Statistical Manufacturing Model of Printing TechnologySource: Journal of Electronic Packaging:;2013:;volume( 135 ):;issue: 001::page 11004DOI: 10.1115/1.4007450Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: There has been an evident increase in the demand for accurate and complex patterns for particles used in microsized electronic devices. Direct printing technology has been promoted as a solution for these needs, as the development of this technology provides both economical and environmental benefits, as well as being a time and energy saving process. Research in the field of printing technologies is still in the initial stages, involving the study of physical and chemical properties of printing materials. There are several methods currently using direct printing methods: microdispensing deposition write (MDDW), maskless mesoscale materials deposition (M3D), and inkjet printing. This study explores the direct printing methods of sequential and randomized printing associated with MDDW, M3D, and inkjet printing using computer simulations compared with actual experimentations. Sequential printing involves depositing particles onto the substrate in a specific order based on particle size. This method is associated with MDDW, where a relatively high viscous ink is dispensed onto the substrate so that particle sizes maintain an order in relation to one another, effectively producing a higher packing factor. Randomized printing involves the dispensing of various sizes of particles onto the substrate in a random order, as in inkjet printing. With this process, the probability of obtaining an efficient packing factor is unlikely and decreases even more with particle size. Therefore, the monolayer method, involving the deposition of individual particles, was developed to increase the packing factor when using the inkjet process. The results presented in this study proved that monolayering methods coincide with the projections predicted by the computer simulation. Sequential packing (MDDW) provides a shorter and higher range of packing factors than that of random packing sequences (ink jet); thus showing sequential packing to be the more efficient method. Sequential packing is closely related to the printing of high viscosity ink because of the higher packing factor that this method provides. An ink with increased viscosity allows for better conductivity which is essential in the development of improved nanoprinting technologies. This study provides evidence for the most efficient means of increasing the packing factor of particles; these methods offer the opportunity for technological advancement and commercialization of nanoprinting materials.
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| contributor author | Kim, Nam | |
| contributor author | Luna, Sarah | |
| contributor author | Lee, Jung | |
| contributor author | Jeong, Tae | |
| date accessioned | 2017-05-09T00:57:37Z | |
| date available | 2017-05-09T00:57:37Z | |
| date issued | 2013 | |
| identifier issn | 1528-9044 | |
| identifier other | ep_135_1_011004.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/151400 | |
| description abstract | There has been an evident increase in the demand for accurate and complex patterns for particles used in microsized electronic devices. Direct printing technology has been promoted as a solution for these needs, as the development of this technology provides both economical and environmental benefits, as well as being a time and energy saving process. Research in the field of printing technologies is still in the initial stages, involving the study of physical and chemical properties of printing materials. There are several methods currently using direct printing methods: microdispensing deposition write (MDDW), maskless mesoscale materials deposition (M3D), and inkjet printing. This study explores the direct printing methods of sequential and randomized printing associated with MDDW, M3D, and inkjet printing using computer simulations compared with actual experimentations. Sequential printing involves depositing particles onto the substrate in a specific order based on particle size. This method is associated with MDDW, where a relatively high viscous ink is dispensed onto the substrate so that particle sizes maintain an order in relation to one another, effectively producing a higher packing factor. Randomized printing involves the dispensing of various sizes of particles onto the substrate in a random order, as in inkjet printing. With this process, the probability of obtaining an efficient packing factor is unlikely and decreases even more with particle size. Therefore, the monolayer method, involving the deposition of individual particles, was developed to increase the packing factor when using the inkjet process. The results presented in this study proved that monolayering methods coincide with the projections predicted by the computer simulation. Sequential packing (MDDW) provides a shorter and higher range of packing factors than that of random packing sequences (ink jet); thus showing sequential packing to be the more efficient method. Sequential packing is closely related to the printing of high viscosity ink because of the higher packing factor that this method provides. An ink with increased viscosity allows for better conductivity which is essential in the development of improved nanoprinting technologies. This study provides evidence for the most efficient means of increasing the packing factor of particles; these methods offer the opportunity for technological advancement and commercialization of nanoprinting materials. | |
| publisher | The American Society of Mechanical Engineers (ASME) | |
| title | Statistical Manufacturing Model of Printing Technology | |
| type | Journal Paper | |
| journal volume | 135 | |
| journal issue | 1 | |
| journal title | Journal of Electronic Packaging | |
| identifier doi | 10.1115/1.4007450 | |
| journal fristpage | 11004 | |
| journal lastpage | 11004 | |
| identifier eissn | 1043-7398 | |
| tree | Journal of Electronic Packaging:;2013:;volume( 135 ):;issue: 001 | |
| contenttype | Fulltext |