# Presentation: 921168

## Technology Footprinting and Solid-State Lighting

**Jeff Tsao and Kevin Boyack  ****·****  Sandia National Laboratories**
**Mark Huey and Ann Miksovic  ·  Strategic Perspectives**

**Break the technology apart into sub-technology areas**
**Develop a lexical signature for these sub-technology areas**
**Identify the footprints of those signatures in a technology activity dataset (e.g., patents)**
**Compare the footprints with a desired footprint**

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

**Notes:**
In this set of viewgraphs, we explore the development of a tool that might be called something like technology footprinting, and the preliminary application of that tool to solid-state lighting.
The basic idea is illustrated in the following sequence, which we will cover in turn in the following viewgraphs.
First, we break the technology into sub-technology areas – in this example, A, B, C and D.
Second, we develop lexical signatures for these sub-technology areas – descriptive words or phrases that are unique yet relatively commonly used to describe the areas.
Third, we use those signatures to identify footprints in a technology activity dataset (e.g., patents).
Finally, we compare the resulting footprints to those desired from a higher-level program management point of view.

## DOE-EERE 2005 SSL Sub-Technology Areas

***from Navigant, “U.S. Lighting Market Characterization Vol II Energy Efficient Lighting Technology Options” (Sep 2005), Sections 3.4 and 3.5.***

**Notes:**
Let’s start by breaking the technology we are interested in (solid-state lighting) into sub-technology areas.  There are many ways of doing this, and the choice of which way is best probably depends on the questions one is trying to answer.
In this preliminary work, we started out trying to break the technology into the 19 solid-state lighting technology challenge areas that were identified in last year’s DOE-EERE report (US Lighting Market Characterization Volume II – Energy Efficient Lighting Technology Options).  The first twelve areas are related to LED technology, the last seven areas are related to OLED technology.
This is a convenient set of sub-technology areas, because it already has associated with it lexical signatures.  These are the “technology description and energy saving principle” and “next steps and data gaps” texts that were associated with the various areas.  Here we’ve listed some of that text alongside each of the sub-technology areas.
Now, using these lexical signatures, we can measure the lexical similarity of these sub-technology areas with records in any of a number of technology activity datasets.  In this study, we used the solid-state lighting U.S. patent database developed in early 2006 and used in the report “U.S. Competitiveness in Solid-State Lighting: Illuminating a Gathering Storm” prepared by Strategic Perspectives, Inc., in April 2006.  We anticipate documenting its development in more detail in a chapter tentatively titled “International trends in solid-state lighting:  analysis of the journal and patent literature,” to be submitted for publication in an edited volume tentatively titled “Solid State Lighting and Illumination Engineering” to be published by SPIE.
Those records that are lexically most similar to a particular sub-technology area are considered to be the “footprint” of that area.
Of course, the footprinting will not be perfect because the lexical signatures are not perfect.  Many of the same words and phrases are used in more than one technology challenge area.  And even if the words and phrases associated with the sub-technology areas were unique, a given record might still contain words or phrases from more than one sub-technology area.  As a consequence, a given record may well be matched to a number of sub-technology areas.  (Though, for the purposes of this analysis, only the closest-association was used as a match).
Indeed, it is clear from the text associated with the sub-technology areas that there is a significant overlap between some of them.

