Variation and variability
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Variation T
va r i a b i l i t y
he world has been turned upside down with the novel Coronavirus pandemic. The most effective approaches to prevent the spread of the virus have been social distancing and wearing personal protective equipment (PPE), which has significantly changed our approach to life. Most of our daily activities have been altered, including medical appointments. My physicians have recommended that I cancel or postpone medical appointments that are not critical. To the extent that I am able, I have followed their advice. My quarterly appointment with my ophthalmologist (for glaucoma) was reduced to tests of the intraocular pressure, which were conducted at a drive-thru location specially set aside in the parking lot at the facility. The nurse also used a small infrared thermometer to get a quick reading of my body temperature, which read 99.2ºF instead of the normal temperature of 98.6ºF, which was slightly concerning. I note that the PPE, the tool for measuring intraocular pressure, and the infrared temperature sensor are all results of materials research. As materials researchers, we are all familiar with variation and variability. We know that even under the best of conditions, repeat measurements of the properties of materials vary in outcome. Wouldn’t it be nice if every measurement was accurate with a precision only determined by the instrumentation? We could then make a single measurement on a single sample for each test condition and be absolutely sure of the result. There would never be any need to make another such measurement. Except, of course, for improvements in precision obtained as instrumentation advances. Obviously, this is not the case. Material quality varies. Consider growth of semiconductor materials. We have a significant amount of experience growing some materials, such as silicon. Hundreds of thousands of wafers of silicon are processed every year by manufacturers of integrated circuits (ICs).1 And yet, IC manufacturers still encounter lot-to-lot variations in device performance, wafer-towafer variations within a lot, and device-to-device variations on a single wafer. Some of these problems are due to processing issues. Some are due to problems with materials. For those of us who perform research on semiconductor materials, we expect to obtain good results when we perform measurements on some materials (e.g., silicon, GaAs, germanium). However, other semiconductor materials (e.g., HgCdTe) can be quite challenging. Although, the quality of HgCdTe samples has improved during the span of my career, working with it can still challenge the unwary. And now, we are attempting to develop materials based upon other ternary, quaternary, quinternary, and even larger agglomerations of materials. As materials researchers, we know how to deal with variations in our measurements.2,3 We know that we need to characterize our samples properly before making measurements. We know that we should make measurements on multiple samples at each test condition and multiple measurements on each sampl
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