# Presentation: 547348

##   Day 1 (General)
1A Overview
1B Technology Evolution

**  **_**Day 1 (General)**_
**1A Overview**
**1B Technology Evolution**

**  **_**Day 2 (Technical Challenges)**_
**2   Roadmap Overview**
**2A Substrates, Buffers and Epitaxy**
**2B Physics, Processing and Devices**
**2C Lamps, Luminaires and Systems**

**Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy’s National Security Administration under Contract DE-AC04-94AL85000**

**OUTLINE OF TOPICS (DAYS 1 & 2)**

**Notes:**
Let me first thank Professor Chua and IMRE for your kind hospitality during this two-week visit.  I’ve enjoyed my discussions with many of the staff here, and I’ve enjoyed seeing the sights of Singapore.  And, especially, thanks to Alice Lee, who made every arrangement for me and my family as efficiently as could be imagined.
As Professor Chua mentioned, I have been involved in solid-state lighting for quite some time, in particular helping out with national-level strategic planning and analyses that blend science, technology and economics.  There have been many exciting developments in solid-state lighting, at all levels, so this two-day workshop is actually a nice and timely opportunity for me to review the field.
We decided to break the workshop up into two days.  I’ve prepared approximately 45 minutes of material for each of these topics (1A, 1B, and 2A, 2B and 2C), but only very approximately.  Some may be longer, some may be shorter, and how long we spend on each topic will also depend on your interests and questions.  I’m thinking we’ll take a short break after each of these topics, so we’ll end up with about an hour for each topic.
In Day 1 I’ll talk about more general issues related to solid-state lighting.  Topic 1A will be a very general overview of solid-state lighting – the grand vision. Topic 1B will summarize some recent work on using solid-state lighting as a case study for how technologies evolve in general.
In Day 2 I’ll talk about some of the technical challenges associated with solid-state lighting.  In particular, the focus will be on those challenges that stand in the way of solid-state lighting achieving its potential in general white-light illumination, rather than just niche colored-light applications.  Topic 2A will be materials-level challenges:  substrates, buffers and epitaxy.  Topic 2B will be device-level challenges:  physics, processing and devices.  Topic 2C will be lamp-level challenges:  lamps, luminaries and systems.
I should point out that I will be focusing most of my attention on solid-state lighting based on inorganic materials, as these are the most mature and have the most definite possibilities for general white-light illumination.  But solid-state lighting based on organic materials is certainly also being considered seriously.
Are there any comments on this outline?  If not, let’s begin with Topic 1A, an overview of solid-state lighting.

## 1A Overview

**History of Luminous Efficacy**
**The Grand Vision of SSL**
**U.S. SSL Roadmap**

**Notes:**
I’ve divided Topic 1A, the overview of solid-state lighting, into three subtopics.
First, I’ll give a brief history of luminous efficacy for the various artificial sources of white light.
Second, I’ll describe the grand vision of solid-state lighting – basically why in the U.S. and worldwide there has been so much interest not just in the private sector, but in the public sector, in solid-state lighting.
Third, I’ll give a brief overview of the U.S. solid-state lighting roadmap, a roadmap that helped concretize for the first time a timeline for the evolution of the technology, along with enumerating the technical challenges associated with solid-state lighting for general white-light illumination.

## History of Lighting Technology

**History of Lighting Technology**

**Notes:**
Let’s begin with the history.  Here I show a condensed history of modern lighting technologies, over the 200-yr time span from 1850, projected out to 2050.  The metric we use is luminous efficacy, in lumens per watt, which is basically the efficiency with which either chemical or electrical power is converted into light, convolved with the human eye sensitivity to that light.  For a white light source composed of red, green and blue components, 100% power conversion efficiency would give about 350-400 lm/W, 50% would give about 175-200 lm/W, and so on.
One can see how terribly inefficient Fire is – even the most efficient gas lamps only achieve about 1 lm/W efficacy, or about 1⁄4 of a percent power conversion efficiency.  Incandescence was a huge improvement – it has the potential to approach 20 lm/W, or about 5% power conversion efficiency.  And, of course, Fluorescence was yet another big improvement – it has the potential to approach 100 lm/W, or about 25% power conversion efficiency.
The latest technology, developing rapidly on this 200-yr time scale, is solid-state lighting.  One can see, beginning in the 1960’s or so, red LEDs gradually developing, with GaP, AlGaAs, and now AlGaInP, materials.  And, beginning in the 1990’s, the much more rapid development of green and blue LEDs, initially with GaAs, SiC and ZnSe materials, but now dominated by AlGaInN.  And, through use of blue and UV LEDs combined with wavelength-conversion phosphors, or through direct use of red, green and blue LEDs, white light can also be created.  The ultimate efficiency of these white solid-state lighting may very well reach 200 lm/W, or about 50% power conversion efficiency.  If it makes it there, it would be two times more efficient than Fluorescence, and ten times more efficient than Incandescence.  In fact, the world record for power conversion efficiency from electricity to light is now 71%, demonstrated by Alphalight under a DARPA-sponsored program, for a 970nm high-power InGaAs/GaAs-based semiconductor laser, with their next target 80%.  There doesn’t seem to be any fundamental physical reason why semiconductor light sources in the visible couldn’t achieve similar efficiencies.
Nevertheless, for white light, there is still some room to go before solid-state efficiencies are in the 50% regime, and before they have a clear competitive advantage over traditional lighting.  That isn’t the case for colored lighting.  Here I’ve sketched the efficiencies of traditional colored lighting, in which white light from an incandescent source is filtered.  The filtering introduces huge inefficiencies, and so semiconductor devices, which naturally produce monochromatic colored light, have a huge advantage.  So most people in the community accept that virtually all applications for monochrome or colored light will soon migrate to solid-state lighting.

## Applications for Colored LEDs

- Programmable Lights on Ben Franklin Bridge, Philadelphia (Color Kinetics)

- NASDAQ’s Giant Video Display in Times Square, New York (Jeff Tsao)

- Red Traffic Light

- Rear Combination Lamp (LumiLeds)

**Notes:**
I’m sure most of you know what many of these applications are; here are some of the more important ones.
Red, green and yellow traffic lights, of course.  At this point, in the U.S., more than 1⁄2 of all traffic lights are LED based; here in Singapore I think it is close to 100%.
Huge outdoor video displays, like this one in New York City’s times Square.
Programmable color light shows, such as on the Ben Franklin Bridge.  Perhaps the biggest of these light shows will be for the upcoming 2008 Olympics in Beijing.
And the interior and exterior lights on next-generation automobiles.

## Lighting the Earth

**Lighting the Earth**

**Earth at Night (courtesy of NASA)**

**Notes:**
But, despite the success of solid-state lighting in colored monochrome applications, the grand dream of solid-state lighting is in general white light illumination.  We often use this photo to illustrate that dream; basically we would like to someday replace every light on Earth with semiconductor lamps.
This photo is also interesting, of course, because it shows which parts of the world consume the most energy for lighting:  the U.S. and Western Europe, of course, but increasingly Asia, not just Japan but of course South Korea and Taiwan.  You can also see on this map some of the other important Asian cities:  Hong Kong, Bangkok, Singapore.
There are two huge motivations for this grand dream of solid-state lighting, illustrated in the next two viewgraphs.

## Projected Energy and Carbon Savings

**Projected Energy and Carbon Savings**

- Adapted from M. Kendall and M. Scholand, “Energy Savings Potential of SSL in General Lighting Applications” (U.S. DOE-OBT study by Arthur D. Little, 2001), and EIA Statistics.

| Projected Year 2025 Savings | US | World |
| --- | --- | --- |
| Electricity used (TWh/yr) | 525 | ~1,800 |
| $ spent on Electricity ($B/yr) | 35 | ~120 |
| Electricity generating capacity (GW) | 70 | ~250 |
| Carbon emissions (MtC/yr) | 85 | ~300 |
| % of Kyoto protocol | 7.5 |  |

**Notes:**
The first big motivation has to do with energy consumption.  In the U.S., energy consumption, in electricity-equivalent units, is about 10,000 TWh/y.  Of that, about 1/3 is consumed as electricity, and of that about 1/5 is consumed by lighting.  So 1/15 of all energy consumed is due to lighting.  Assuming reasonable growth rates, by the year 2025, the U.S. may be consuming as much as 1,000 TWh/y of electricity for lighting. At an electricity price of about 7 cents/kWh, that’s about $70B/y.
Moreover, lighting isn’t very efficient.  Its aggregate efficiency, averaged over the traditional lamps (incandescent, fluorescent and high-intensity discharge), is only about 20%, which means that 80% of that $70B is wasted.
In principle, solid-state lighting can be much more efficient, and the grand dream is this:  to achieve an efficiency more than twice that of traditional lighting, while replacing every lamp on Earth, all the way from the smallest indicator lamp to the largest football-stadium-sized floodlight.  If we could do that, we’d decrease consumption of electricity for lighting by more than half, as illustrated here in the dotted lines, and, by 2025, save roughly $35B/y.  At the same time, of course, we’d eliminate the carbon emissions associated with generating that electricity.  Although the U.S. didn’t ratify the Kyoto protocol, if it had, solid-state lighting alone would provide 7.5% of the necessary carbon emissions reduction.
Worldwide, all of these numbers are multiplied by roughly 3-4x, so the worldwide electricity savings would be of the order 120B$ per year.