## Lexical Clustering of Sub-Technology Areas

**A LED Lamps and Chips**

**B LED/OLED Drivers & Electronics**

**C LED Materials**

**D LED/OLED Light Extraction and Optical Tools**

**E OLED Panels and Lamps**

**F OLED Materials and Structures**

**Notes:**
That overlap is illustrated in this viewgraph, which is a matrix in which each entry is the lexical similarity between one sub-technology area and another.  The diagonal elements are all unity, since each sub-technology area is perfectly similar to itself.  The off-diagonal elements are color coded, so that darker blue represents more similar, and lighter blue represents less similar.
Entries (i.e., Sub-Technology Areas) have been reordered for ease of viewing according to lexical similarity.
One can see that there are clusters of areas that are more similar to each other than to the rest.  These clusters are indicated by the red squares.  Areas 1-4 and 10-11 form a cluster that might be called “LED Lamps and Chips.”  Area 5 forms a cluster all by itself that might be called “LED/OLED Drivers and Electronics.”  Areas 6-8 form a cluster that might be called “LED Materials.”  Areas 9, 12 and 17 form a cluster that might be called “LED/OLED Light Extraction and Optical Tools.”  Areas 13, 14 and 18 form a cluster that might be called “OLED Panels and Lamps.”  And areas 15, 16 and 19 form a final cluster that might be called “OLED Materials and Structures.”
So in what follows, we have used this clustering.  We call these clusters sub-technology macro areas.
Decisions on where to delineate these macro areas have been made based on lexical similarity scores (in practice, a lexical similarity score < 0.10 [and colored light blue in the grid above] disqualifies an entry from inclusion in a macro area) as well as subject matter expertise (e.g., a judgment call was made that “OLED Light Extraction” should be grouped with “Optical Tools” instead of “OLED Panels and Lamps”)
But we should also note for future work that it might be possible to eliminate this clustering step through more judicious choices of unique key words and key phrases associated with each of the sub-technology areas.

## Representative Patentsin Sub-Technology Macro Areas

**Notes:**
The results of the clustering process are illustrated here -- the sub-technology macro areas, their constituent sub-technology areas, and some representative patents that were binned by their lexical similarity into the various areas.
In general, we felt that the binning process was effective in terms of placing items in the right category, and of placing like-items together.  For instance:
In the “LED Lamps and Chips” macro area, which includes phosphor materials, white light systems and reflector lamps, there is a patent by Lumileds Lighting on tri-color lamps, and there is one by Nanocrystals Technology on nanophosphors.
In the “LED/OLED Drivers & Electronics” macro area, there is a patent by Great Britain’s Defence Department on edge connectors for display panels, and a patent by Gelcore on the optics and electronics for a modular array of LEDs.
In the “LED Materials” macro area, there is a patent by Motorola on a photon recycling LED, and a patent by JDSU on arsenide-nitride optoelectronic materials.
In the “LED/OLED Light Extraction and Optical Tools” macro area, there is a patent by Cree on enhanced light extraction, and a patent by HP on transparent substrates for direct light extraction.
In the “OLED Panels and Lamps” macro area, there is a patent by Princeton University on a stacked full-color OLED lamp, and there are several patents by Kodak on manufacturing processes.
In the “OLED Materials and Structures” macro area, there is a patent by Philips on a layered OLED structure, and there is a patent by IBM on a hybrid organic/inorganic material for use in an OLED.
Note that the binning process is not perfect.
Some of the patents had very low lexical similarity scores.  Out of 7,291 patents, 930 were determined to not be binnable (we used a somewhat arbitrary, but empirically effective, lexical similarity threshold of 0.01).
As mentioned already, of the patents that were lexically similar to at least one of the sub-technology macro areas, some were similar to more than one sub-technology macro area.  In these cases, we simply binned the patent into that sub-technology macro area to which it was most similar.  One could instead have assigned such patents partial weights to the various sub-technology macro areas.  But for this study we quantized the patents, and binned them into a single sub-technology macro area.

## Sub-Technology Macro Areasand Energy Savings Potentials

**Notes:**
Now let’s take this one step further.
Each of the original sub-technology areas had energy savings potentials (in Quads/y) associated with them, illustrated here.  These energy savings potentials were derived by Navigant Consulting, and represent the best available mapping of technology areas to energy savings.
What this means is that just as these sub-technology areas were rolled up into sub-technology macro areas, the energy savings potentials can be rolled up.  In other words, we can identify an energy savings potential for each of the macro areas, as illustrated in the second column from the left.
Sub-technology macro area A, “LED Lamps and Chips” has the highest estimated energy savings potential, 4.7 Quads/y.  Sub-technology macro area B, “LED/OLED drivers and electronics” has the lowest estimated energy savings potential, 0.2 Quads/y.  And the other sub-technology macro areas have intermediate estimated energy savings potential.

