NRT-DESE: Data Intensive Research Enabling Clean Technologies (DIRECT)

发现将以低成本、环境友好和可扩展的方式产生和存储可再生能源的新材料可能是当今社会面临的最重要的技术挑战。这一科学过程的所有阶段(设计、合成和表征)都经常受到相同挑战的阻碍：研究人员没有准备好处理来自我们实验室和高性能计算机的海量数据。这项授予华盛顿大学的国家科学基金会研究培训(NRT)奖将为清洁能源材料数据密集研究领域的研究生创建、测试和评估一种新的培训模式。华盛顿大学的DIRECT项目：数据密集研究促进清洁技术，通过培训新一代能源研究人员来应对这些挑战，他们有能力处理材料发现的所有阶段产生的海量数据集。该项目预计招收72名学员(18名硕士研究生和54名博士生)，其中包括16名资助学员，来自化学工程、化学、材料科学与工程、分子工程和以人为中心的设计与工程。DIRECT创建了一种新的培训模式，包括三个阶段：1)在数据科学和能源先进材料的结合点进行新的研究生课程工作；2)基于项目的学习计划，在基于团队的环境中应用新技能并致力于挑战现实世界的问题；以及3)利用横跨行业、国家实验室和几个国际合作伙伴的广泛网络的顶峰体验。研究的主题重点是电池和光伏的下一代材料。我们将使用植根于社会科学的民族志方法来理解为什么一些方法被成功部署，而另一些方法则没有，并学习如何将数据科学工具以上下文的方式应用于材料科学，以最大限度地提高可用性。实习生培训的基于项目的学习部分将为研究生提供教授和练习领导力和管理技能的机会，这是大多数实习生否则不会获得的独特机会。直接受训人员将为许多需要数据科学培训的新职业选择做好准备，并将准备好在21世纪的经济中蓬勃发展所需的技能。该项目还将提供以项目为基础的学习在获取研究生教育高级技术技能和学科知识方面的有效性的独特信息。NSF研究培训(NRT)计划旨在鼓励开发和实施大胆的、具有潜在变革意义的STEM研究生教育培训模式。培训路径致力于通过创新的、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培训模式，在高度优先的跨学科研究领域对STEM研究生进行有效培训。

Discovering new materials that will generate and store renewable energy in a low cost, environmentally benign, and scalable fashion is perhaps the most important technological challenge facing society today. All phases of this scientific process (design, synthesis, and characterization) are routinely stymied by the same challenge: researchers are not equipped to handle the deluge of data coming from our labs and high performance computers. This National Science Foundation Research Traineeship (NRT) award to the University of Washington will create, test and evaluate a new training model for graduate students in the area of data intensive research in materials for clean energy. The University of Washington program, DIRECT: Data Intensive Research Enabling Clean Technologies, addresses these challenges by training a new generation of energy researchers who are equipped to handle the massive data sets arising from all stages of materials discovery. This project anticipates 72 trainees (18 MS and 54 PhD students), including 16 funded trainees, from Chemical Engineering, Chemistry, Materials Science & Engineering, Molecular Engineering and Human Centered Design & Engineering. DIRECT creates a new training modality comprised of three phases: 1) new graduate coursework at the nexus of data science and advanced materials for energy, 2) a project-based learning scheme to apply new skills and work on challenging real world problems in a team-based setting, and 3) capstone experiences that leverage broad networks spanning industry, national labs and several international partners. The thematic focus of the research is next-generation materials for batteries and photovoltaics. We will use an ethnographic approach rooted in the social sciences to understand why some methods are successfully deployed while others are not, and learn how to apply data science tools in a contextualized manner to materials science to maximize usability. The project-based learning component of the traineeship will provide graduate students the chance to teach and practice leadership and management skills, a unique opportunity most trainees would not otherwise receive. DIRECT trainees will be equipped for many new career options that require data science training and will be prepared with the skills needed to thrive in the economy of the 21st century. The project will also provide unique information about the effectiveness of project-based learning in the acquisition of advanced technical skills and disciplinary knowledge in graduate education.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 Traineeship Track is dedicated to effective training of STEM graduate students in high priority interdisciplinary research areas, through the comprehensive traineeship model that is innovative, evidence-based, and aligned with changing workforce and research needs.