DocumentCode :
980768
Title :
Analysis and characterization of device variations in an LSI chip using an integrated device matrix array
Author :
Ohkawa, Shin-Ichi ; Aoki, Masakazu ; Masuda, Hiroo
Author_Institution :
Semicond. Technol. Acad. Res. Center, Yokohama, Japan
Volume :
17
Issue :
2
fYear :
2004
fDate :
5/1/2004 12:00:00 AM
Firstpage :
155
Lastpage :
165
Abstract :
For future large-scale integration design technology, the device matrix array (DMA), which precisely evaluates within-die variation in device parameters, has been developed. The DMA consists of a 14-by-14 array of common units. The unit size is 240 by 240 μm, and each unit contains 148 measurement elements (52 transistors, 30 capacitors, 51 resistors, and 15 ring oscillators). The element selection and precise measurement are achieved with low parasitic resistance measurement buses and leakage-controlled switching circuits, which allow the measurement accuracy for a transistor, resistor, or capacitor of 90 pA, 11 mΩ, and 23 aF, respectively, in the 3σ range. The ability to obtain 29 008 samples from a chip enables statistical analysis of the variation in 148 elements of each chip with 240-μm spatial resolution. This high resolution and large sample number allows us to precisely decompose the data into systematic and random variation parts with newly developed fourth-order polynomial fitting. Our methodology has been verified using a test chip fabricated by a 130-nm CMOS process with a 100-nm physical gate length and five Cu interconnect layers. In MOSFETs, the random part was dominant and indicated a certain σ value in every chip. In the case of the interconnect layers, the random and systematic parts of the resistance and the capacitance indicated variance fluctuations. By chip, by item, by size, by structure, random or systematic, the σ values of each variation show inconsistency which we believe is attributable to the Cu process. The correlation coefficients of systematic part between device element and ring oscillator frequency shown very high value (0.87-0.98), and those of a random part were low enough (-0.10-0.22) to prove the accuracy of decomposition.
Keywords :
CMOS integrated circuits; MIS structures; MOSFET; capacitance; capacitors; copper; integrated circuit interconnections; large scale integration; oscillators; resistors; switching circuits; 100 nm; 130 nm; 23 aF; 240 micron; CMOS process; Cu; Cu interconnect layers; LSI chip; MOSFET; capacitance; capacitors; chip enables statistical analysis; device matrix array; fourth order polynomial; integrate device matrix array; leakage-controlled switching circuits; oscillator frequency; oscillators; parasitic resistance; resistors; test chip; transistors; Electrical resistance measurement; Integrated circuit interconnections; Large scale integration; MOSFETs; Measurement units; Resistors; Ring oscillators; Semiconductor device measurement; Size measurement; Spatial resolution; Correlation analysis; device variation; leakage control; parameter measurement; polynomial fitting; statistical analysis; switching matrix; variance characteristic; variance decomposition; within-die variation;
fLanguage :
English
Journal_Title :
Semiconductor Manufacturing, IEEE Transactions on
Publisher :
ieee
ISSN :
0894-6507
Type :
jour
DOI :
10.1109/TSM.2004.827001
Filename :
1296719
Link To Document :
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