## Human Visual Experience

**Human Visual Experience**

**Joseph Wright (1768)**
**"An Experiment on a Bird in the Air Pump“**

**Notes:**
These are huge numbers, but even they don’t convey the full benefit of solid-state lighting.  Many in the community believe that a second and perhaps even more important benefit will be an enhanced human visual experience.
I like to show this painting by Joseph Wright, because it is such a nice illustration of how important light is to us.  Lighting illuminates, of course, as this scene is illuminated by the moonlight from the window at the upper right.  But by selectively illuminating some parts of the scene rather than others, it focuses our attention and interest, as it is focusing our attention here on the little girl slightly off-center in the painting.  And by the warmness or, in this case, coolness, of the light, it alters our emotional response to scenes, and affects whether we interpret what we see with comfort or, as in this case, with some apprehension.  This painting is actually one of an experiment on an air pump, where this mad scientist is about to pump the air out of this bell jar, and when he does so, the bird will die, so that’s why there is apprehension on this girl’s face.
With semiconductor-based solid-state lighting, it is possible to imagine lights that are independently and digitally controlled in space, time, intensity and color temperature to best enhance a particular visual experience -- something that is impossible to do with traditional lighting technologies.  In fact, one might anticipate that, in the long term, solid-state lighting won’t save us energy at all.  As with other technologies that enhance our lives, we may use more, rather than less, of it.  But in using more of it, presumably our overall productivity and quality of life will also improve.

## U.S. National Initiatives

**U.S. National Initiatives**

**Notes:**
So two of the most important benefits of solid-state lighting are:  reduced energy consumption and an enhanced human visual experience.  But there are a lot of technical challenges that stand between where we are now and where we would need to be if these benefits are to be realized.
So in 1999, actually right after I returned from my half-year sabbatical in IMRE, a few of us in the community got together to put together this white paper on solid-state lighting.  Roland Haitz, then at Hewlett-Packard, spearheaded the paper, and I consider him to be the original visionary of solid-state lighting.  But Arpad Bergh, President of the Optoelectronics Industry Development Association, also played an important cheerleading role.  And I helped place the entire idea in a strategic context.
The immediate consequence of this white paper was interest at the U.S. Department of Energy as well as in Congress, and one consequence was the initiation of legislation, by Senator Jeff Bingaman of New Mexico, for a major next-generation lighting initiative, for R&D related to solid-state lighting.  As it turns out, this legislation was incorporated into a larger energy bill that had other controversial provisions, including oil drilling in the Alaska Arctic National Wildlife Refuge.  That kept the larger energy bill from being passed, until this year, when that provision was dropped.  And, just this last week, the legislation was passed – President Bush signed it into law Monday of this week.
Of course, just because a bill is passed authorizing expenditures doesn’t mean those expenditures will take place – there is also an appropriations process that follows, and we will have to see how that goes.  But there is certainly a lot of excitement in the community right now.

## US SSL-LED Roadmap Update 2002

| Sponsors | OIDA (Arpad Bergh), DOE (Jim Brodrick), NEMA (Kyle Pitsor) |
| --- | --- |
| Editors | Mar 2001 Roadmap - Eric Jones (SNL)
Aug 2002 Update - Jeff Tsao (SNL) |
| Technical Area Coordinators | Steve Denbaars, Bernd Keller, Mike Coltrin, Bob Davis, Tom Kuech, George Craford, Paul Martin, Jim George, Chips Chipalkatti |
| Workshop Speakers | Arto Nurmikko, Axel Scherer, Bob Davis, Weng Chow, Tom Kuech, Shuji Nakamura, Chips Chipalkatti, Nadarajah Narendran, Kevin Dowling, Alok Srivastava, Paul Martin |
| Chap 0 Contributors | Yoshi Ohno, Michael Scholand, Kate Bogart, Roland Haitz |
| Chap 1 Contributors | Dan Koleske, John Bumgarner, Christine Mitchell, Randy Creighton, Eric Jones, Sam Myers |
| Chap 2 Contributors | Weng Chow, Art Fischer, Mike Krames, Ed Stokes, Spilios Riyopoulos |
| Chap 3 Contributors | Dan Doxsee, Yongchoi Tian, Karel Vanheusden, Lauren Rohwer, Stan Weaver, Steve Richfield, Frank Steranka, Chuck Becker, James Gee |

**Notes:**
In the meantime, with or without a next-generation lighting initiative, we also recognized that there were tremendous technical challenges associated with solid-state lighting.  To help understand these challenges, in 2001-2002 we put together a roadmap for solid-state lighting.  The main sponsors were OIDA (Arpad Bergh) DOE (Jim Brodrick) and NEMA (Kyle Pitsor), with OIDA providing most of the energy to drive the process forward.  And, of course, many individuals contributed as well, including the technical area coordinators listed here, the speakers at a major workshop we held, and a lot of technical experts.
This roadmap provided a guidebook for the technical community, and in tomorrow’s topics I’ll touch on many of the roadmap challenges.  But in the next two viewgraphs I’ll give a brief overview of the high-level targets of the roadmap, and of some of the challenges.

## SSL-LED Roadmap Targets

**SSL-LED Roadmap Targets**

**Targets based on raw economic performance (not human factors)**
**Incandescence in 5 years**
**Fluorescence in 10 years**
**Ownership Cost**
**= Operating Cost + Capital Cost**

**0.01**

**0.10**

**1.00**

**10.00**

**100**

**Operating Cost [$/(Mlm-hr)]**

**Capital Cost [$/(Mlm-hr)]**

- SSL-LED 2002

- SSL-LED 2007

- SSL-LED 2012

- SSL-LED 2020

- Fluorescent

- Incandescent

**Notes:**
Let’s start with the high-level Roadmap targets.  Here you see the various categories of targets.  There’s luminous efficacy, in lm/W; there’s lifetime, in hours; there’s flux per lamp, in lm/lamp; there’s input power to the lamp, in W/lamp; there’s the cost to purchase a lamp, in $/klm and $/lamp; and finally there’s color rendering index, or CRI, which is a measure of the quality of the white light.
This column is where solid-state lighting was in 2002; these three columns are where we wanted to be in 5, 10 and 18 years; and these last two columns are where the competition, incandescent and fluorescent lighting, were then.
Except for one – this color rendering index --  these high-level targets were chosen based on raw economic performance.  The idea was to beat incandescence in 5 years, and to beat fluorescence in 10 years, purely through brute force economics.
To see that, I’ve plotted here two costs associated with light.  The operating cost – how much it costs you to run your light bulb, day after day – is the bottom axis of this plot.  The capital cost – how much it costs you to buy your light bulb or lamp, amortized over its lifetime – is the left axis of this plot.  The units we use are $/Mlm-hr.
Take incandescent lighting.  Its luminous efficacy is pretty low (16 lm/W), so its operating cost is relatively high.  Light bulbs are pretty cheap (about 0.4 $/klm), but because their lifetimes are so short (1,000 hrs), their capital cost amortized over the life of the lamp isn’t as low as you might expect.  You can see from this green incandescence data point that the capital and operating costs are actually pretty similar.
Now, to enable us to compare incandescence to other technologies, this green curve represents a constant life-ownership-cost curve.  Points up here have very high capital cost but very low operating cost.  Points down here have very high operating cost but very low capital cost.  But they all have the same life ownership cost as incandescence.
Now take fluorescent lighting.  Its luminous efficacy is higher (85 lm/W), so it’s further to the left in operating cost than incandescence.  Also because of its long lifetime (10,000 hours), its farther down in capital cost, again amortized over the life of the lamp, than incandescence.
So where is solid-state lighting?  Well, it’s more efficient than incandescence, so it lies to the left, but it’s way more expensive, so it lies way up high here.  By 2007, though, the idea is to beat , and to have significant replacement of, incandescence lighting.  And by 2012, the idea is to beat, and to have significant replacement of, fluorescence lighting.  And by 2020, to have massive replacement of all lighting.
To do this, our targets for 2020 are the following.  A luminous efficacy of 200lm/W, which is about 50% wall-plug efficiency.  A lifetime of 50,000-100,000hrs.  A lumens costs of 2 $/klm, which is a little higher than that of fluorescence, but when you factor in the longer lifetime, implies a much lower capital cost.

