Graduate Traineeship on Advances in Materials Science using Machine Learning

该奖项的全部或部分资金来自《2021年美国救援计划法案》(公法117-2)。应对社会的重大挑战将需要一支准备工作的劳动力，以整合来自多个学科的知识，作为一个团队工作，并利用来自不同背景的个人的智力贡献。然而，雇主经常发现，进入职场的研究生缺乏跨学科培训，也缺乏对数据科学的欣赏。这些情况需要STEM研究生教育项目的新设计，以促进跨学科团队建设，将数据科学整合到解决方案方法中，并让研究生接触到多元文化的工作环境。这项授予阿克伦大学(UA)的国家科学基金会研究培训(NRT)奖将支持俄亥俄州东北部为材料科学和机器学习领域工作的硕士和博士生提供的第一个此类培训项目，这些项目将导致新材料的发现和材料研究的重大进展。培训项目将服务于40名硕士和博士生，其中包括20名受资助的硕士和博士生，这些学生来自不同的背景，包括代表性较低的少数群体，他们注册了聚合物科学和聚合物工程、机械工程和计算机科学的研究生课程。这个NRT项目旨在识别和缓解知识差距，同时为广泛的材料研究社区感兴趣的几个跨学科研究问题提供数据驱动的答案。例子包括i)材料模数随温度的可调性和通过添加剂制造生产的复合材料部件的质量一致性，ii)离子的动力学和离子在结晶聚合物领域中的离子传输机制，iii)具有可调节的热和机械性能的化学可回收聚合物的分子设计；iv)当前机器学习工具中的新的特征选择技术，以处理来自大型复杂聚合物系统的数据；以及v)来自多个来源的大规模不同数据的高效和系统集成。该研究将利用实验和数值方法相结合的方法，包括分子动力学模拟、有限元分析、聚合物化学合成、添加剂制造技术和机器学习工具，以实现预期的目标。该项目将创建一个可与现有聚合物储存库集成的可扩展材料数据库，可用于开发新型复合材料、具有优异导电性的固体电解质的分子设计规则，以及可有效回收的新聚合物材料的设计。学员将通过课程和研究工作、讲习班和研讨会、实验室轮换、在联邦和工业实验室的实习以及国际接触，发展强大的跨学科技能。他们将获得数据科学工程研究生证书，并有望成为材料研究中数字化工具的坚定支持者。学员还将参加高中和两年制大学的外展和指导活动，以增强STEM领域的多样性。NSF研究培训(NRT)计划旨在鼓励开发和实施大胆的、具有潜在变革性的STEM研究生教育培训模式。该计划致力于通过创新的、基于证据的、与不断变化的劳动力和研究需求保持一致的综合实习生模式，在高度优先的跨学科或趋同研究领域对STEM研究生进行有效培训。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2). Tackling society’s grand challenges will require a workforce that is prepared to work to integrate knowledge from multiple disciplines, to work as a team, and to leverage the intellectual contributions of individuals from diverse backgrounds. However, employers often find that graduate students entering the workforce lack interdisciplinary training and an appreciation for data science. These scenarios necessitate new designs of STEM graduate education programs that promote interdisciplinary team building, integration of data science in solution methodologies, and exposure of graduate students to multicultural work environments. This National Science Foundation Research Traineeship (NRT) award to The University of Akron (UA) will support the first such traineeship program in Northeast Ohio for masters and doctoral students working at the interface of materials science and machine learning that will lead to the discovery of new materials and major advances in materials research. The traineeship will serve 40 M.S. and Ph.D. students including 20 funded M.S. and Ph.D. students recruited from diverse backgrounds including underrepresented minority groups and enrolled in graduate programs in polymer science and polymer engineering, mechanical engineering, and computer science.This NRT program seeks to identify and mitigate the knowledge gaps while providing data-driven answers for several cross-disciplinary research questions that are of interest to the broad materials research community. Examples include i) the tunability of a material modulus with temperature and the quality consistency of composite parts produced via additive manufacturing, ii) the dynamics of ions and mechanisms of ion transport in crystalline polymer domains as in batteries, iii) the molecular design of chemically recyclable polymers with tunable thermal and mechanical properties; iv) novel feature selection techniques in current machine learning tools to handle data from large complex polymeric systems; and v) efficient and systematic integration of large-scale heterogeneous data from multiple sources. The research will utilize a combination of experimental and numerical approaches, including molecular dynamics simulation, finite element analysis, polymer chemistry synthesis, additive manufacturing techniques and machine learning tools, to achieve the desired objectives. This project will create a scalable materials database that is integrable with existing polymer repositories and can be used to develop novel composite materials, molecular design rules for solid electrolytes with superior conductivity, and the design of new polymer materials that can be efficiently recycled. The trainees will develop strong interdisciplinary skills via courses and research work, workshops and seminars, laboratory rotations, internships at federal and industrial laboratories, and international exposure. They will receive a Data Science Engineering graduate certificate and are expected to become strong proponents of digitalization tools in materials research. The trainees will also participate in outreach and mentoring activities at high schools and two-year colleges to enhance diversity in STEM fields.The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new potentially transformative models for STEM graduate education training. The program is dedicated to effective training of STEM graduate students in high priority interdisciplinary or convergent research areas through comprehensive traineeship models that are innovative, evidence-based, and aligned with changing workforce and research needs.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.