Carbon nanotubes （CNTs） possess excellent electrical, thermal and mechanical properties. They are light in weight yet stronger than most of the other materials. They can be made both highly conductive and semi-condu...Carbon nanotubes （CNTs） possess excellent electrical, thermal and mechanical properties. They are light in weight yet stronger than most of the other materials. They can be made both highly conductive and semi-conductive. They can be made from nano-sized small catalyst particles and extend to tens of millimeters long. Since CNTs emerged as a hot topic in the early 1990s, numerous research efforts have been spent on the study of the various properties of this new material. CNTs have been proposed as alternative materials of potential excellence in a lot of applications such as electronics, chemical sensors, mechanical sensors/actuators and composite materials, etc. This paper reviews the use of CNTs particularly in electronics manufacturing and packaging field. The progresses of three most important applications, including CNT-based thermal interface materials, CNT-based interconnections and CNT-based cooling devices are reviewed. The growth and post-growth processing of CNTs for specific applications are introduced and the tai- loring of CNTs properties, i.e., electrical resistivity, thermal conductivity and strength, etc., is discussed with regard to specific application requirement. As the semiconductor industry is still driven by the need of getting smaller and faster, CNTs and the related composite systems as emerging new materials are likely to provide the solution to the future challenges as we make more and more complex electronics devices and systems.展开更多
This paper proposes a novel double regular- ization control （DRC） method which is used for tablet packaging image segmentation. Since the intensities of tablet packaging images are inhomogenous, it is difficult to m...This paper proposes a novel double regular- ization control （DRC） method which is used for tablet packaging image segmentation. Since the intensities of tablet packaging images are inhomogenous, it is difficult to make image segmentation. Compared to methods based on level set, the proposed DRC method has some advantages for tablet packaging image segmentation. The local re- gional control term and the rectangle initialization contour are first employed in this method to quickly segment un- even grayscale images and accelerate the curve evolution rate. Gaussian filter operator and the convolution calcula- tion are then adopted to remove the effects of texture noises in image segmentation. The developed penalty energy function, as regularization term, increases the constrained conditions based on the gradient flow conditions. Since the potential function is embedded into the level set of evo- lution equations and the image contour evolutions are bi- laterally extended, the proposed method further improves the accuracy of image contours. Experimental studies show that the DRC method greatly improves the computational efficiency and numerical accuracy, and achieves better results for image contour segmentation compared to other level set methods.展开更多
基金supported by EU programs‘‘Smartpower’’,‘‘Nanotec’’,‘‘Nanocom’’,‘‘Mercure’’the Swedish National Science Foundation (VR) under the project‘‘Onchip cooling using thermo-electrical device(Grant No.2009-5042)+2 种基金SSF program‘‘Scalable Nanomaterials and Solution Processable Thermoelectric Generators’’(Grant No.EM11-0002)the Chinese Ministry of Science and Technology for the International Science and Technology Cooperation program of China(Grant No.2010DFA14450)the National Natural Science Foundation of China(Grant No.51272153)
文摘Carbon nanotubes （CNTs） possess excellent electrical, thermal and mechanical properties. They are light in weight yet stronger than most of the other materials. They can be made both highly conductive and semi-conductive. They can be made from nano-sized small catalyst particles and extend to tens of millimeters long. Since CNTs emerged as a hot topic in the early 1990s, numerous research efforts have been spent on the study of the various properties of this new material. CNTs have been proposed as alternative materials of potential excellence in a lot of applications such as electronics, chemical sensors, mechanical sensors/actuators and composite materials, etc. This paper reviews the use of CNTs particularly in electronics manufacturing and packaging field. The progresses of three most important applications, including CNT-based thermal interface materials, CNT-based interconnections and CNT-based cooling devices are reviewed. The growth and post-growth processing of CNTs for specific applications are introduced and the tai- loring of CNTs properties, i.e., electrical resistivity, thermal conductivity and strength, etc., is discussed with regard to specific application requirement. As the semiconductor industry is still driven by the need of getting smaller and faster, CNTs and the related composite systems as emerging new materials are likely to provide the solution to the future challenges as we make more and more complex electronics devices and systems.
基金the Science and Technology Commission of Shanghai Municipality(Grant No.14YF1408600)the Shanghai Municipal Commission of Economy and Informatization under Shanghai Industry University Research Collaboration(Grant No.CXY-2013-71)+2 种基金the Natural Science Foundation of Shandong Province(Grant No.ZR2012FM008)the Science and Technology Development Program of Shandong Province(Grant No.2013GNC11012)the National Natural Science Foundation of China(Grant No.61100115)
文摘This paper proposes a novel double regular- ization control （DRC） method which is used for tablet packaging image segmentation. Since the intensities of tablet packaging images are inhomogenous, it is difficult to make image segmentation. Compared to methods based on level set, the proposed DRC method has some advantages for tablet packaging image segmentation. The local re- gional control term and the rectangle initialization contour are first employed in this method to quickly segment un- even grayscale images and accelerate the curve evolution rate. Gaussian filter operator and the convolution calcula- tion are then adopted to remove the effects of texture noises in image segmentation. The developed penalty energy function, as regularization term, increases the constrained conditions based on the gradient flow conditions. Since the potential function is embedded into the level set of evo- lution equations and the image contour evolutions are bi- laterally extended, the proposed method further improves the accuracy of image contours. Experimental studies show that the DRC method greatly improves the computational efficiency and numerical accuracy, and achieves better results for image contour segmentation compared to other level set methods.
