alixModerated by Alix Paultre, Editorial Director, the Roundtable is where industry players talk about market and industry trends. This month's question is:What emerging technologies or processes do you believe are the most promising to improve the performance of solid-state lighting?  



Jordi  TorrebadellJordi Torrebadell, Director of Engineering – Americas, RECOM Power (

Energy efficient Solid State Lighting systems are helping to reduce the energy consumption of one of the most wasteful commodities, the light bulb. However, even with a highly efficient solution, the waste of energy through light can be further controlled by implementing an intelligent/automated communication system to control and optimize our interaction with light. This is a key differentiator from other low-consumption light sources. 

I think that the standardization of a wireless control system is one of the most critical processes for the success of total implementation of Solid State Lighting in our future. There are currently several protocols for lighting wireless control: Zigbee, Z-Wave, SNAP, DALI, PLC, etc.  Once one of these protocols becomes the true standard, the current complexity and fear of obsolescence will disappear. This will make it easy for lighting designers to implement wireless control systems and create intelligent systems to boost efficiency and further decrease energy waste.


Xiantao YanDr. Xiantao Yan, CTO and Founder, LED Engin (

I believe that the most important emerging technology is the single color bin (one or two MacAdam ellipse) of white color emitters with stable color over the life of the lamps or lighting fixtures. For given different wavelengths across a wafer and the variation of phosphor coating thickness, we have to find a fundamental way to control the color AT EMITTER LEVEL. With this level of color consistency and stability, the adoption of solid state lighting in commercial, retail, and general lighting will be accelerated at a much lower cost.

The LED Engin solution for controlling CCT at emitter level is accomplished with multiple LEDs within a single package and proprietary tuning algorithms and devices in the production line. LED Engin solution can provide single color bin emitters with uniform color distribution and the best color stability over the life of lamps or lighting fixtures. A customer can also use the same technology to tune the color temperature along black body curve, such as neutral white during daytime for productivity and warm white during night for comfort.

Thomas DavenportThomas Davenport, Ph.D., Systems Illumination Engineer, Optical Solutions Group at Synopsys(

One emerging technology improving solid-state lighting performance is the use of reflective optics based on total internal reflection (TIR).  Traditionally, single-surface, reflective optics used in air (such as vacuum metalized mirrors on a plastic substrate) were the most ubiquitous lighting optics.  Now that LED lighting is maturing, designers are moving to TIR optics to reduce optical losses and improve control of the light distribution.  TIR reflectors are (theoretically) perfectly reflective, and each refractive surface has approximately 4% loss.  Therefore, the upper limit of the efficiency, assuming no anti-reflective coatings and a very transmissive material, is around 92%.  On the other hand, a specular reflector’s mirrored surface can oxidize in air, and often has up to 20%-30% loss from the reflective surface.  Additionally, and perhaps more importantly, the TIR approach provides two additional refractive optical surfaces (see figure below), which can be used to shape the light distribution emanating from the LED.  The TIR optic also interacts with all of the light from the LED, whereas there is typically a large cone of light from a traditional, reflector-based luminaire (a.k.a. the direct light) that does not strike the reflector at all, and is therefore uncontrolled—typically not desirable.


In order to design TIR optics for luminaires without lots of prototyping, one needs to simulate the LED luminaire system.   Although the concept of modeling optical systems is not new, there are some emerging technologies for modeling and optimizing solid-state lighting designs as well.  There are various aspects to the simulation question, but here we consider two specific ones: the optimization of the optical geometry and the LED model.

                Monte Carlo ray tracing has proven to be a robust technique for evaluating an optical system.  When Monte Carlo ray tracing is combined with correctly parameterized, geometric modeling and a state-of-the-art optimization capability, the design can be pushed to its practical limits.  This is exactly the approach emerging for designing optics like the one above.  First, the optic is parameterized in a convenient way; in the above example, four spline curves with slope discontinuities at their connection points are rotated to form the solid.  Lighting metrics, such as center beam candle power (CBCP), Beam width at ½ of the CBCP (FWHM), and cutoff angle (beam width at 10% of CBCP) are then used to construct a merit function.  When the merit function gets smaller in value, this means the optical performance of the system improves.  An optimization algorithm is used to minimize the merit function by changing each variable slightly and using the resulting change in merit function value to guess which way to adjust all the variables at once.  The process is repeated iteratively until the merit function no longer can change to a lower value or some other exit criterion is met (for instance, reaching a specified maximum number of iterations).  This type of optimization is robust and helps find the best solution for a wide range of optics designs.

White light is typically more important than individual colors for the lighting market.  Since LEDs are close to being monochromatic emitters, one popular way to make a broader, white spectrum involves blue or violet LEDs used with a phosphor coating.  New LED simulation technology is also emerging in this area.  For instance, phosphor models that include excitation and emission spectra are becoming more commonplace.  Additionally, scattering models for the phosphors are included, which are sometimes Mie scatter distributions, or might be based on wavelength-dependent models.  Manufacturers are also beginning to make more information about their products available to designers.  For instance, it is now common to get ray files (a collection of rays in space that simulate the goniometric-measured light distribution from a particular LED) with the ‘blue’ and ‘white’ portions separated out, or with tristimulus values incorporated.  Optical software is now using these data to predict Correlated Color Temperature (CCT), Color Rendering Index (CRI), color coordinates, RGB true color, and color difference, among other color metrics.  With the widespread adoption of LED sources, new, more-appropriate-to-LED metrics are also emerging, such as the Color Quality Scale (CQS) developed recently by NIST.