5962-9679801VCA datasheet, PDF

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5962-9679801VCA: DescriptionComparator, 2 Func, 6800uV Offset-Max, BIPolar, CDIP14, CERAMIC, DIP-14; CategoryAnalog mixed-signal IC Amplifier circuit; File Size142KB，4 Pages; ManufacturerDefense Logistics Agency; Related ProductsFound1parts with similar functions to 5962-9679801VCA

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Comparator, 2 Func, 6800uV Offset-Max, BIPolar, CDIP14, CERAMIC, DIP-14

5962-9679801VCA Parametric

Parameter Name	Attribute value
Maker	Defense Logistics Agency
Parts packaging code	DIP
package instruction	DIP,
Contacts	14
Reach Compliance Code	unknown
ECCN code	EAR99
Amplifier type	COMPARATOR
Maximum average bias current (IIB)	0.475 µA
Maximum input offset voltage	6800 µV
JESD-30 code	R-GDIP-T14
JESD-609 code	e0
Negative supply voltage upper limit	-18 V
Nominal Negative Supply Voltage (Vsup)	-15 V
Number of functions	2
Number of terminals	14
Maximum operating temperature	125 °C
Minimum operating temperature	-55 °C
Package body material	CERAMIC, GLASS-SEALED
encapsulated code	DIP
Package shape	RECTANGULAR
Package form	IN-LINE
Certification status	Qualified
Filter level	MIL-PRF-38535 Class V
Supply voltage upper limit	18 V
Nominal supply voltage (Vsup)	15 V
surface mount	NO
technology	BIPOLAR
Temperature level	MILITARY
Terminal surface	TIN LEAD
Terminal form	THROUGH-HOLE
Terminal location	DUAL

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Application Note

SLVK047 – May 2020

Single-Event Effects (SEE) Confidence Interval

Calculations

ABSTRACT

This application note describes the methodology used to calculate confidence intervals for radiation-

hardened devices that exhibit few or zero radiation-induced events.

Contents

Introduction

...................................................................................................................

References

...................................................................................................................

List of Tables

Experimental Example Calculation of Mean-Fluence-to-Failure (MFTF) and,

Using a 95% Confidence

Interval

........................................................................................................................

Introduction

Determining the SEE cross-section of robustly radiation-hardened devices becomes more difficult since

often few, or possibly even no events are observed during an entire exposure. Determining the cross-

section using an average event rate with standard deviation is no longer a viable option, and the common

practice of assuming a single error occurred at the conclusion of a null-result can end up in a greatly

underestimated cross-section.

In cases where observed events are rare or non-existent, the use of confidence intervals and the Chi-

Squared distribution is indicated. The Chi-Squared distribution is particularly well-suited for determining a

reliability level when the events occur at a constant rate. In the case of SEE testing where the ion events

are random in time and position within the irradiation area, it is expected that the event rate is independent

of time (presuming that parametric shifts induced by the total ionizing dose do not affect the failure rate),

so the use of Chi-Squared statistical techniques is valid (since events are rare an exponential or Poisson

distribution is usually used).

In a typical SEE experiment, the device-under-test (DUT) is exposed to a known, fixed fluence (ions/cm

)

while the DUT is monitored for events. This is analogous to fixed-time reliability testing and, more

specifically, time-terminated testing, where the reliability test is terminated after a fixed amount of time

whether or not a failure has occurred (in the case of SEE tests, fluence is substituted for time and hence it

is a fixed fluence test) [1]. Calculating a confidence interval specifically provides a range of values which is

likely to contain the parameter of interest (the actual number of events/fluence). Confidence intervals are

constructed at a specific confidence level. For example, a 95% confidence level implies that if a given

number of units was sampled numerous times and a confidence interval was estimated for each test, the

resulting set of confidence intervals would bracket the true population parameter in about 95% of the

cases.

To estimate the cross-section from a null-result (no events observed for a given fluence) with a confidence

interval, start with the standard reliability determination of lower-bound (minimum) mean-time-to-failure for

fixed-time testing (an exponential distribution is assumed):

SLVK047 – May 2020

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Single-Event Effects Confidence Interval Calculations

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