## SSL Science and Technology Taxonomy

**0 **_**General**_
**1 **_**Substrates, Buffers and Epitaxy**_
**   ****1.1 Substrates**
**   ****1.2 Buffers**
**   ****1.3 Epitaxy Tools**
**   ****1.4 Epitaxy Processes**
**2 **_**Physics, Processing and Devices**_
**   ****2.1 Semiconductor Physics**
**   ****2.2 Device Processing**
**   ****2.3 LEDs and Integrated LEDs**
**   ****2.4 Directional Emitters**
**3 **_**Lamps, Luminaires and Systems**_
**   ****3.1 Phosphors and Encapsulants**
**   ****3.2 Lamps and Electronics**
**   ****3.3 Luminaires**
**   ****3.4 Lighting Systems**

**Notes:**
Now, one half of the roadmap was the high-level targets.  The other and much larger half was identifying the technical challenges associated with achieving those targets.  Again, I’ll go through many of those challenges in tomorrow’s topics.
Today, I’ll just say that we divided them into three major areas.
The first area was materials:  substrates, buffers, epitaxy tools, and epitaxy processes.  Substrates and buffers are mostly about defects.  For a while people thought defects weren’t such a bad thing in GaN.  But increasingly there is the realization that defects are indeed bad, particularly when devices are driven hard.  So there is a lot of interest in substrates or buffers that can enable lower defect density.  Epitaxy tools and processes are all about the difficulty of GaN epitaxy, particularly its alloys.  For example, there are a lot of parasitic chemical reactions that go on that make growth of AlGaN or InGaN alloys very nonlinear with flow rates and temperatures.
The second area was devices:  semiconductor physics, device processing, LEDs and integrated LEDs, and directional emitters. This area is all about creating light efficiently, despite challenges such as internal piezoelectric fields which tend to make creating light inefficient, then extracting the light efficiently, despite challenges such as a high refractive index, which tend to make extracting light inefficient.
The third area was lamps:  lamps, luminaires and systems.  This area is all about how to best create white light from colored light.  How many colors, and at what wavelengths, and with what spreads in wavelengths, is best matched to the human visual system and to the particular lighting task.

## Sandia’s SSL Website

**Sandia’s SSL Website**

***Semiconductor light emitting devices, once limited to a narrow range of colors, now span nearly the entire visible spectrum. Someday, they may be bright, efficient and inexpensive enough to replace vacuum tubes for white lighting. Energy consumption and environmental pollution would be reduced, and the quality of the human visual experience would be enhanced, dramatically. Yet, enormous challenges lie ahead.***
***This web-site aims to provide a comprehensive portal to the emerging knowledge that will enable the promise of solid-state lighting.***
***http://lighting.sandia.gov/***

**Notes:**
Again, I’ll go through many of these challenges in tomorrow’s topics, so let me close this topic with a URL to Sandia’s solid-state lighting website.
The purpose of the website is indicated here – “ ”.  We started it in 2002, and since then it has gone through several design changes.  At this point, it represents a fairly comprehensive source of solid-state lighting information, both technical and business.

## 1B Technology Evolution

**Traditional vs SSL Technologies**
**Evolution of SSL Technology**
**Evolution of SSL Markets**

**Notes:**
Now let’s move on to Topic 1B, the evolution of solid-state lighting technology.  Just as was the previous Topic, this is a preliminary study, and some of the figures that you see are in the process of being updated.  But I thought it would be interesting for you to see how one might think about the possible evolution of solid-state lighting science and technology.
I can also make the same point that I made for the previous Topic -- understanding technology evolution in general is an interesting topic in and of itself, so one can also think of this as a study on technology evolution, using solid-state lighting as a case study.
I’ve divided this overview into three parts.  First, I’ll say a few words about traditional lighting.  Second, I’ll say a few words about solid-state lighting in the context of traditional lighting.  Third, I’ll say a few words about the evolution of solid-state lighting markets as a response to the evolution of solid-state lighting technology.
Throughout, I’m going to pick two performance metrics to describe the evolution of the technology.  The first metric will be color rendering index, which is a measure of how pleasing the white light is to the human visual system.  The second metric will be ownership cost, which is a measure of how costly the white light source is to own and operate.  Tomorrow, I’ll talk about how it would be interesting to expand this to other performance metrics, but for today’s discussion we’ll limit them to these two.

## Traditional Lighting

**Traditional Lighting**

**Color Rendering Index (CRI)**

**Ownership Cost ($/Mlmh)**

**Metal Halide &**
**High-Pressure**
**Sodium**

**Linear**
**Fluorescent**

**Standard**
**Incandescent**

**Notes:**
Let’s start with traditional lighting.
Here, I’ve plotted the 26 lamps from the comprehensive 2002 inventory of lighting in the U.S. compiled by Michael Scholand and Eugene Hong of Navigant Consulting.  The axes for the map are, as advertised, color quality and ownership cost.  For color quality, I use the color rendering index.  This is actually a somewhat complex metric, and there is currently quite a bit of debate in the community over it.  For our purpose, though, just think of 100 as being the best, and 0 as being the worst.  For ownership cost, I use the sum of the operating cost (how much it costs to operate the light) and the capital cost (how much it costs to purchase the light).  Both have units of $/Mlmh, so the sum also has the units $/Mlmh.
The lamps themselves fall into three overall families:  incandescent, in green, fluorescent, in blue, and high-intensity discharge, in red.  The area of each circle is proportional to the market size of the lamp in lumens.  As indicated in the parentheses, fluorescent lamps as a family have the largest market share, 62%, HID lamps as a family have the second largest market share, 26%, and incandescent lamps as a family have the smallest, though still substantial, market share, 12%.
To orient you a little better, these three large blue circles all represent linear fluorescent tubes – the 1.5 or 1.0 inch diameter ones that light most of our offices.  This medium red circle represents metal halide high-intensity discharge lamps – the kind often used to light high-bay areas such as warehouses and gymnasiums.  The medium red circle down here represents high-pressure sodium lamps – the kind often used to light outdoor parking lots and highways.  The medium green circle up here represents the standard incandescent lamp that lights most of our homes.
As you can see from this map, the market is trifurcated into a high-CRI high-ownership-cost niche occupied by incandescent lamps, a medium-CRI medium-ownership-cost niche occupied mostly by fluorescent lamps, and a low-CRI low-ownership-cost niche occupied by high-intensity-discharge lamps.

## Solid-State Lighting

**Solid-State Lighting**

_**Phosphor**_
_**Down-**_
_**Conversion**_

_**Color**_
_**Mixing**_

**Color Rendering Index (CRI)**

**Ownership Cost ($/Mlmh)**

**Notes:**
Now let’s consider solid-state lighting, again in the context of the same two technology performance metrics, CRI and ownership cost.  Here, I plot two kinds of things.
Over on the right, I’ve plotted targets from the 2002 U.S. solid-state lighting roadmap, along with a dashed line connecting those targets.  In 2002 we were at roughly 20 $/Mlmh and a CRI of about 70, and by 2020 we want to be at 0.5 $/Mlmh and a CRI of over 80.
Over on the left, I’ve plotted with these solid white lines what one might call the “frontiers of reasonable possibility” for solid-state lighting.  These lines represent the lowest ownership costs that one can reasonably imagine achieving for a given CRI, given an overall approach to solid-state lighting.  I’ve drawn frontiers for the two approaches that are currently being considered:  the color mixing approach shown in the lower right, where one mixes red, yellow, green and blue primary light from LEDs to create white; and the phosphor downconversion approach shown in the upper right, where one mixes blue primary light from an LED with red, yellow and green secondary light from phosphors to create white.  The phosphor downconversion approach, of course, suffers a Stokes-shift energy loss associated with the phosphor downconversion, so its frontier of reasonable possibility is shifted over to the right by about 1.5x.
For both, though, there is a similar dependence of color rendering on ownership cost.  If you concentrate most of your lumens into the green, where the human eye is most sensitive, then you can increase your luminous efficacy, and decrease your ownership cost.  But you will also decrease your CRI.  Conversely, if you expand your lumens to fill the entire visible spectrum, then you will increase your CRI, but your eye will also be seeing colors it isn’t very sensitive to, so your luminous efficacy will decrease, and your ownership cost will increase.  So, basically, the higher the CRI the higher the ownership cost.
I don’t have time to talk in more detail about these curves, except to say that they were calculated using a luminous-efficacy-CRI simulator developed by Yoshi Ohno at NIST, and assumed a constant color temperature of 4000K, with no allowed deviation from Planckian white.
For completeness, I’ve also drawn another frontier, to the left, in black.  This is what one might call the “frontier of physical possibility,” where all the LEDs (red, yellow, green and blue) of a color-mixed solid-state lighting source are 100% efficient.  It’s conceivable that as our scientific understanding expands, we will learn how to move the white frontiers of reasonable possibility over to the black frontier of physical possibility.  But presumably we will never move beyond the frontier of physical possibility.

