EAGER: A Longitudinal Study of Knowledge Diffusion and Societal Impact of Nanomanufacturing Research & Development: Harnessing Data for Science and Engineering

EAGER：纳米制造研究的知识传播和社会影响的纵向研究

基本信息

批准号：
1832926
负责人：
Hsinchun Chen
金额：
$ 15.84万
依托单位：
University of Arizona
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2018
资助国家：
美国
起止时间：
2018-08-01 至 2021-07-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1832926&HistoricalAwards=false
关键词：
EAGER Longitudinal Study Knowledge Diffusion

项目摘要

Since the National Nanotechnology Initiative was implemented in 2000, significant progress has been made in understanding the unique physical phenomena that occur at the nano-scale and in designing and fabricating new nano-scale materials, structures, devices and systems. To realize the benefits to the nation of these advances in nanotechnology, however, advances must also be made in nanomanufacturing, and these advances must translate, in turn, into production by industry. This EArly-concept Grant for Exploratory Research (EAGER) project will investigate the knowledge diffusion and societal impact of nanomanufacturing research, using advanced data analytics frameworks. The study results are expected to inform government, industry, and researchers in identifying research gaps and how resources and investments could be directed to address obstacles to scaling the most promising nanotechnology discovery to industrial production. The project is highly exploratory and hence suitable for the EAGER program. The research results will be broadly distributed. The project responds to the NSF Big Idea--Harnessing Data for 21st Century Science and Engineering.This project develops new analytical models and frameworks to study and analyze the outputs of research in nanomanufacturing. Nanotechnology studies are mostly high-level industry-wide reviews based on smaller-scale survey and are mostly available to members. This project is data science-driven, based on existing large databases and state-of-the-art data analytics including journal articles, patents, licenses and technology transfer datasets and made publicly available. The project develops a framework that systematically collects relevant data generated in the past 15-20 years from university technology transfer offices, public news databases, patents and publications, and analyzes the influence of research investments and specific projects on knowledge diffusion and its commercial impact. From the data, the project develops a novel, scalable text mining, topic modeling, trend analysis, and network analysis to quantify, evaluate, and visualize each research effort's long-term knowledge diffusion. The expected outcomes are to understand, (1) nanomanufacturing knowledge diffusion path from academic publications to patents to commercialization, (2) impact of federal investment in nanomanufacturing research in facilitating long-term knowledge diffusion, and (3) the difference between large-scale collaborative projects and small-scale individual projects facilitating long-term knowledge diffusion. The broad set of analytical techniques developed from this research are expected to further advance the scientific use of these methods.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.

自2000年实施国家纳米技术计划以来，在理解纳米级发生的独特物理现象以及设计和制造新的纳米级材料、结构、器件和系统方面取得了重大进展。然而，为了实现纳米技术进步给国家带来的好处，纳米制造也必须取得进步，而这些进步又必须转化为工业生产。这个早期概念探索性研究资助 (EAGER) 项目将利用先进的数据分析框架来研究纳米制造研究的知识传播和社会影响。研究结果预计将为政府、行业和研究人员提供信息，帮助他们确定研究差距，以及如何引导资源和投资来解决将最有前途的纳米技术发现扩展到工业生产的障碍。该项目具有高度探索性，因此适合 EAGER 计划。研究成果将广泛传播。该项目响应了 NSF 大理念——利用数据促进 21 世纪科学与工程。该项目开发了新的分析模型和框架来研究和分析纳米制造的研究成果。纳米技术研究大多是基于小规模调查的高水平全行业审查，并且大部分可供会员使用。该项目由数据科学驱动，基于现有的大型数据库和最先进的数据分析，包括期刊文章、专利、许可证和技术转让数据集，并公开发布。该项目开发了一个框架，系统地收集过去15-20年从大学技术转让办公室、公共新闻数据库、专利和出版物产生的相关数据，并分析研究投资和具体项目对知识传播的影响及其商业影响。该项目根据数据开发了一种新颖的、可扩展的文本挖掘、主题建模、趋势分析和网络分析，以量化、评估和可视化每项研究工作的长期知识传播。预期结果是了解：(1) 纳米制造知识从学术出版物到专利再到商业化的传播路径，(2) 联邦投资纳米制造研究对促进长期知识传播的影响，以及 (3) 大规模纳米制造知识传播与大规模纳米制造知识传播之间的差异。合作项目和小规模个人项目促进长期知识传播。这项研究开发的广泛的分析技术预计将进一步促进这些方法的科学应用。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。