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

从材料发现到制造的跨尺度建模最佳实践研讨会的差旅支持；

• 批准号: 2315913
• 负责人: Elif Ertekin
• 金额: $ 4.69万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-01 至 2024-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2315913&HistoricalAwards=false
• 关键词: Travel; Support; Workshop; Best; Practices

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.

该奖项为主要演讲者和演讲者提供差旅支持，以参加“从材料发现到制造的跨尺度建模的最佳实践：对错误和不确定性的系统分析”研讨会。“本次研讨会将解决需要了解的挑战和机遇，在该地区的第一原则建模的材料创新和制造。该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其科学成就的机会，与学术界，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。该研讨会为与会者提供了材料发现，设计和制造周期的更广泛的视野，这对于推进造福社会的新技术至关重要。与NSF扩大科学和工程参与的目标相一致，研讨会寻求妇女和代表性不足的少数群体作为演讲者和与会者的参与。该研讨会符合国家促进先进材料和制造的优先事项。该研讨会为专家提供了一个平台，展示和讨论他们在从材料建模和发现到制造的跨尺度误差和不确定性系统分析最佳实践中的研究和成果。研讨会的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。该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，工艺设计和制造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计算工作流程中，以便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，以及跨领域研究机会的识别。研讨会分为不同的会议，包括国内和国际领先的专家讨论他们的最新研究和确定研究差距的主题，如（1）电子结构，第一原理和量子化学方法的误差控制，（2）与实验工作者合作时建模的最佳实践，（3）更高尺度的误差控制：包括多尺度材料建模中的机器学习误差传播的原子间势，（4）用于材料合成、处理和制造的误差控制，（五）将错误分析纳入工作流程和材料数据存储库。该奖项反映了NSF的法定使命，并被认为是值得的。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来提供支持。