## Alignment betweenPatent Activity and Energy Savings Potential

**Notes:**
Now, if energy savings potential were the main “driver” for solid-state lighting patents, we might expect patent activity (as a proxy for research activity) to be proportional to energy savings potential.  In other words, if there were perfect alignment between patent activity and energy savings potential, then on a plot of total patents vs energy savings potential, we’d fall on the white diagonal line – the higher the energy savings potential, the greater the total patents.
In fact, we don’t quite fall on the line.  Sub-technology macro area B, “LED/OLED Drivers and Electronics,” has much more activity than one would expect given its energy savings potential.  Sub-technology macro area A, “LED Lamps and Chips,” has somewhat more activity than one would expect.  Sub-technology macro area E, “OLED Panels and Lamps”, has appreciably less activity than might be expected were the research activity (as reflected in patent activity) driven exclusively by energy-efficiency motivations.  
Government and industry have different long-term R&D motivations.  There are convincing arguments that the two groups are generally in alignment for basic SSL R&D: in the short-term, product performance is essentially coincident with increasing efficiency.  However, in the long-term government entities are focused on energy efficiency (as a societal good, as a component of overall energy policy) as well as national interest (i.e., securing a place in an attractive industry), whereas commercial entities are naturally motivated by markets and profit.  In fact, the LED market in 2005 was nearly $6B, feeding applications such as signaling, backlights and flashlights.  The OLED market in 2005 was roughly $0.6B, mostly for display panels.
Two approaches to estimating total R&D yield consistent investment levels of ~$1B.  Government-supported R&D is a small fraction of this, perhaps $0.13-$0.17B, or roughly 6-8x smaller, and with only a fraction focused explicitly on general white lighting applications with high energy-savings potential.
By simply taking an R&D rate of 10-15% of sales, we would estimate roughly $1B being spent per year on R&D in the broad area of solid-state lighting technology (almost none of which is focused particularly on general white-lighting applications with high energy-savings potential).
But businesses are able, of course, to invest ahead of sales to secure a profitable future position in a growth industry.  Accordingly, a bottoms-up approach was used for the report “U.S. Competitiveness in Solid-State Lighting: Illuminating a Gathering Storm” prepared by Strategic Perspectives, Inc., in April 2006.  This approach catalogued specific R&D activities by government and industry and yielded a global R&D estimate of ~$0.8B

## Alignment betweenPatent Activity and Energy Savings Potential, Cont.

**Notes:**
Clearly, there’s no a priori reason why patent activity should be aligned with energy savings potential, but it is reasonable to assume that government entities would choose to use their R&D funds as leverage to push an efficiency strategy.
The gaps in patenting activity above/below expected levels given energy efficiency yields suggest two attractive allocation tactics to take advantage of underlying commercial industry motivations:
Essentially, industry has demonstrated by its patenting in the last 20 years that it will pursue research in Macro Area B (LED / OLED Drivers & Electronics) well ahead of energy savings potential – in other words, that there is a significant alternative driver (more than likely, market and profit-potential) that merits the investment.  Government entities therefore could be able to increase their leverage by directing future funds towards under-resourced areas (e.g., OLED Panels, Lamps, OLED Materials, Structures, LED/OLED Light Extraction and Optical Tools) – and allowing industry to carry the R&D burden for other areas.
Conversely, the lack of activity in Macro Area E (OLED Panels and Lamps) suggests an opportunity for government R&D to provide added impetus in an area where past activity has been well in deficit when considering energy savings potential.
It is worth noting that the outliers (Macro Areas E and B) also could be interpreted in opposite directions – that the extent of past activity, insofar as it demonstrates alternative motivations, is an argument for reinforcing these other motivations (essentially, blowing with the wind instead of into it).  But in either determination, the outliers as a class should arguably be treated differently in terms of future funding decisions.
Since funding decisions naturally take place at the local or national level, this raises the question of whether, and how much, individual countries show research patterns with a bias towards factors other than energy efficiency.  The following chart looks at this issue.

