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.

该奖项为关键演讲者提供了旅行支持，并提供了参加“从材料发现到制造业的范围建模的最佳实践研讨会：朝着错误和不确定性进行系统分析。”该研讨会将解决了解材料创新和制造的第一原理建模领域的挑战和机遇的需求。该研讨会提供了一个论坛，可以分享有关材料建模，不确定性量化和错误分析的领先研究。它为参与者提供了展示他们的科学成就，与学术界，政府实验室和行业的同伴和同事互动，扩展其网络，并在更广泛的高级材料和制造业社区中培养新的合作。该研讨会为与会者提供了更广泛的材料发现，设计和制造周期的看法，这对于促进有益于社会的新技术至关重要。与NSF扩大参与科学和工程的目标一致，该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。该研讨会符合培养高级材料和制造业的全国优先事项。该研讨会为专家提供了一个平台，以介绍和讨论他们的研究和结果，以系统地分析从材料建模和发现到制造业的错误和不确定性的系统分析中的最佳实践。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。该研讨会汇集了建模和仿真，多尺度建模，机器学习，信息信息，数据分析，过程设计和制造的人工智能，以讨论跨剪切途径，挑战和机遇的研究人员和专家。目的是确定并将不确定性分析和不确定性分析整合到标准的计算工作流程中，以便严格的错误确定和报告成为材料建模社区的标准规范。该研讨会着重于新材料发现，其设计和制造的创新途径，以及横切研究机会的识别。研讨会被组织为不同的会议，包括领导国内外专家讨论其最新研究并确定有关主题的研究差距，例如（1）（1）对电子结构，第一原理和量子化学方法的误差控制，（2）模型的最佳实践，用于与实验者合作时，（3）对较高的材料控制材料的材料模型，包括机器间的材料模型：4：4处理和制造，（5）将错误分析纳入工作流程和材料数据存储库中。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响评估标准，通过评估诚实地表示支持。