## SSL Evolution

**$/W (4.5x)**

**lm/W (9x)**

**Ownership (40x)**

**SSL Evolution**

**Color Rendering Index (CRI)**

**Ownership Cost ($/Mlmh)**

_**Costs**_**:**
**Ownership  =  Operating  +  Capital**

***Electricity***

***Luminous***
***Efficacy***

***Power***
***Delivery***
***Cost***

***Lifetime***

**Notes:**
Now let’s overlay the two maps, for traditional and solid-state lighting.  So here you see the colored circles that represent traditional lighting.  And you see the dashed line that represents the roadmap.
But now, I’ve also added a couple of new data points that represent state-of-the-art white LED lamps that you can buy now.  One of these data points I’ve labeled warm white, the other I’ve labeled power white.  Of course, these are only a couple of data points, so one has to be careful about extrapolating into a trend.  But one can already see that we’re not really following the roadmap at all.  Instead, just as with traditional lighting, the white LED lamp market seems to be bifurcating, into a high-CRI high-ownership-cost niche, and a medium-CRI medium-ownership-cost niche.
That kind of makes sense.  After all, people do care about color quality.  So if you’re going to compete with incandescence, you need to have high CRI, and after that, you need to get your ownership cost down.  So one can imagine the evolution of this branch of the bifurcation, now that’s it’s moved up, continuing on to the left, without much further change in CRI.  And, if you’re going to compete with fluorescence, you only need a medium CRI.  So one can imagine the evolution of this branch of the bifurcation also continuing on to the left, without much further change in CRI.  As a side point, one can even imagine that another technology will be spawned, one that moves downwards and to the left to compete with high-pressure sodium lamps for outdoors.  This would be a solid-state lamp that concentrates more of its light into the green, so that is would have a higher luminous efficacy, at the expense of a lower CRI.
So the future evolution of these two solid-state lighting data points might be upwards a little, but mostly to the left.  In fact, ideally, we’d like the warm white to move to the left by about 40x.  That’s a big factor, and to see how to think about it, here on the right I’ve broken the ownership cost down into its two sub-costs.
As I mentioned before, there’s operating cost, which is the cost of electricity divided by the luminous efficacy.  Then there’s capital cost, which is something that might be called the power delivery cost, divided by luminous efficacy and lifetime.  The cost of electricity we can’t control, and lifetime is already high enough for general illumination, so for our purpose here we won’t worry about either of these.
That leaves these two:  the power delivery cost, which is how much it costs you to sink a certain amount of power at the chip, and the luminous efficacy, the lumens you can create given the power you’re sinking at the chip.  Each of these can be improved, and if each is improved to its 2020 roadmap target value, one can calculate the impact on ownership cost.
The results are shown up here for warm white.  Of the 40x decrease in ownership cost, about 4.5x might reasonably come from a reduction in power delivery cost, and about 9x might reasonably come from an increase in luminous efficacy.  I’ll talk about this more tomorrow, so far now I’ll just say that both of these are important challenges.

## SSL Evolution(DraftProjections)

**SSL Evolution****(Draft****Projections)**

**Technology Evolution**

**Technology Diffusion (Market Penetration)**

**Impact on**
**Energy Consumption**

**Impact on**
**Industry Revenue**

**Notes:**
What are the implications of this kind of technology evolution?  Here I’ve drawn a series of panels, all sharing the same time axis.
The bottom panel depicts how SSL technology would evolve if the Roadmap Targets are met – in particular, how the ownership cost would evolve.  The blue curves drawn through the Roadmap targets assume that technology evolves exponentially – i.e., that the rate of evolution is fast at the beginning, but slows as one approaches the limits of physical possibility.  For comparison purposes we have also drawn green and red curves, which less aggressive technology evolution.  Also for comparison, we show the evolution of aggregate traditional lighting in grey.  We expect the ownership cost of SSL to fall below that of aggregate traditional lighting somewhere between 2010 and 1016 – if the aggressive roadmap scenario holds true, then it would be closer to 2010.
The second-from-bottom panel depicts how the lighting market might be penetrated in response to that technology evolution.  Basically, as the ownership cost of SSL approaches and crosses under that of aggregate traditional lighting, we expect consumers to begin to replace their traditional lighting with SSL.  Hence, that’s the point in time when market penetration will begin to increase, though with a lag time associated with how fast traditional lighting burns out, and how fast one can develop a new office and residential building infrastructure for SSL.  If one assumes a lag time of roughly 6 years, then one gets these market penetration curves.  The aggressive scenario agrees reasonably well with a more sophisticated analysis done by Navigant.  The green and red curves correspond, again, to less aggressive technology evolution.
The top two panels depict the impact of technology evolution and diffusion on energy consumption and on industry revenue.
As SSL penetrates the lighting market, its higher efficiency results in a lower aggregate electricity consumption for lighting.  If there were no SSL, electricity consumption for lighting would correspond to the gray curve.  By 2025, lighting will consume about 900TWh/yr of electricity.  At 7 cents/kWh, that’s about a $60B/yr cost to the consumer.  If SSL evolves as projected by the Roadmap, then we’d get this blue curve.  As market penetration approaches 100%, electricity consumption decreases by roughly 2x, which translates to approximately a $30B/yr savings to the consumer.  Of course, projecting into the future is always tricky.  If, instead, luminous efficacy and ownership cost evolve more slowly, and follow the green and red curves, then the ownership cost crossovers are delayed, market penetration is pushed out, and the cumulative savings decrease significantly.  All of these numbers are huge, and so the stakes are very high, and there is a huge benefit to achieving these Roadmap targets.
Finally, if we know the ownership cost of light, and we know the market penetration, then we also know how much industry is making by selling these lights, so we can calculate industry revenue from solid-state lighting.  You can see that it spikes at the ownership cost crossover point in time, and then decreases.  The reason for the decrease is the longer lifetime of solid-state lamps than traditional lamps.  Once you’ve purchased a solid-state lamp to replace a traditional lamp, it will take a while before you’ll need to buy a replacement.  Note that the markets are reasonably sized – on the order of US16B$ or so at their peaks.
Also note that there is a key caveat here.  If solid-state lamps are simply a replacement for traditional lights, then this is what one would expect.  But if solid-state lamps evolve from providing the same performance as traditional light, just more economically, to providing light with new performance attributes, like programmable color temperature, or spatial direction, then solid-state lighting may create new markets in addition to penetrating the old market.

## Semiconductor Industry and SSL (Draft Data)

**Blue/Green/White LEDs**

**HD-DVD Lasers**

**High-Power Electronics**

**High-Speed Electronics**

**CD Lasers**

**Telecom Lasers/Receivers**

**DVD Lasers**

**Red LEDs**

**Energy Conversion, Imaging, Sensing**

**Ultra-High-Speed Electronics**

**High-Power Lasers**

**Compound Semiconductors 2004 ~US$7.3B**

**Silicon 2004 ~US$218B**

**Semiconductor Industry and SSL (Draft Data)**

**AlN**

**GaN**

**InN**

**InSb**

**AlSb**

**GaSb**

**InAs**

**GaAs**

**AlAs**

**InP**

**GaP**

**AlP**

**Projected SSL 2015 ~US$50B**

**Notes:**
Finally, let’s put that market in the context of other compound semiconductor markets.  Here I show the main ones, organized by materials system.  The nitrides are over here at small lattice constants; the phosphides over here at larger lattice constants; the arsenides over here, then the antimonides over here.
I put this together on short notice, so some of the numbers may not quite be right.  But you can see some of the main markets:  the high-speed GaAs-based electronics used in mobile phones, telecom lasers and receivers, CD, DVD and HD-DVD lasers.  And, of course, blue/green/white, and red, LEDs.
The overall compound semiconductor was about US7.3B$ last year, in 2004.  That’s increasing every year, of course, so it’s hard to know what it will be by the 2010-2020 time frame.  But, still, it’s safe to say that solid-state lighting will be comparable to all compound semiconductor markets, if not somewhat larger.

