Skip Nav Destination
Close Modal
Update search
Filter
- Title
- Authors
- Author Affiliations
- Full Text
- Abstract
- Keywords
- DOI
- ISBN
- EISBN
- Issue
- ISSN
- EISSN
- Volume
- References
Filter
- Title
- Authors
- Author Affiliations
- Full Text
- Abstract
- Keywords
- DOI
- ISBN
- EISBN
- Issue
- ISSN
- EISSN
- Volume
- References
Filter
- Title
- Authors
- Author Affiliations
- Full Text
- Abstract
- Keywords
- DOI
- ISBN
- EISBN
- Issue
- ISSN
- EISSN
- Volume
- References
Filter
- Title
- Authors
- Author Affiliations
- Full Text
- Abstract
- Keywords
- DOI
- ISBN
- EISBN
- Issue
- ISSN
- EISSN
- Volume
- References
Filter
- Title
- Authors
- Author Affiliations
- Full Text
- Abstract
- Keywords
- DOI
- ISBN
- EISBN
- Issue
- ISSN
- EISSN
- Volume
- References
Filter
- Title
- Authors
- Author Affiliations
- Full Text
- Abstract
- Keywords
- DOI
- ISBN
- EISBN
- Issue
- ISSN
- EISSN
- Volume
- References
NARROW
Format
Subjects
Article Type
Volume Subject Area
Date
Availability
1-4 of 4
Grigore Moldovan
Close
Follow your search
Access your saved searches in your account
Would you like to receive an alert when new items match your search?
Sort by
Proceedings Papers
ISTFA2023, ISTFA 2023: Conference Proceedings from the 49th International Symposium for Testing and Failure Analysis, 427-431, November 12–16, 2023,
Abstract
View Paper
PDF
Key improvements to data acquisition, visualization and analysis are presented for Electrical Failure Analysis (EFA). Multi-channel image acquisition is introduced, where every nanoprobe is used for simultaneous imaging, in combination with color coding either by probe or by current. This new approach improves visualization of new device technologies with increasing three-dimensional complexity, in particular for overlapping structures and fields. Further, this new multichannel method opens opportunities for image mixing to improve data quality and signal interpretation.
Proceedings Papers
ISTFA2022, ISTFA 2022: Conference Proceedings from the 48th International Symposium for Testing and Failure Analysis, 277-283, October 30–November 3, 2022,
Abstract
View Paper
PDF
The Electron Beam Induced Resistance Change (EBIRCH) technique is becoming more popular for localization of defects in Electrical Failure Analysis (EFA). Whilst EBIRCH is clear and straightforward in the procedure that must be followed for localization, it does not provide a direct understanding of the fundamental origin of its signal. This contribution addresses this significant shortfall in the technique, proposing a few basic experimental steps to be added to the technique in continuation of localization, with the principal aim of interrogating the physical origin of signal.
Proceedings Papers
ISTFA2018, ISTFA 2018: Conference Proceedings from the 44th International Symposium for Testing and Failure Analysis, 353-357, October 28–November 1, 2018,
Abstract
View Paper
PDF
This work presents advanced resistance mapping techniques based on Scanning Electron Microscopy (SEM) with nanoprobing systems and the related embedded electronics. Focus is placed on recent advances to reduce noise and increase speed, such as integration of dedicated in situ electronics into the nanoprobing platform, as well as an important transition from current-sensitive to voltagesensitive amplification. We show that it is now possible to record resistance maps with a resistance sensitivity in the 10W range, even when the total resistance of the mapped structures is in the range of 100W. A reference structure is used to illustrate the improved performance, and a lowresistance failure case is presented as an example of analysis made possible by these developments.
Proceedings Papers
ISTFA2014, ISTFA 2014: Conference Proceedings from the 40th International Symposium for Testing and Failure Analysis, 156-159, November 9–13, 2014,
Abstract
View Paper
PDF
Electron Beam Induced Current (EBIC) characterization is unique in its ability to provide quantitative high-resolution imaging of electrical defects in solar cells. In particular, EBIC makes it possible to image electrical activity of single dislocations in a Dual-Beam Focused Ion Beam (FIB) Scanning Electron Microscope (SEM), to cut and lift out a micro-specimen containing a particular dislocation, and then transfer it for further structural or chemical analysis. As typical solar cell material presents a complex array of defects, it is important to observe statistical variations within a sample and select key sites for analysis. This paper describes a method for automated defect identification and characterization, and shows an application to multi-crystalline silicon (mc-Si) solar cell wafers selected from different heights along the manufactured ingot. Information presented here includes the experimental setup for data acquisition, as well as the basic algorithms used for identification and extraction of dislocation contrast.