Engineering Research Equipment Grant: Insitu Intelligent Materials Processing

工程研究设备资助：原位智能材料加工

• 批准号: 9212792
• 负责人: Vinod Sarin
• 金额: --
• 依托单位: Trustees of Boston University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1992
• 资助国家: 美国
• 起止时间: 1992-09-01 至 1995-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9212792&HistoricalAwards=false
• 关键词: Engineering; Research; Equipment; Grant; Insitu

A multi-processor platform will be used for the development of an insitu intelligent materials processing system. This system includes data acquisition, analysis and control of advanced material processing that can be conducted in real-time as the process is running. This equipment will be dedicated to support research in advancing several material processing problems including: (1) composition and structure control for laminated coatings, (2) real-time control for chemical vapor deposition processing, and (3) automated inspection of coatings. All these projects take a multi-disciplinary approach in developing a fundamental understanding and control of the principal phenomena of manufacturing and structure/property correlations which would assist in the engineering and development of new and novel materials capabilities. There is an urgent need in all segments of technology and industry for new and advanced materials. Custom tailoring of materials provides exciting new capabilities for all applications from advanced electronic devices to new structural materials. A major barrier to wide-spread use of this approach has been the difficulties in utilizing all the data and processing information needed to design and fabricate these materials. An intelligent materials processing capability will significantly aid the materials engineer in achieving these objectives.

多处理器平台将用于开发原位智能材料处理系统。该系统包括先进材料加工的数据采集、分析和控制，可以在过程运行时实时进行。该设备将致力于支持推进几个材料处理问题的研究，包括：（1）层压涂层的成分和结构控制，（2）化学气相沉积处理的实时控制，以及（3）涂层的自动检测。所有这些项目都采用多学科方法，对制造和结构/性能相关性的主要现象进行基本理解和控制，这将有助于新材料能力的工程和开发。技术和工业的所有部门都迫切需要新的和先进的材料。定制材料为从先进电子设备到新型结构材料的所有应用提供了令人兴奋的新功能。广泛使用这种方法的一个主要障碍是难以利用设计和制造这些材料所需的所有数据和处理信息。智能材料处理能力将大大帮助材料工程师实现这些目标。