##   Day 1 (General)
1A Overview
1B Technology Evolution

**  **_**Day 1 (General)**_
**1A Overview**
**1B Technology Evolution**

**  **_**Day 2 (Technical Challenges)**_
**2   Roadmap Subtargets/Decisions**
**2A Substrates, Buffers and Epitaxy**
**2B Physics, Processing and Devices**
**2C Lamps, Luminaires and Systems**

**Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy’s National Security Administration under Contract DE-AC04-94AL85000**

**OUTLINE OF TOPICS (DAYS 1 & 2)**

**Notes:**
Yesterday, in Day 1, we talked about general issues related to solid-state lighting: an overview of the grand vision of solid-state lighting; and a summary of some recent work on using solid-state lighting as a case study for how technologies evolve.
Today, in Day 2, we’ll talk about some of the technical challenges associated with solid-state lighting.  In particular, the focus will be on those challenges that stand in the way of solid-state lighting achieving its potential in general white-light illumination, rather than just niche colored-light applications.  Topic 2A will be materials-level challenges:  substrates, buffers and epitaxy. Topic 2B will be lamp-level challenges:  lamps, luminaries and systems.  I should point out that these technical challenges will be very broadly stated in terms of basic underlying physics, and for the most part I will stay away from discussing the detailed implementation of solid-state lighting at any of these levels.
Before we begin with those challenges, though, let me give a brief overview of some additional aspects of the solid-state lighting roadmap that will help put these challenges in context.

## 2 Roadmap Overview

**   **_**Technology Building Block**_**	****	**_**Targets**_**	**_**Subtargets**_**	**_**Decisions**_**	**_**Challenges**_
**	****	**
**0 **_**Introduction to SSL**_**	****	****	**_**7**_**	**_**11**_**	**_**3**_
**1 **_**Substrates, Buffers and Epitaxy**_**	****	****	****	**_**2**_**	**_**14**_
**   ****1.1 Substrates****	****	****	****	****	****	**** 3**
**   ****1.2 Buffers****	****	****	****	****	****	**** 3**
**   ****1.3 Epitaxy Tools****	****	****	****	****	****	**** 4**
**   ****1.4 Epitaxy Processes****	****	****	****	****	**** 4**
**2 **_**Physics, Processing and Devices**_**	****	****	**_**2**_**	**_**13**_
**   ****2.1 Semiconductor Physics****	****	****	****	****	**** 3**
**   ****2.2 Device Processing****	****	****	****	****	**** 3**
**   ****2.3 LEDs and Integrated LEDs****	****	****	****	****	**** 3**
**   ****2.4 Directional Emitters****	****	****	****	****	**** 4**
**3 **_**Lamps, Luminaires and Systems**_**	****	****	**_**1**_**	**_**11**_
**   ****3.1 Phosphors and Encapsulants****	****	****	****	**** 3**
**   ****3.2 Lamps and Electronics****	****	****	****	****	**** 3**
**   ****3.3 Luminaires****	****	****	****	****	****	**** 3**
**   ****3.4 Lighting Systems****	****	****	****	****	****	**** 2**
**   **_**Totals**_**	****	****	****	**_**7**_**	**_**11**_**	**_**8**_**	**_**38**_

**Notes:**
Basically, the roadmap consisted of four kinds of things.
The first were the high-level targets for solid-state lighting technology.  There were 7 of these, and we talked about most of them yesterday, having to do with luminous efficacy, $/klm, lifetime, CRI, etc.
The second were subtargets for various subtechnologies that underly solid-state lighting technology.  There were 11 of these.
The third were decisions that the technology would face as it evolves, and that would be made on the basis of which if the various challenges ended up being solved.  There were 8 of these.
The fourth were the challenges themselves.  These challenges dominated the report, and there were 38 of these.
So, before we get to the challenges, let me briefly walk you through in the next two viewgraphs the various subtargets and decisions.

## Roadmap Subtargets

**Roadmap Subtargets**

**Notes:**
These are the roadmap subtargets.
5 of the subtargets had to do with chip and phosphor operating conditions and costs.  For example, we expect chips to be driven relatively hard, and hence expect chip and phosphor operating temperatures to gradually rise.  Presumably the phosphor temperature will be a little less than the chip temperature, but all of these temperatures are relatively high – in the 200C range.  We also expect input power densities to increase, of course, possibly to the point that these devices actually begin to look like lasers, or power amplifiers.  At the same time, we expect chip and packaging costs to decrease.
6 of the subtargets have to do with chip and phosphor wavelengths and efficiencies.  These are broken down by the approach that is taken to solid-state lighting.
In the wavelength conversion approach, one starts with UV light and downconverts to the visible.  In this case you don’t want a wavelength that is too far in the UV, because then the Stokes shift downconversion loss becomes too great.  But you don’t want a wavelength that is too far towards the visible, because the farther into the UV the better the absorption of most phosphors.  So the roadmap calls for a range of 370-410 nm.  The phosphor wavelengths need to span those wavelengths that render color best while still having good human eye sensitivity.  So the roadmap calls for an orange-red for the long wavelength color, a range that overlaps the green that the human eye is most sensitive to, for the mid-wavelength color, and a pure blue for the short wavelength color.  Note that for this approach there are a number of inefficiency factors, including the Stokes shift inefficiency, the phosphor inefficiency, the package inefficiency, and the chip inefficiency.  With this many inefficiencies in series, it is important for each of these to be as efficient as possible.  So these subtargets end up being quite aggressive – one ends up needing phosphor quantum efficiencies as high as 95%, and chip efficiencies as high as 76%, in order to meet the high-level technology targets.
In the color-mixing approach, one starts with LEDs of various colors, and mixes them to create white light.  The ideal wavelength ranges are similar.  But because there are no Stokes shift or phosphor inefficiencies, one doesn’t need to be as aggressive on the chip efficiency – it only needs to be as high as 53% in order to meet the high-level technology targets.
In the hybrid approach, one starts with a blue LED, then uses this blue in addition to downconverting some of the blue into the green and red to create white.  Just as with the wavelength conversion approach there is a Stokes shift inefficiency, but the inefficiency is less since one is starting in the blue rather in the UV.  So the chip power conversion efficiency needs to be higher that for the color mixing approach, but not as high as for the wavelength conversion approach.

## Roadmap Decisions

**Roadmap Decisions**

**0 **_**General**_
**Will the SSL-LED chip “engine” be driven at low input power densities with low cost/cm****2**** and T****oper****, or will it be driven at high input power densities at high cost/cm****2**** and T****oper****?**
**Will SSL-LED white light production be through a wavelength conversion, color mixing, or a hybrid approach?**
**How many colors (and in what wavelength ranges) will best balance the three constraints of pure white, high color rendering and high luminous efficacy?**
**1 **_**Substrates, Buffers and Epitaxy**_
**Which semiconductor materials family will form the basis for the SSL-LED chip “engine” -- AlGaInN only, or a combination of AlGaInP and AlGaInN?**
***Which low-defect-density substrate or substrate+buffer combination will form the basis for epitaxial AlGaInN devices:  Native GaN, Sapphire/SiC + Buffer, or Removable GaN?**
**2 **_**Physics, Processing and Devices**_
**Will the SSL-LED light chip “engine” be based on spontaneous (LEDs) or stimulated (lasers) emission devices?**
***Will the SSL-LED light chip “engine” be a single-function generator of monochromatic light, or will it monolithically integrate other functions, such as white-light production and programmable drive electronics?**
**3 **_**Lamps, Luminaires and Systems**_
***Will SSL-LED white lighting compete with conventional lighting by emphasizing traditional attributes such as low cost-of-ownership, high efficiency and environmental friendliness, or will it compete by emphasizing new attributes such as programmability and improved interplay with building architectures and the human visual system?**

**Notes:**
These are the roadmap decisions, and I’ll just briefly run through them.

## 2A Substrates, Buffers, Epitaxy

***2 Constraints on substrate quality***

***1 Constraints on semiconductor materials***

***3 Constraints on epitaxy tools and processes***

**Notes:**
OK, now let’s start in on the technical challenges.  As I noted earlier, there were about 38 of them in the roadmap.  But I’m not planning to go through all of them.  Instead, I’ve picked out a few issues in each of the three overall roadmap areas to discuss, from a more basic physics viewpoint.
Let’s start with substrates, buffers and epitaxy.  In this area I’ll talk about three issues, phrased as “constraints”.  The first will be semiconductor materials, the second will be substrate quality, and the third will be epitaxy tools and processes.

