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Superconducting Technology Assessment - nitrd

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B. Yield<br />

Yield measurements are an important part of any manufacturing<br />

process [95]. Several parts, including wafer fabrication<br />

yield, parametric test yield, functional test yield, and packaging<br />

yield factor in overall product yield. Of these, wafer<br />

fabrication yield is the easiest to measure. Parametric test<br />

yield is being addressed through the use of standard test vehicles<br />

as described previously. Quantitative estimates of functional<br />

test yield may be difficult because it requires enough<br />

resources to test a large quantity of circuits of a given type<br />

to establish reliable yield statistics. Ideally, measured circuit<br />

yield can be correlated with parametric test yield and used<br />

to project yield of more complex circuits [96]–[98]. Testing<br />

at speed is also important because margins may be strong<br />

functions of frequency over some range. Packaging yield is<br />

important in the production of products or systems and will<br />

become more important as the superconductor electronics<br />

community fields more products based on active circuits.<br />

Although parameter variations are known, little work<br />

has been done in superconductor electronics in the area of<br />

yield assessment. Since it is difficult to determine circuit<br />

yield from measurements of discrete device components,<br />

one would ideally develop a product-oriented yield vehicle<br />

that will allow a better understanding of the process yield,<br />

to correlate its yield with PCM measurements of spreads,<br />

etc., and to predict yield on future products. Several yield<br />

vehicles such as RAM [99] and shift registers [91], [98] have<br />

been developed to provide this type of information.<br />

In the absence of more extensive yield data, one can nevertheless<br />

make projections about the effects of defect density<br />

and its effect on die yield by leveraging the yield models<br />

developed for the semiconductor industry. These models are<br />

directly applicable to superconductor electronics because the<br />

fabrication processes are similar. The relationship between<br />

yield and defect density is based on the model<br />

AD , where is the defect sensitive area, is defect<br />

density, and describes how the defects tend to cluster on<br />

the wafer [95]. For a given defect density, smaller area chips<br />

will have a higher yield than larger area chips. Estimates for<br />

present defect densities are 1 or 2 defects/cm and 0.5<br />

(defects clustered toward the edges of the wafer). Based on<br />

this model, it is clear that defect density is an important consideration<br />

for high yield. NGST concluded, after a major effort<br />

to reduce gross visual defects, that most defects were<br />

induced by process tools and not by the fabrication facilities<br />

that were already operating at class 10 or better. Further<br />

reductions in defect density would require cleaner process<br />

tools.<br />

VI. PROCESS BENCHMARKING: STATIC DIVIDER<br />

PERFORMANCE<br />

The maximum operating speed of the toggle flip-flop<br />

(TFF) has become the standard measure or benchmark used<br />

to compare superconductor integrated circuit fabrication<br />

processes [18], [100], [101]. The TFF also has been used<br />

to compare the performance of semiconductor processes<br />

Fig. 14. Maximum reported TFF divider speed � versus<br />

t for trilayers from HYPRES, NGST, and SUNY. The numbers<br />

adjacent the to NGST points indicate the optimum s ‚ product<br />

of the shunted junctions used in the TFF. Also, shown is the<br />

projected divider speed of $450 GHz for the next-generation<br />

20-kA/cm process.<br />

[102], but it is important to distinguish between true “static”<br />

divide-by-two operation from narrow band operation, which<br />

often results in inflated claims of switching speed. True static<br />

divide-by-two operation means that a well-designed TFF<br />

operates correctly from near dc to its maximum reported<br />

frequency without adjusting its bias point. The near-dc frequency<br />

response is necessary if the gate is to function with<br />

arbitrary data which may have long strings of logical zeros or<br />

ones. Superconductor integrated circuit fabrication process<br />

benchmarks or maximum TFF speeds are based on the more<br />

stringent measurements of static divider performance.<br />

The NGST standard benchmark circuit is a 12-stage static<br />

divider that consists of an on-chip voltage-controlled oscillator<br />

(VCO) (a dc SQUID with damped junctions) and a 12-b<br />

TFF counter chain. Each stage of the counter chain uses of<br />

a symmetric four-junction TFF with symmetric current bias<br />

and a separate magnetic flux bias, which is described elsewhere<br />

[103]. The last two bits of the counter chain have<br />

self-resetting junction outputs that can be counted by a room<br />

temperature electronic frequency counter.<br />

The circuit parameters are chosen to optimize operating<br />

margin and yield at high speed. The design of the NGST<br />

static divider uses junctions that are slightly underdamped. 1<br />

The maximum divider speeds achieved are just above<br />

200 and 300 GHz for the 4-kA/cm and 8-kA/cm processes,<br />

respectively. These results along with results from<br />

HYPRES and SUNY for other ’s are shown in Fig. 14.<br />

The maximum divider speed scales approximately<br />

as kA/cm GHz to about 50 kA/cm , above<br />

which the speed saturates at a frequency corresponding to<br />

the gap frequency for Nb. There is good agreement among<br />

the different niobium trilayer processes shown in Fig. 14.<br />

Details of the divider speed measurements and characterization<br />

can be found in [18], [59].<br />

1 For the 8-kA/cm process, s ‚ aIXHS mV for a Stuart–McCumber<br />

parameter @ AaPXS and for 4-kA/cm Ys ‚ aHXU mV, and aPXH.<br />

1528 PROCEEDINGS OF THE IEEE, VOL. 92, NO. 10, OCTOBER 2004

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