Chasing the Rainbow Eric Bretschneider Chasing the Rainbow

Chasing the Rainbow Eric Bretschneider

Chasing the Rainbow This is not an ad for Skittles® Chasing rainbows – pursuing things that are unrealistic or unlikely Chase /CHās/ to follow rapidly to catch or overtake

Rainbows A rainbow is a spectral path in space. . . a path can be followed. . . legends tell us there is a pot of gold at the end of the rainbow.

Lighting Parameters Flux • Luminous (TM-21 -11) • Photon (TM-21 -19? ) • Radiant (TM-21 -19? ) Chromaticity • • xy or u’v’ Du’v’ (TM-35 -19? ) CCT duv These dependent variables are our pot of gold S/P Ratio Color Rendering/Quality • • CRI R 9 Rf Rg Photobiology • Photobiological hazard (IEC 62471) • Circadian. . .

Reliability Standards Predict Parameters Reliability standard development process • define a parameter • develop/approve a standard to calculate the parameter • collect data • analyze trends/develop reliability metric 2 -3 years 3 -5 years 2 -3 years 5 -8 years after we develop a standard for a metric we might be able to predict future behavior

If we calculate everything from the SPD, why don’t we just predict the SPD? Lumen maintenance: predict 1 parameter vs time Chromaticity shift: predict 2 parameters vs time If white LEDs are (typically) made using an LED and phosphor can’t we just model each emitter? After all, it’s only an LED and a phosphor or two. . .

Reality Check for Emitter Based Models For a reasonably accurate model we should expect at ~20 parameters (or more) Prior knowledge of LED construction required to prevent “mode hopping” Short summary: it’s really complicated, even if you know the details

Mode Hopping Peak parameters (center, FWHM, etc. ) can make a step change over time The negative peak is the absorption spectrum of the phosphor material.

Finding an Alternative Approach If only we had experience in modeling the spectral output of a light source that changed in a predictable manner over time. . .

D-Series Illuminants D-Series (daylight) illuminants are calculated using a linear combination of 3 eigenspectra S(l) = S 0(l) + M 1 S 1(l) + M 2 S 2(l) Could a similar approach work for LEDs? This approach was actually developed when “computer” was a job description, not an electronic device – its surprisingly old

Exponential Decay Analog S(l) = S 0(l) x e[-S 1(l)t]

Results These results are at least as good as predictions from existing standards and those in development

What else can we predict? These are examples of the enormous number of parameters we can predict with the spectral power distribution

Eigenspectral Analysis The first eigenspectrum S 0(l) does not contain significant information It’s the initial spectrum This doesn’t tell us anything we don’t already know

Eigenspectral Analysis Peak shift in time The second eigenspectrum S 1(l) is far more interesting Although this is the rate of change, it gives information on construction/materials This is a decaying phosphor it is an ~96% match to the emission spectrum of a commercial red phosphor

Perspective • The accuracy of even rudimentary eigenspectral models is on par with that of existing (or in process) standards that predict a single parameter or a pair of related parameters • A successful eigenspectral model will likely be the only reliability model needed • In addition to predicting performance, the eigenspectra themselves contain valuable information about the aging mechanisms of LED products/devices

Takeaways • The traditional reactive approach to reliability standards will never be able to keep up with a changing industry • New and proactive approaches to developing reliability standards need be considered in rapidly evolving markets like the lighting industry • A willingness to embrace ambitious goals can pay dividends far in excess of what we expected

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