Travel Support for Workshop on Best Practices in Modeling Across Scales from Materials Discovery to Manufacturing; Arlington, Virginia; Summer 2023

该奖项为参加“从材料发现到制造的跨尺度建模的最佳实践：走向错误和不确定性的系统分析”研讨会的主要演讲者和主持人提供旅费支持。本次研讨会将讨论了解材料创新和制造的第一性原理建模领域的挑战和机遇的需要。研讨会提供了一个论坛，分享材料建模，不确定性量化和误差分析的前沿研究。它为参与者提供了一个展示他们的科学成就的机会，与来自学术界、政府实验室和工业界的同行和同事互动，扩展他们的网络，并在更广泛的先进材料和制造社区内促进新的合作。研讨会为与会者提供了一个更广阔的材料发现、设计和制造周期的视角，这对于推进新技术造福社会至关重要。与美国国家科学基金会扩大科学和工程参与的目标一致，研讨会寻求妇女和未被充分代表的少数群体作为演讲者和与会者的参与。该车间符合国家培育先进材料和制造业的优先事项。本次研讨会为专家们提供了一个平台，展示和讨论他们在从材料建模和发现到制造的各个尺度的误差和不确定性系统分析的最佳实践中的研究和结果。研讨会参与者将讨论数据科学、机器学习和人工智能（AI）在开发材料及其制造的第一原理建模中的应用。研讨会汇集了建模和仿真、多尺度建模、机器学习、信息学、数据分析、过程设计和制造的人工智能方面的研究人员和专家，讨论跨领域的途径、挑战和机遇。目标是确定并将误差和不确定性分析集成到标准的计算工作流程中，从而使严格的误差确定和报告成为材料建模社区的标准规范。研讨会的重点是新材料发现的创新途径，它们的设计和制造，以及交叉研究机会的确定。研讨会分为不同的会议，包括由国内外领先的专家讨论他们的最新研究和确定研究空白的主题，如：(1)电子结构，第一原理和量子化学方法的误差控制，(2)建模者与实验人员合作时的最佳实践，(3)更高尺度的误差控制。原子间电位包括多尺度材料建模中的机器学习误差传播，(4)材料合成、加工和制造的误差控制，(5)将误差分析纳入工作流程和材料数据库。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。

This award provides travel support for key speakers and presenters to attend the workshop on “Best Practices in Modeling Across Scales from Materials Discovery to Manufacturing: Towards Systematic Analysis of Errors and Uncertainty." This workshop will address the need to understand the challenges and opportunities in the area of first principles modeling for materials innovation and manufacturing. The workshop provides a forum to share leading-edge research on materials modeling, uncertainty quantification and error analysis. It offers participants an opportunity to showcase their scientific accomplishments, interact with peers and colleagues from academia, government labs, and industry, extend their network, and foster new collaborations within the broader advanced materials and manufacturing communities. The workshop provides attendees with a broader view of the materials discovery, design, and manufacturing cycle, that are critical to advancing new technologies that benefit society. Consistent with NSF's goal of broadening participation in science and engineering, the workshop seeks participation of women and underrepresented minority groups as speakers and attendees. The workshop meets the national priority of fostering advanced materials and manufacturing.This workshop provides a platform for experts to present and discuss their research and results in Best Practices in Systematic Analysis of Errors and Uncertainty Across Scales from Materials Modeling and Discovery to Manufacturing. The workshop participants will discuss the application of Data Science, Machine Learning and Artificial Intelligence (AI) in developing First Principles Modeling of Materials and their Manufacturing. The workshop brings together researchers and experts in modeling and simulation, multiscale modeling, machine learning, informatics, data analytics, artificial intelligence for process design and manufacturing to discuss cross-cutting pathways, challenges, and opportunities. The goal is to determine and integrate error and uncertainty analysis into standard computational workflows, so that rigorous error determination and reporting become a standard norm for the materials modeling community. The workshop focuses on innovative pathways for new materials discovery, their design and manufacture, and identification of cross-cutting research opportunities. The workshop is organized into different sessions and includes talks by leading domestic and international experts discussing their latest research and identifying research gaps on topics such as (1) Error control for electronic structure, first principles, and quantum chemistry methods, (2) Best practices for modelers when working with experimentalists, (3) Error control at higher scales: interatomic potentials including machine learned error propagation in multiscale materials modeling, (4) Error control for materials synthesis, processing, and manufacture, (5) Incorporating error analysis into workflows and materials data repositories.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.