逐步改进。数据科学的发展目标是(i)为机器智能编码复杂结构和机械路径的策略，（ii）进化系统的新预测能力，以及（iii）可视化和集成机器和人类专业知识的进步。推动这些数据科学发展的是跨高维设计空间的动态过程的大规模模拟。这些大规模模拟的实验验证解决了最终产品预测和其中的机制途径。该研究所的数据科学创新可能会推动STEM内外涉及复杂时间演化系统的领域，包括分子生物学、大气科学、地球物理学和物理宇宙学。该研究所寻求发展和团结分散的数据驱动设计社区。通过拓展活动寻求长期增长，包括(i)高中编码学校，（ii）本科生参与数据丰富的研究，以及（iii）向学生介绍数据科学并激励他们追求更高学位的学士后桥梁项目。数据驱动的设计社区活动包括(i)跨学科暑期学校和研讨会，（ii）合作发展和传播研究所发展的研究员计划，以及（iii）致力于为设计社区创建开源软件。通过这些努力，学院积极寻求在STEM领域招募、留住和毕业各种各样的学生。这个虚拟研究所试图通过机器和人类智能的结合来设计复杂的动态材料和结构。为了学习动态行为并最终发现新机制，需要解决三个核心数据科学需求：(i)捕获和编码复杂材料和几何结构的空间排列、相互作用和时间演变的新表示和学习架构，（ii）对高维、时变设计空间的有效探索，以及（iii）新的可视化分析工具，以定量地结合人在环设计反馈。这些领域的进步形成了一个良性循环，在新机制的驱动下加速了新材料的发现。该研究所汇集了一个跨学科团队，专注于四个处于“临界点”的设计空间，在这些空间中可以很容易地创建大量动态数据：(i)用于燃料电池和电池的具有定制离子传输的结晶固体，（ii）用于机器人的压敏超材料，（iii）用于化学生产的光驱动催化反应，以及（iv）用于化学分离的多孔框架的合成和组装。这四个领域是为更广泛的科学界开发网络基础设施的试验台。贯穿这些活动的是专门的活动，旨在在数据科学和物理科学/工程的交叉点培养新一代STEM人才，并通过有针对性的外展扩大STEM的参与。该项目是美国国家科学基金会“利用数据革命”（HDR）大创意活动的一部分。该奖项由先进网络基础设施办公室颁发，由NSF数学和物理科学理事会的化学、材料研究和数学科学部门联合支持。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。

From molecules to robots, designing for dynamics has common theoretical underpinnings despite differences in length and time scale. However, such research is often overwhelmed by the high dimensional design space. The Institute for Data-Driven Dynamical Design addresses the challenge of prediction of dynamical processes in materials, including ion and molecular transport, catalytic pathways, and phase transformations in metamaterials, with a focus on discovering fundamentally new mechanisms and pathways. This research represents a paradigm shift from traditional material efforts involving incremental improvements in ground-state and steady-state properties. Developments in the data sciences target (i) strategies for encoding complex structures and mechanistic pathways for machine intelligence, (ii) new predictive capabilities for evolving systems, and (iii) advances in visualization and integrating machine and human expertise. Fueling these data science developments are large-scale simulations of dynamical processes across high dimensional design spaces. Experimental validation of these large-scale simulations addresses both end-product prediction and mechanistic pathways therein. The Institute's data science innovations may advance fields both within and beyond STEM involving complex time-evolving systems including molecular biology, atmospheric science, geophysics, and physical cosmology. The Institute seeks to grow and unite the dispersed data-driven design community. Long-term growth is sought through outreach activities involving (i) high school coding schools, (ii) undergraduate involvement in data-rich research, and (iii) a post-baccalaureate bridge program that introduces students to data sciences and motivate them to pursue higher degrees. Data-driven design community activities include (i) interdisciplinary summer schools and workshops, (ii) a Fellows program to collaboratively grow and disseminate the Institute’s developments, and (iii) dedicated efforts to create open-source software for the design community. Throughout these efforts, the Institute actively seeks to recruit, retain, and graduate a diverse array of students in STEM. This virtual Institute seeks to design complex dynamical materials and structures through the union of machine and human intelligence. To learn dynamical behavior and ultimately discover new mechanisms, three core data science needs are addressed: (i) new representations and learning architectures that capture and encode the spatial arrangement, interactions, and temporal evolution of complex materials and geometrical structures, (ii) efficient exploration of high dimensional, time-dependent design spaces, and (iii) new visual analytics tools to quantitatively incorporate human-in-the-loop design feedback. Advances in each of these areas form a virtuous cycle that accelerates discovery of new materials, driven by new mechanisms. This Institute converges an interdisciplinary team focused on four design spaces at their `tipping point', where large quantities of dynamical data can be readily created: (i) crystalline solids with tailored ion transport for fuel cells and batteries, (ii) pressure-sensitive metamaterials for robotics, (iii) light driven catalytic reactions for chemical production, and (iv) synthesis and assembly of porous frameworks for chemical separations. These four areas are testbeds for cyberinfrastructure development for the broader scientific community. Interwoven throughout these activities are dedicated activities to build a new generation of STEM talent at the intersection of data science and the physical sciences/engineering and to broaden participation in STEM through targeted outreach.This project is part of the National Science Foundation's Big Idea activities in Harnessing the Data Revolution (HDR). The award by the Office of Advanced Cyberinfrastructure is jointly supported by the Divisions of Chemistry, Materials Research, and Mathematical Sciences within the NSF Directorate for Mathematical and Physical Sciences.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.