碳纳米材料生产过程建模及过程分析与控制研究

Due to lots of excellent properties, Carbon nanotubes (CNTs) have the potential to replace lots of traditional materials. However, the mass production of CNTs have not been achieved because of its unstable synthesis process. To address the issue, this research first constructs a measurement model to describe the relationship between the key quality index of interest which is usually hard to measure and the micro index which is easy to obtain. Then the research decrease the dimension of problem by building a characterization model for micro index which extracting the lower-dimensional characteristic parameters from the high-dimensional spatial micro index. After that, a process model has been proposed to relate the characteristic parameters to control variables, which is followed by the process controller based on the process model. In this research, the measurement model is built by capturing the spatial properties of the relationship between two types of indices. The characterization model is constructed based on the spatial distribution of micro index. Different types and sources of information, such as engineering model, expert opinions as well as field data, have been combined by Bayesian framework to build the process model. With the process controller, all the three models mentioned above have integrated the key quality index, micro index, characteristic parameters as well as the process variables to become a set of analysis and quantitative tool which focuses on the measurement, characterization, process modeling and control for CNTs. This project will be helpful to the achievement and quality control of the mass production of CNTs, and has the potential to be applied for other nano-materials.

碳纳米管以其优异的性能从而具有巨大的应用前景。但由于其生长过程尚不稳定，还未实现工业化生产。针对此现状，本研究从关键质量指标入手，建立其与易测量的微观指标之间的测量模型；其次通过建立表征模型提取微观指标的空间特征，将高维空间指标转化为低维的特征参数以便于提高后续模型及控制算法的稳定性；然后建立特征参数与控制参数之间的生长过程模型；最后基于过程模型设计控制算法。本研究基于关键质量指标和微观指标之间相关性的空间分布建立了测量模型，考虑了微观指标的空间分布建立了表征模型，利用贝叶斯框架综合了工程知识、专家意见以及实验数据等多类型信息建立了生长过程模型；将碳纳米管的关键质量指标、微观指标、特征参数以及生长过程参数有机的联系在一起，通过控制算法将其融合成针对碳纳米管测量、表征、过程建模及控制的完整分析工具。本研究将有助于碳纳米管工业化生产的实现，同时对其他纳米材料的研究也将有一定的借鉴意义。

碳纳米管具有巨大的应用前景。然其生长过程不稳定，未实现工业化生产。对此，本项目从关键质量指标入手，建立其与易测微观指标间的测量模型；通过建立表征模型提取微观指标的空间特征，将高维空间指标转化为低维的特征参数；然后建立特征参数与控制参数间的生长过程模型；最后基于过程模型设计控制算法。该项目与清华大学纳米中心及天津富源原创合作，将该成果应用于纳米材料的制备中，取得了良好的实践成果。目前已发表4篇文章，另有1篇文章在撰写中，其中3篇文章发表在SCI核心期刊上。“A Spatial Calibration Model for Nanotube Film Quality Prediction”基于关键质量指标和微观指标之间相关性的空间分布建立了测量模型，达到降低测量成本和提高测量精度的目的。“A physical-statistical model for the growth process of Carbon Nanotubes”结合了碳纳米管生长过程中的物理信息以及实验数据等多类型信息建立了一个表征模型，将碳纳米管的关键质量指标与生长过程参数有机的联系在一起。“A Run-to-Run Profile Control Algorithm for Improving the Flatness of Nano-Scale Products”提出了一种融合Run-to-Run控制技术和形态监视技术的形态控制算法，通过使用该算法，形成针对碳纳米管测量、表征、过程建模及控制的完整分析工具。“An engineering-statistical model for synthesis process of nanomaterials” 将生长过程分为趋势项和残差项，建立了基于工程统计的生长模型。项目通过王鑫在美国佐治亚理工学院研究交流半年，与J.C. Lu 教授的课题组建立了合作，通过范孟琪与南加州大学黄强教授建立了合作关系并将赴美继续该研究，说明本项目的研究水平与国际研究是齐头并进的。和传统的材料制作过程不同，碳纳米材料存在着测量系统精度低、生产过程波动大的问题。目前对纳米材料的研究集中于其生长机理的研究，而对其制备过程的质量控制研究很少。本研究从质量控制出发，建立了针对纳米材料生产过程的完整的研究体系，使得制备质量和生产过程控制进入研究视野，对类似的研究和大规模制备有借鉴意义。