Early Testable Addressable Logic (ETAL) Test Structure: Showcasing the use of an Alternate Logic Yield Learning Test Structure for Technology Development

Author(s):  
Ishtiaq Ahsan ◽  
Shahrukh Khan ◽  
Joerg Winkler ◽  
Kannan Sekar ◽  
Neerja Bawaskar ◽  
...  
2018 ◽  
Author(s):  
Seng Nguon Ting ◽  
Hsien-Ching Lo ◽  
Donald Nedeau ◽  
Aaron Sinnott ◽  
Felix Beaudoin

Abstract With rapid scaling of semiconductor devices, new and more complicated challenges emerge as technology development progresses. In SRAM yield learning vehicles, it is becoming increasingly difficult to differentiate the voltage-sensitive SRAM yield loss from the expected hard bit-cells failures. It can only be accomplished by extensively leveraging yield, layout analysis and fault localization in sub-micron devices. In this paper, we describe the successful debugging of the yield gap observed between the High Density and the High Performance bit-cells. The SRAM yield loss is observed to be strongly modulated by different active sizing between two pull up (PU) bit-cells. Failure analysis focused at the weak point vicinity successfully identified abnormal poly edge profile with systematic High k Dielectric shorts. Tight active space on High Density cells led to limitation of complete trench gap-fill creating void filled with gate material. Thanks to this knowledge, the process was optimized with “Skip Active Atomic Level Oxide Deposition” step improving trench gap-fill margin.


2003 ◽  
Vol 43 (9-11) ◽  
pp. 1383-1387 ◽  
Author(s):  
Th. Nirschl ◽  
M. Ostermayr ◽  
A. Olbrich ◽  
D. Vietzke ◽  
M. Omer ◽  
...  

2015 ◽  
Vol 28 (4) ◽  
pp. 474-479 ◽  
Author(s):  
Ishtiaq Ahsan ◽  
Carl Schiller ◽  
Fred Towler ◽  
Zhigang Song ◽  
Robert Wong ◽  
...  

Author(s):  
Zhigang Song ◽  
Felix Beaudoin ◽  
Stephen Lucarini ◽  
Stephen Wu ◽  
Yunyu Wang ◽  
...  

Abstract With the microelectronic technology progresses in nanometer realm, like SRAM, logic circuits and structures are also becoming dense and more sensitive to process variation. Logic failures may have different root causes from SRAM failure. If these technology weak points for logic circuits are not detected and resolved during the technology development stage, they will greatly affect the product manufacturing yield ramp, leading to longer time of design to market. In this paper, we present a logic yield learning methodology based on an inline logic vehicle, which includes several scan chains of different latch types representative of product logic. Failure analysis for the low yield wafers had revealed several killer defects associated with logic circuits. A few examples of the systematic failures unique to logic circuits will be presented. In combination with SRAM yield learning, logic yield learning makes the technology development more robust thus improving manufacturability.


Author(s):  
Felix Beaudoin ◽  
Zhigang Song ◽  
Stephen Lucarini ◽  
Thomas F. Mechler ◽  
Stephen Wu ◽  
...  

Abstract This paper presents the successful use of the novel inline product-like logic vehicle (PATO) during the last technology development phases of IBM's 22nm SOI technology node. It provides information on the sequential PATO inline test flow, commonality analysis procedure, and commonality signature trending. The paper presents examples of systematic defects uniquely captured by the product-like back end of the line layout. Moreover, this complex logic vehicle also uncovered a rich Pareto of more than 20 types of systematic and random defect mechanisms across the front end of the line, the middle end of the line, and the back end of the line. And more importantly, the non-defect found rate was kept below 20%. This achievement was possible by: leveraging high volume inline test ATPG scan fail data through the novel commonality analysis approach; and selecting the highest ATPG confidence defects representing a known commonality signature to physical failure analysis.


Author(s):  
Xu Ouyang ◽  
David Riggs ◽  
Ishtiaq Ahsan ◽  
Oliver D. Patterson ◽  
Dallas M. Lea ◽  
...  

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