## Semiconductor Materials Constraints

**Semiconductor Materials Constraints**

**Notes:**
Let’s start with materials, and ask the question:  what are the basic materials choices that can enable us to get the widest range of visible colors?
To see these choices, I’ve graphed two key physical properties, bandgap and hardness, for all the binary octet semiconductor materials.  In order to have good color quality, the materials need to span the right bandgap range to emit red, yellow, green and blue light.  And in order to have good reliability, the material cannot be too soft, otherwise its degradation rate during operation is likely to be too fast.  In fact, if the material is too hard, that’s also a disadvantage, since then it is likely to be difficult to process.  So the candidate materials must lie approximately within this narrow band of color here, and between the two dashed white lines.
In a way, this map just quantifies what we already know – that there aren’t very many candidates.  The IV-IVs have bandgaps that are just too narrow, and, even worse, as indicated by the open circles, they are all indirect gap with very low luminescence efficiencies.  As the ionicity of bonding increases, bandgaps increase but also the materials get softer.  So the I-VIIs, which have very ionic bonds, have bandgaps that are too wide, and they are also all too soft.
The II-VIs have bonds that are not quite as ionic, so they have narrower bandgaps and are a little harder.  In fact, you’ll note that Zn-based materials, ZnOSSeTe, have bandgaps that are nearly perfectly matched to solid-state lighting.  However, they are just a little on the soft side, and experience has shown that degradation rates at least for lasers are just a little too high.  Still, they are close, and it isn’t inconceivable that for LEDs degradation rates could be made much lower.
The III-Vs have bonds that are even less ionic, so they have even narrower bandgaps and are a little harder.  This combination gives two good, though not perfect, families of III-V materials.  The first is the AlGaInP family, which is very good in the deep red, but isn’t very good if pushed into the light red, much less into the yellow, green and blue.  The second is the AlGaInN family, which is very good in the blue and purple, but isn’t very good if pushed into the green, yellow and red.
So the trade-off here is:  If the AlGaInN family of materials can be pushed further into the green and yellow, then this family of materials will be all we will need – reliability will certainly not be a problem.  But if it cannot, then we may need to consider other materials, such as the Zn-based II-VI materials, provided their reliability issues can be surmounted.  Or, we may end up stuck with phosphors for down-conversion of purple and UV light into the green and yellow, and a less efficient solid-state lighting technology.

## Substrate Constraints

**Substrate Constraints**

**2   In InGaN, E****g**** fluctuations (50meV?)  trap e-h pairs away from dislocations**

**1   In GaN, radiative e-h recombination is quenched within 160nm? radii around dislocations**

**3   As temperature increases, traps become leaky**

**4   Near-unity radiative efficiency is only a loose constraint:           ********disl**** < 10****7****-10****9****/cm****2**

**7   50,000 hr lifetime is a tighter constraint:                ********disl**** < 10****6****-10****8****/cm****2**

**5   If degradation rate is mediated by dark-line defects and scales as (********disl****) (j****current****) e****-dE/kT****, and if Egawa, et al’s data (J Appl Phys 82, 5816 (1997)) is fit, then:**

**6 To get lifetimes of 50,000 hr:**

**Notes:**
Now let’s turn to the GaN substrates or pseudo-substrates on which the chips are most likely to be built.  In this case, there are two high-level targets that impact the substrate directly.  The first is the internal radiative efficiency of the epimaterial grown on the substrate.  The second is the lifetime of the device.  Both may scale with dislocation density, which I assume here is the main undetermined parameter associated with the substrate.
Let’s start with internal radiative efficiency.
There is a lot of evidence now indicating that, in GaN, radiative recombination is quenched in a dark zone (shown in purple) around dislocations.  So, as dislocation density increases, internal radiative efficiency decreases, as shown by the purple curve.  For a 160nm or so quenching radius, this decrease begins to be noticeable at around a dislocation density in the 1e7-1e8/cm2 range.
In InGaN, one is saved by nanoscale composition fluctuations (shown in green), which trap electron-hole pairs away from the dislocations.  As dislocation density increases, internal radiative efficiency still decreases.  But, as shown in the green curve,  the decrease doesn’t begin to be noticeable until a dislocation density in the 1e9-1e10/cm2 range.
However, at higher-than-room operating temperatures, it is possible for the carriers to leak out of these traps – the traps become translucent.  Then, the decrease in radiative efficiency becomes noticeable at lower and lower dislocation densities.  For both of the scenarios discussed in the previous viewgraph, the decrease now begins to be noticeable at a dislocation density in the low 1e9/cm2 range.
So, the dislocation density necessary for efficient InGaN chips is probably in the low 1e9/cm2 range, and for efficient GaN chips is probably in the mid 1e7/cm2 range.  But both of these are within the range of current buffer layer technologies, so high internal radiative efficiency seems to be a relatively loose constraint on dislocation density.
But now let’s consider lifetime.
We know that in many high-current-density optoelectronic technologies, degradation is caused by non-radiative recombination at dislocations, which causes them to move, multiply, and eventually form dark-line defects that absorb light and reduce overall chip efficiencies.  We don’t yet know enough about the physics of degradation in GaN and InGaN LEDs and lasers, but it is reasonable to expect that it ultimately may be limited by a similar kind of non-radiative recombination.  That means it would scale with both current density and dislocation density, and would be “lightly” thermally activated.  If we assume this kind of scaling, fit data from Egawa et al at Nagoya University, then one can project these three curves.
The curve in grey is the lifetime for a small chip driven fairly softly – this is roughly the past year’s technology.  To get lifetimes of 50,000 hours, one needs a dislocation density of the order 2e9/cm2, which is perhaps in the right ballpark.  The curve in red is the large chip scenario -- to get lifetimes of 50,000 hours, one needs dislocation densities of the order 4e7/cm2.  The curve in blue is the small chip scenario -- to get lifetimes of 50,000 hours, one needs dislocation densities of the order 8e5/cm2.
So, if these projections are valid, the dislocation density necessary for long-lived GaN and InGaN chips is in the 1e6 to 1e8/cm2 range, depending on whether the small or large chip scenario “wins.”  Better data and better models are necessary, of course, but this analysis indicates that lifetime may constrain dislocation density more tightly than high radiative efficiency does.
The good news is that this dislocation density is still pretty high, on the scale of things; and it may mean that there is no need to push so hard for bulk crystal growth technologies that usually achieve defect densities in the range 1 to 1e4/cm2.  The bad news is that this dislocation density is lower than can be achieved by either the common GaN on sapphire thin buffer technology or epitaxial lateral overgrowth technology; and may mean that some intermediate technology (e.g., thick HVPE buffers) will be necessary.

## InGaN Epitaxy Process Constraints

**Notes:**
Finally, let’s turn to epitaxy processes.
Basically, the challenge here is getting to the green, especially to the 550 nm green that the human eye is most sensitive too.  The problem is that there are a number of severe and competing constraints which seem to circumvent getting there.
(1) The first constraint is to get the composition of In high enough.  If the InGaN is strained on GaN, then the In composition needs to be higher than it is if it is not strained (e.g., grown on a substrate such as ZnO with a lattice constant larger than that of GaN).  I don't know what the most reliable numbers are.  But if those in the graph are reasonable, then In compositions near 50% may be necessary for strained material, while In compositions near 30% may be sufficient for unstrained material.
(2) The second constraint is the pyrolysis temperature of trimethylindium.  Ideally, one would like to grow just above that temperature, but not much above it, since otherwise there's a good chance of substantial parasitic particle nucleation in the boundary layer above the wafer.
(3) The third constraint is the evaporation rate of InN.  Ideally, one would like to grow at a temperature low enough so the evaporation rate is low compared to the growth rate.
(2-3) These two constraints together try to drive the growth temperature lower.
(4) The fourth constraint is islanding driven by a combination of strain and chemical immiscibility.  Steve Lee and others at Sandia have been looking at this in the InGaAs system, but a lot more work needs to be done, especially to transfer this understanding to the InGaN system.  The curve that's drawn is the simple bulk phase decomposition diagram, without strain and without surface morphology considerations.
(5) The fifth constraint is the epi temperature required for good enough adatom mobility to get high crystal quality.  The curve that's drawn is a linear curve that connects the usual 1050C GaN MOCVD temperature with an InN MOCVD temperature scaled downwards by the ratio of melting temperatures.
(4-5) The maximum of these two constraints is drawn as a solid line.  Ideally, one wants to grow at temperatures above this maximum (though there may be some questions and uncertainties about (4).
If one puts all these constraints together, then the window for growing high-quality green InGaN, strained on GaN, appears to be vanishingly small.  But, many of the curves drawn are just guesses, and not well understood, so there may yet be some window.  Plus, the window for green InGaN, grown unstrained on an intermediate substrate, would likely be much wider.

