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

发现能够以低成本、环境友好和可扩展的方式产生和储存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）都经常受到同样的挑战的阻碍：研究人员没有能力处理来自实验室和高性能计算机的大量数据。这个国家科学基金会研究培训（NRT）奖给华盛顿大学将创建，测试和评估在清洁能源材料的数据密集型研究领域的研究生的新的培训模式。华盛顿大学的项目DIRECT：数据密集型研究支持清洁技术，通过培训新一代能源研究人员来应对这些挑战，这些研究人员有能力处理材料发现各个阶段产生的大量数据集。该项目预计将有72名学员（18名硕士和54名博士生），其中包括16名资助学员，来自化学工程，化学，材料科学工程，分子工程和以人为本的设计工程。DIRECT创建了一种新的培训模式，包括三个阶段：1）数据科学和先进能源材料的新研究生课程，2）基于项目的学习计划，以应用新技能并在团队环境中解决具有挑战性的真实的世界问题，以及3）利用跨越行业，国家实验室和几个国际合作伙伴的广泛网络的顶点体验。该研究的主题重点是电池和光电池的下一代材料。我们将使用植根于社会科学的人种学方法来理解为什么有些方法成功部署，而另一些则没有，并学习如何以情境化的方式将数据科学工具应用于材料科学，以最大限度地提高可用性。培训的项目学习部分将为研究生提供教授和实践领导和管理技能的机会，这是大多数受训人员无法获得的独特机会。DIRECT学员将为许多需要数据科学培训的新职业选择做好准备，并将为在21世纪世纪经济中蓬勃发展所需的技能做好准备。该项目还将提供关于基于项目的学习在研究生教育中获得先进技术技能和学科知识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，新的潜在变革性模型，用于STEM研究生教育培训。该培训轨道致力于在高优先级的跨学科研究领域的STEM研究生的有效培训，通过全面的培训模式，是创新的，以证据为基础，并与不断变化的劳动力和研究需求保持一致。

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.