Title Slide Chasing the Rainbow Eric Bretschneider

Chasing the Rainbow This is not an ad for Skittles® Chasing rainbows – pursuing things that are unrealistic or unlikely In order to catch something you need to know where it is going. So if you want to catch a rainbow you need to know where it is going Chase /CHās/ to follow rapidly to catch or overtake

Rainbows A rainbow is a spectral path in space . . . . . . a path can be followed One wonders what sort of treasure we will find if we can catch our rainbow . . . legends tell us there is a pot of gold at the end of the rainbow.

Lighting Parameters Flux S/P Ratio Color Rendering/Quality Luminous (TM-21-11) Photon (TM-21-19?) Radiant (TM-21-19?) S/P Ratio Color Rendering/Quality CRI R9 Rf Rg Chromaticity xy or u’v’ Du’v’ (TM-35-19?) CCT duv Photobiology Photobiological hazard (IEC 62471) Circadian . . . These are all dependent variables, they are calculated from the SPD. They are our pot of gold . . . These dependent variables are our pot of gold

Reliability Standards Predict Parameters Reliability standard development process define a parameter develop/approve a standard to calculate the parameter 2-3 years collect data analyze trends/develop reliability metric 3-5 years 2-3 years You have to collect years of data before you can begin trying to predict behavior. Once you have the data, it still takes years before you can make a prediction. That’s fine if you don’t mind a slow response/reaction to the demands of an industry. 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? How bad could it be? 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 For a single phosphor you need 8+ parameters: 4+ for the emission 4+ for the excitation Mode hopping refers to one of the modeled peaks suddenly shifting dramatically between two time intervals. You either let the peak jump or at that point in time your model starts diverging from the data. You can do a better job if you know how the LED is constructed, but a generalized approach should not require prior knowledge. Just try asking manufacturers to give up the material/component list for all of their LED packages . . . This is very sensitive information!

Mode Hopping Peak parameters (center, FWHM, etc.) can make a step change over time For a single phosphor you need 8+ parameters: 4+ for the emission 4+ for the excitation Mode hopping refers to one of the modeled peaks suddenly shifting dramatically between two time intervals. You either let the peak jump or at that point in time your model starts diverging from the data. You can do a better job if you know how the LED is constructed, but a generalized approach should not require prior knowledge. Just try asking manufacturers to give up the material/component list for all of their LED packages . . . This is very sensitive information! 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 . . . Wouldn’t it be great if we had a really well known light source That changed in a predictable way And that had been modeled? Oh, wait we do

D-Series Illuminants D-Series (daylight) illuminants are calculated using a linear combination of 3 eigenspectra S(l) = S0(l) + M1S1(l) + M2S2(l) M1 and M2 are functions of CCT. If you know the CCT, you can calculate the their values and then calculate the SPD. Could a similar approach work for LEDs? 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) = S0(l) x e[-S1(l)t] We have been modeling LED lumen maintenance as an exponential decay for almost a decade now. Perhaps we could use an exponential decay analog . . .

Results It’s almost impossible to tell the difference between the actual data and the prediction. TM-21 and TM-35 are highly specialized reliability models, they predict very specific metrics and no additional information. Even this rudimentary eigenspectral analysis gives very comparable results on lumen maintenance and chromaticity shift – at the same time These results are at least as good as predictions from existing standards and those in development

What else can we predict? But look at what else we can predict! All of these parameters are predicted with a single model/method. Every single parameter listed here and even more can be predicted as a function of time These are examples of the enormous number of parameters we can predict with the spectral power distribution

Eigenspectral Analysis The first eigenspectrum S0(l) does not contain significant information It’s the initial spectrum This is boring. Knowing the spectrum at time = 0 doesn’t tell us anything we don’t already know This doesn’t tell us anything we don’t already know

Eigenspectral Analysis Peak shift in time The second eigenspectrum S1(l) is far more interesting Although this is the rate of change, it gives information on construction/materials The second eigenspectrum though is far more interesting. This shows a peak that shifts location over time This shows a loss of emission and is an exceptional match to a commercial phosphor Without knowing anything about the package, we can identify some of the materials and also have a very good idea of what is changing inside the package. We even have an idea of what we should focus on to improve performance stability over time 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 This method is potentially a very powerful tool.

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 The industry is changing more rapidly than ever. Reacting to the industry means we will on get further behind as time goes on. If we want to adapt, then we have to take a more proactive stance. It is our only hope to keep up. Sometimes being ambitious pays off far better than we ever expected.

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