## 2B Physics, Processing, Devices

***2 Power Delivery Cost***

***1 Luminous Efficacy***

**Notes:**
Now let’s move on to technical challenges that have to do with physics, processing and devices.
The two issues here I’d like to spend some time on are: luminous efficacy, and power delivery cost.  I was going to discuss piezoelectricity, but decided there wasn’t time.  Instead, I’ll just mention that GaN has among the highest piezoelectric coefficients of all the compound semiconductors, and that this is generally undesirable.  It separates electrons and holes in quantum wells, decreases their spatial overlap, and decreases the radiative recombination rate.

## Luminous Efficacy & Power Delivery Cost

**$/W (4.5x)**

**lm/W (9x)**

**Ownership (40x)**

**Luminous Efficacy & Power Delivery Cost**

**Color Rendering Index (CRI)**

**Ownership Cost ($/Mlmh)**

_**Costs**_**:**
**Ownership  =  Operating  +  Capital**

***Electricity***

***Luminous***
***Efficacy***

***Power***
***Delivery***
***Cost***

***Lifetime***

**Notes:**
Let me start by putting luminous efficacy and power delivery cost in context.
Yesterday, we talked about breaking ownership cost into operating and capital costs.  And we talked about how these costs in turn could be broken down into the cost of electricity, luminous efficacy, lifetime, and power delivery cost.  Of these, luminous efficacy and power delivery cost are perhaps the two most important.  In principle, improvements in luminous efficacy have the potential to reduce ownership cost by 9x, and improvements in power delivery cost have the potential to reduce ownership cost by 4.5x.
So let’s drill down a little and talk about each of these in turn.

## Luminous Efficacy: intexteye

**Notes:**
First, luminous efficacy.  Luminous efficacy can be thought of as the product of the internal radiative efficiency, the external extraction efficiency, and the human eye sensitivity.  The most basic of these three is the internal radiative efficiency, so let’s focus on that one.
Here I show, in the bottom figure, a plot of internal radiative quantum efficiencies of LEDs where the active light-emitting layers are fabricated from the GaN-InN family of materials. Pure GaN emits at roughly 370nm.  Adding 40% InN gets you to the red, and in between you get blue, green and yellow.
The data points are from Nichia and LumiLeds, and are not the most up-to-date numbers, particularly in the purple and UV.  But they serve to illustrate two key issues.
The first issue is that, at all wavelengths, the internal radiative efficiencies are a lot lower than unity.  If we’re targeting a 50% electricity-to-usable-light power conversion efficiency, then these internal radiative efficiencies must be very close to unity.  The reason is that there will be lots of other losses that will be almost impossible to reduce, especially related to light extraction from the chip, but also including power losses on the way to the chip.
The second issue is that, although the internal radiative efficiency does increase from the UV to the purple and to the blue, it decreases in the green, and is nearly zero in the yellow and red.  This is of course why the dominant current approach to white light creation is phosphor down-conversion of light from blue, purple or near-UV LEDs.
To see at one more level of detail what might be going on, just above I show a plot of radiative and non-radiative electron-hole recombination rates.  The numbers were estimated using data from Kyoto University, Nichia, Linkoping University, and UCSB.  The data in the two graphs aren’t from the same devices or structures, so they can’t be compared.  However, they do give a semi-quantitative idea of the trends.
Now, the internal radiative efficiency is the result of a dynamic competition between radiative and non-radiative recombination, so if radiative recombination were much faster than non-radiative recombination, internal radiative efficiency would be near unity.  Instead, radiative recombination is slower, rather than faster, than non-radiative recombination, throughout the wavelength spectrum.  So the key challenge is to reverse this ordering.  Now, you can either do that by increasing the radiative recombination rate, or by decreasing the non-radiative recombination rate.
In fact, radiative recombination in pure GaN, here at roughly 365nm, is relatively fast.  Radiative recombination coefficients generally increase with bandgap, so GaN, with the widest bandgap, has the highest radiative recombination coefficient of all the III-V compound semiconductors.  So, aside from going to stimulated emission devices, it’s not likely that this rate is going to be increased by much.  The problem is that non-radiative  recombination is even faster, probably because of dislocations and other defects associated with growth of GaN on the commonly-used but lattice-mismatched sapphire substrates.  So, a major materials challenge is to develop lattice-matched substrates so that low defect-density InGaN can be grown.  And, even better, to develop such substrates at the four different lattice constants needed for four different InGaN compositions – one for blue, one for green, one for yellow, and possibly one for orange!
Interestingly, you’ll notice that, even without lattice-matched substrates, non-radiative recombination is already decreasing as one adds In.  That’s commonly thought to be due to the chemical immiscibility of GaN and InN, and to the tendency for InGaN alloys to phase separate into InN-rich and GaN-rich regions.  The problem is that as this happens, local strain develops, because GaN and InN have such different lattice constants.  The strain causes large piezoelectric fields, which spatially separate the electrons and holes within the InN-rich regions, slowing radiative recombination.  Eventually, even though non-radiative recombination is also getting slower, radiative recombination is getting slower faster, and the internal radiative efficiency goes to zero.
So it’s not yet clear whether, in the long run, phase separation will be viewed as good or bad.  If you’re stuck with lattice-mismatched substrates and a high density of dislocations and other defects, then you need phase separation to slow non-radiative recombination, and the challenge will be to somehow reduce the piezoelectric fields to speed up radiative recombination.  But if lattice-matched substrates can be developed, then you probably don’t want phase separation, and the challenge will be to somehow, through non-equilibrium growth techniques, overcome the natural tendency for such phase separation.

## Power Delivery Cost

**Notes:**
Now let’s talk about power delivery cost.  This is basically the cost associated with a packaged chip that can sink a certain number of Watts:  $/Win.  This cost can itself be broken down into the ratio of two other costs:  the cost of the packaged chip, normalized by the area of the chip it houses, or $/cm2, and the power density sunk by the chip, or Win/cm2.  Breaking the cost out in this way draws attention to the fact that chip area is an important design choice in solid-state lighting.
This plot shows contours of constant power delivery cost, from the 2002 value of $3.85/Win to the 2020 roadmap value of $0.40/Win.  The contours look pretty close together, but this is a log-log plot over 8 orders of magnitude, so they are further apart than they appear.
The main point I want to make here is that there are different ways of achieving the necessary power delivery cost.  One is using expensive chips driven hard.  This is what I call the high-power infrared laser regime, at high input power density and high cost per unit area.  A second is using modestly expensive chips driven modestly hard.  This is what I call the red LED regime, at medium input power density and medium cost per unit area.  A third is using inexpensive chips driven very softly.  This is what one might call the organic LED regime, at low input power density and low cost per unit area.
The plot also shows the 2002 to 2004 solid-state lighting power white trajectory, extrapolated into the future.  Note that the extrapolation looks like it’s heading towards the high-power infrared laser regime.  This is what makes me, for one, tend to wonder whether in the end it will be a laser that will win.

## 1  Lamp targets (1.5 klm/lamp, 200 lm/W, $3/lamp) imply overall chip targets (lm/chip, W/chip, W into heat sink, $/chip)

