scholarly journals Laser Erasing and Rewriting of Flexible Copper Circuits

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Xingwen Zhou ◽  
Wei Guo ◽  
Peng Peng

AbstractIntegrating construction and reconstruction of highly conductive structures into one process is of great interest in developing and manufacturing of electronics, but it is quite challenging because these two involve contradictive additive and subtractive processes. In this work, we report an all-laser mask-less processing technology that integrates manufacturing, modifying, and restoring of highly conductive Cu structures. By traveling a focused laser, the Cu patterns can be fabricated on the flexible substrate, while these as-written patterns can be selectively erased by changing the laser to a defocused state. Subsequently, the fresh patterns with identical conductivity and stability can be rewritten by repeating the writing step. Further, this erasing–rewriting process is also capable of repairing failure patterns, such as oxidation and cracking. Owing to the high controllability of this writing–erasing–rewriting process and its excellent reproducibility for conductive structures, it opens a new avenue for rapid healing and prototyping of electronics.

Author(s):  
Klaus-Ruediger Peters

Differential hysteresis processing is a new image processing technology that provides a tool for the display of image data information at any level of differential contrast resolution. This includes the maximum contrast resolution of the acquisition system which may be 1,000-times higher than that of the visual system (16 bit versus 6 bit). All microscopes acquire high precision contrasts at a level of <0.01-25% of the acquisition range in 16-bit - 8-bit data, but these contrasts are mostly invisible or only partially visible even in conventionally enhanced images. The processing principle of the differential hysteresis tool is based on hysteresis properties of intensity variations within an image.Differential hysteresis image processing moves a cursor of selected intensity range (hysteresis range) along lines through the image data reading each successive pixel intensity. The midpoint of the cursor provides the output data. If the intensity value of the following pixel falls outside of the actual cursor endpoint values, then the cursor follows the data either with its top or with its bottom, but if the pixels' intensity value falls within the cursor range, then the cursor maintains its intensity value.


PIERS Online ◽  
2010 ◽  
Vol 6 (2) ◽  
pp. 105-108 ◽  
Author(s):  
Haipeng Lu ◽  
Jing Yang ◽  
Longjiang Deng

2020 ◽  
Vol 6 (1) ◽  
pp. 039
Author(s):  
Trie Omitha Purba ◽  
Suparmi Suparmi ◽  
Dahlia Dahlia

The study aimed to determine the effect of rebon shirmp (mysis relicta) protein hydrolisate fortification to the sago noodles and to observe the characteristics of the sago noodles produced. The research was carried on in February – April 2019 in the  Laboratory of Fish Processing Technology, Integrated Laboratories, and the Fisheries and Marine Chemistry Laboratories at the Universitas Riau. The method used was the experimental method, designedas a non-factorial complete randomized design. The treatment conducted was addingof rebon shrimp protein hydrolysate at 4 level concentrations (0%, 5%, 10% dan 15%). The variables assessed were the quality of organoleptic (appearance, texture, odor, flavor) and the proximate composition. The results showed that the proteinhydrolysate of rebon shrimp at concentration of 15% was the best treatment and in accordance to the quality standards of dried noodles (SNI 01-2974-1996), indicated bythe highest organoleptic qualityof the dried noodles produced, including: the appearance that was brown, less attractive, whole, less neat; the texture that was dry and compact; the aroma that was quite fragrant, spesific rebon shrimp; and the taste that was quite tasty and shrimp flavored. The proximate composition ofthe best product was presented by the content of moisture, ash, fat, protein, and carbohydrate at 7.55%,1.02%, 0.17%, 16.76%, and 74.49%, respectively.Keywords: Hydrolysate protein, rebon shrimp, sago noodles


Author(s):  
T. Zanon ◽  
W. Maly

Abstract Building a portfolio of deformations is the key step for building better defect models for the test and yield learning domain. A viable approach to achieve this goal is through geometric characterization and classification of failure patterns found on memory fail bitmaps. In this paper, we present preliminary results on how to build such a portfolio of deformations for an IC technology of interest based on a fail bitmap analysis study conducted on large, modern SRAM memory products.


Author(s):  
Katja Reiter ◽  
Hans Bundgaard

Abstract Based on the requirements regarding target, reproducibility, and specimen surface quality, an automatic system for controlled material removal and target preparation has been developed. The tool is for metallographic failure analysis of electric and microelectronic components, and provides an accuracy of 5 micrometer. This article presents details of sample preparation and device evaluation methods. The images presented show typical objects of examination in the analysis of microstructures and materials in the electronics packaging industry with brief comments. For automatically controlled material removal and preparation, the tool offers alignment and measuring of the sample prior to the preparation. The desired preparation layers were achieved precisely and reproducibly with several specimens of the same kind. The automatic preparation system allowed the preparation of critical samples within a short time, with high precision and with excellent reproducibility.


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