## Alignment between Patent Activityand Energy Savings Potential for Top 10 Countries

**Notes:**
We can calculate the percentage deviation from perfect alignment.  To do this, we take the root mean square deviation of the number of patents in each of these macro areas from this line of “perfect alignment,” then divide by the total number of patents.  For the overall patent portfolio, which includes all nations, this percentage deviation turns out to be about 22%.  We can also do the same for individual countries (as represented, given this dataset, by their distribution of USPTO patents).
Here, we plot the percentage deviation for the top ten SSL U.S.-patent-holding countries, dispersed on the horizontal axis by total U.S. patents.  This line indicates the 22% average percentage deviation characteristic of the patent dataset as a whole.  If a country is above this line, then its deviation from alignment between its patent activity and the energy savings potential is greater than the average.  If a country is below this line, then its deviation is less than average.
Variation is significant – almost 2x between the best and worst performer.
The three countries whose patent activity is most aligned with energy savings potential – i.e., those that may be using their leverage most effectively –  seem to be Japan, Germany and Korea.
The three countries that are least aligned are Canada, Netherlands and France.
A variety of factors likely influence the extent to which a country’s patenting activity is shown as aligned with energy-efficiency.  Historical areas of expertise, size of industrial footprint, commercial industry strongholds, research focus of academic programs, the presence of other industries with overlapping R&D thrust areas, etc., may all influence the extent to which a country’s patenting activity is aligned with energy-efficiency.  As such, this chart does not necessarily provide a useful absolute metric of the extent to which an efficiency strategy is being effectively executed by a government entity.  However, it does provide a baseline for future comparisons – in that the ability of a significant investment to influence the degree of alignment over time should eventually be visible in trends for country placement (i.e., movement up or down, left or right).  In the case of DOE’s SSL program, it is still too early to see direct footprints of activity within the patent pool, but in 2-3 years it may be feasible to identify a correlation.

## Caveats and Future Directions

**Break the technology apart into sub-technology areas**
**Develop a lexical signature for these sub-technology areas**
**Identify the footprints of those signatures in a technology activity dataset (e.g., patents)**
**Compare the footprints with a desired footprint**

**Notes:**
Of course, all of these results must be viewed with some caution: these all are preliminary results.  There are significant improvements that could be made at each level of the “technology footprinting” methodology.
First, as we mentioned at the beginning, there are many ways of breaking apart a technology into sub-technology areas, and more thought should go into exactly how to best do that for the particular questions one is interested in answering.
Second, given a set of sub-technology areas, there are many ways of assigning a lexical signature.  Again as mentioned at the beginning, one would like descriptive words or phrases that are unique yet relatively commonly used.  Perhaps one could devise a systematic method of optimizing how this is done.
Third, it is unlikely that a given patent will impact exclusively one sub-technology area.  Hence, assigning partial weights to more than one sub-technology area could improve the fidelity of the results.
And fourth, different applications will emphasize investments in different sub-technology areas.  And activity in a particular sub-technology is a sum over investments from all applications.  Some applications will be of greater importance to the private sector, some to the public sector.  Since private sector investment is typically larger than public sector investment, those sub-technology areas that are emphasized by applications important to the private sector may tend to be better supported, while those that are underemphasized by these applications may tend to be less well supported.  It is in supporting these underemphasized sub-technology areas that national governments can perhaps optimize their impact.  Hence it will be particularly interesting to take a step back and try to understand better the various applications for solid-state lighting, and to tailor the choice of sub-technology areas to all of those applications, including general white lighting.