**2  $/chip target implies inverse relationship between chip area and chip areal cost**

**3  Two extremes in chip areal cost (and chip area) subtargets:**

**4  Heat conduction physics implies inverse relationship between thermal resistance and (chip area)****1/2**

**5  Two extremes in thermal resistance (and operating temperature) subtargets**

**Chip Size**

**Notes:**
Now, to see in a little more detail what the implications of chip area are, here I’ve drawn a schematic of what that chip needs to look like.
First, we’re looking for about 1.5klm of white light per lamp.  That’s actually a pretty convenient unit of light, because it’s roughly the output of a 75W light bulb.
Second, we’re looking for about 50% conversion efficiency, or 200 lm/W.  1.5 klm of light divided by 200 lm/W means that we need 7.5W of input power.  Half of that 7.5W goes into white light generation; the other half, or 3.75W, is lost and must be sunk by the heat sink.
Third, we’re looking for a capital cost of light of 2 $/klm to the consumer.  To get 1.5 klm means we’d pay $3.  Assuming a factor of 2x mark-up, and a factor 2x due to packaging cost, that means we’re looking for a chip that costs 3$ divided by four, or 75 cents.
So, all together, we have a 75 cent chip, driven by 7.5W, producing 3.75W of white light and sinking 3.75W of waste heat.
What I haven’t drawn on this schematic is how big the chip needs to be, because we don’t yet know how big the chip needs to be.  What we do know, instead, are some of the trade-offs that go into determining how big the chip needs to be.  These trade-offs are indicated in these three panels, all having chip area as their y-axis.
The first trade-off is the areal cost of the chip (in $/cm2).  For a fixed chip cost, the chip areal cost scales inversely as chip area.  If the chip is large, its areal cost needs to be low; if the chip is small, its areal cost can be high.
The second trade-off is the operating temperature of the chip.  As shown here, thermal impedances (RT) generally scale inversely as the square root of chip area.  These data points are research results for high-power lasers with state-of-the-art diamond-heat-sinking.  This line assumes that solid-state lighting chips will be within a factor 3x of these research results.  What this means is that, for a fixed power wasted into the heat sink, the chip operating temperature scales inversely as the square root of chip area.  If the chip is large, its operating temperature can be low; if the chip is small, its operating temperature is going to be high.
In fact, one can imagine two extremes.
On the one hand, there is the low-cost extreme, which one might call the red LED scenario, because GaAs-based high-brightness red LEDs, which cost about $30/cm2, are one of the least expensive compound semiconductor technologies.  In fact, if GaN-based blue or white LEDs become as cheap, the size of the chip can be pretty large:  about 1.5mm2.  On the other hand, there is the high-cost extreme, which one might call the high-power laser scenario, because GaAs-based high-power IR lasers, which cost about $200-300/cm2, are one of the more expensive compound semiconductor technologies.  If GaN-based LEDs or lasers end up being this expensive, the size of the chip will need to be much smaller:  about 0.15mm2.
At the cheap, red LED extreme with large, 1.5mm2, chip areas, the operating temperature can be as low as 375K, only 75K above normal room temperature.  But at the expensive, high-power laser extreme with 0.15mm2 chip areas, the operating temperature may need to be as high as 450K, 150K above normal room temperature.
So the trade-off is:
If light creation in the chip can be made very efficient, then hot chips will be OK, and small highly-processed chips that maximize light extraction will also be OK.  More expensive and smaller is better for efficient light extraction from the semiconductor, because more expensive and smaller chips can have more sophisticated chip processing, and an enhanced ability to control optical modes through resonant cavities, or photonic lattices, or texturing.  You could even make a laser, which is the ultimate in optical mode control.
But if light creation cannot be made very efficient, then hot chips will not be OK, and large, less-highly-processed chips that run cooler will probably be necessary.  Bigger is better for efficient light creation within the semiconductor, because bigger chips sink heat more easily and run cooler, so the less important parasitic non-radiative electron-hole recombination in the semiconductor will be.
As a side comment on the laser scenario, one sometimes hears that vertical-cavity rather than edge-emitting lasers are likely to be the best suited for solid-state lighting.  I have a feeling that won’t be the case.  The reason is illustrated in the upper right.  Basically, VCSELs are too temperature sensitive.  When you heat a semiconductor, its gain spectrum shifts.  If you have a lot of longitudinal cavity modes that can lase, as in an edge emitter, then that shifting doesn’t matter much, you’ll just lase on a new mode.  But if you have very longitudinal cavity modes than can lase, as in a vertical cavity laser, then that shifting matters a lot.  There may be ways around this, but generally speaking I have a feeling edge emitters will be a better bet than vertical cavity lasers for solid-state lighting.

## 2C Lamps, Luminares, Systems

***2 Approaches to White Light***

***1 Color Rendering and Luminous Efficacy***

***3 System-Level SSL Driving Forces***

**Notes:**
Finally, let’s move on to technical challenges that have to do with lamps, luminaires and systems.
The three issues here I’d like to spend some time on are:  the trade-off between color rendering and luminous efficacy, the various approaches to white light production, and the forces that drive solid-state lighting technology at the system level.

## Color Rendering and Luminous Efficacy

**Color Rendering and Luminous Efficacy**

**Relative sensitivity for 3 types of cones**

**After Bruce MacEvoy http://www.handprint.com/HP/WCL/color1.html**

**Vertebrates**

**Mammals**

**Primates**

**After Zukauskas, et al Appl Phys Lett 80, 234 (2002)**

**Notes:**
Let’s start with the trade-off between color rendering and luminous efficacy.
The three photos in the lower left are intended to give a feel for this metric of color rendering.  Many animals see in black and white, so color rendering isn’t an issue at all.  Many mammals see in only two colors.  But primates see in three colors.
The three colors that we do see are illustrated in the upper graph, which shows the relative sensitivity of the three types of cones in the human eye:  one type that sees blue, another type that sees green, and yet another that sees red.  Note that this is a log scale, so the differences between the three sensitivity curves is larger than it appears.
So the idea is to fill this sensitivity curve with light of various colors.  These graphs from a study by Zukauskas illustrate four ways of doing this, with different numbers of colors:  two, three, four, and five.  Of course, as you fill out the curve with more colors, particularly the blue and red, the color rendering index increases, but then the luminous efficacy also decreases.
This is illustrated in this plot, also from Zukauskas’ study, where they simulated the trade-off between CRI and luminous efficacy, for various numbers of colors.  The best luminous efficacy is the same no matter how many colors, because they are all being concentrated in the green.  As you allow the luminous efficacy to decrease, the CRI can increase.  But the CRI saturates, and the saturation value does depend on how many colors there are.
With two colors, the CRI is limited to about 20 or so.  With three colors, the CRI is limited to about 85 or so.  And with four colors, the CRI is limited to about 98 or so.  So there’s definitely no need for more than four colors, though it may be that three colors may be not enough.

## Approaches to White Light

**Sunlight**

**Incandescence**

**Computer Monitor**

**Approaches to White Light**

_**Phosphor**_
_**Down-**_
_**Conversion**_

_**Color**_
_**Mixing**_

_**Tri-color phosphor Fluorescent Lamp Spectrum**_

**Notes:**
Now let me say just a few more words about the trade-offs and specific challenges associated with the two main approaches to white light.  We’ve already mentioned that there are two main approaches to creating white light.
The first approach is phosphor down-conversion, shown at the upper left.  You start with a blue LED, then down-convert some of the blue into a distribution of red, yellow and green colors using phosphors.  The advantage of this approach is that you only need an efficient blue LED, you don’t need efficient LEDs at other colors.  The disadvantage, however, is that the phosphor may not be perfectly efficient.  In fact, there is an irreducible 50% efficiency penalty due to the Stokes shift associated with the photon energy downconversion.
Another issue is that many phosphors are broadband, not line, emitters.  This is OK for the green, where you want a broad spectrum for good color rendering.  But for the red, you want a sharp cut-off, because if you have a tail in the deep red, where the human eye isn’t very sensitive, you are basically wasting light.  Here’s an example of the emission spectrum from a tri-color phosphor for a fluorescent lamp, and you can see that it is relatively ideal.  There is a large peak in the orange-red, with very little in the deep red.  This is the kind of spectrum one would like to duplicate with solid-state lighting.
The second approach is color mixing, shown at the lower left.  You start with LEDs of various colors, then optically mix them to create white.  The advantage of this design choice is that there are no phosphor inefficiencies.  The disadvantage, though, is that you need efficient LEDs at a number of colors.
And that’s the main issue.  To get a good quality white light from monochromatic light, you need at least three, and possibly four wavelengths.  One such set of four wavelengths is shown as grey dots along the perimeter of this chromaticity diagram – 460, 530, 570 and 610nm.  By mixing these four colors with various intensities, one can produce light of any color within these dashed boundaries, and white light of any color temperature along this Planckian black-body equivalent curve, all the way from the warm 2850K light associated with incandescence, to the 4800K light associated with sunlight, to the cool 6500K light associated with computer monitors.  But you do need at least three, and possibly four, of these colors, and right now nobody knows how to make efficient chips at two of the colors -- the green and yellow.
Of course it is possible, and some companies are trying this, to create a pseudo-color mixing approach.  You use blue from an LED, combine it with green produced from phosphor-downconverted blue, then combine it with red from an LED.  So you still end up with independent control over three colors, but one of the colors, the green, is made using phosphor downconversion.

## SSL Driving Forces

**SSL Driving Forces**

**Ownership Cost ($/Mlmh)**

**Color Rendering Index (CRI)**

**Notes:**
Finally, let me just say a few additional words about what really drives solid-state lighting.  It isn’t white lighting, at least not yet, because solid-state lighting isn’t yet really competitive with traditional lighting there.
Instead, it’s all the various niche applications that can benefit from LEDs, like signs and displays, automotive, signals, and mobile appliances.  All of these applications seek performance metrics that can be different from those important for white lighting.
For example, the size of the light source is really important for mobile appliances, but less important for signs and displays.  The shock threshold is really important for mobile appliances and automotive, but less important for signs and displays.  Turn-on time is relatively important for almost all of these applications.  And so on.  So the evolution of the technology is pulled by a complex set of markets and applications, via a complex set of technology performance metrics.