Conference Paper

NREL/CP-520-45012

February 2009

Performance Limitations of mc-Si 

Solar Cells Caused by Defect 

Clusters

Preprint 

B. Sopori, P. Rupnowski, V. Mehta, V. Budhraja

S. Johnston, N. Call, H. Moutinho, and M. Al-Jassim

National Renewable Energy Laboratory

A. Shaikh

Ferro Electronic Materials

M. Seacrist

MEMC Electronic Materials

D. Carlson

BP Solar

To be presented at Semicon China 2009

Shanghai, China 

March 17–19, 2009
NOTICE

The submitted manuscript has been offered by an employee of the Alliance for Sustainable Energy, LLC 

(ASE), a contractor of the US Government under Contract No. DE-AC36-08-GO28308. Accordingly, the US 

Government and ASE retain a nonexclusive royalty-free license to publish or reproduce the published form of 

this contribution, or allow others to do so, for US Government purposes.

This report was prepared as an account of work sponsored by an agency of the United States government. 

Neither the United States government nor any agency thereof, nor any of their employees, makes any 

warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or 

usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not 

infringe privately owned rights. Reference herein to any specific commercial product, process, or service by 

trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, 

recommendation, or favoring by the United States government or any agency thereof. The views and 

opinions of authors expressed herein do not necessarily state or reflect those of the United States 

government or any agency thereof.

Available electronically at http://www.osti.gov/bridge

Available for a processing fee to U.S. Department of Energy

and its contractors, in paper, from:

U.S. Department of Energy

Office of Scientific and Technical Information 

P.O. Box 62

Oak Ridge, TN 37831-0062

phone: 865.576.8401

fax: 865.576.5728

email: mailto:reports@adonis.osti.gov

Available for sale to the public, in paper, from:

U.S. Department of Commerce

National Technical Information Service

5285 Port Royal Road

Springfield, VA 22161

phone: 800.553.6847

fax: 703.605.6900

email: orders@ntis.fedworld.gov

online ordering: http://www.ntis.gov/ordering.htm

Printed on paper containing at least 50% wastepaper, including 20% postconsumer waste
1 

Performance Limitations of mc-Si Solar Cells Caused by Defect Clusters*

ABSTRACT

Bhushan Sopori,1 P. Rupnowski,1 V. Mehta,1 V. Budhraja,

1 S. Johnston,1 N. Call,1

 

H. Mountinho,1 M. Al-Jassim,

1 Aziz Shaikh,2 M. Seacrist,3

 and D. Carlson4

1

National Renewable Energy Laboratory, 2Ferro Electronic Materials, 3MEMC Electronic 

Materials, 4BP Solar

Multicrystalline silicon wafers used for solar cells exhibit defect clusters—localized crystal 

defects in and near grains of some specific orientations. Defect clusters are also dominant sites 

for impurity precipitation, and they remain ungettered and unpassivated through the solar cell 

processing. This paper describes characteristics of defect clusters, and shows, through theory 

and experiment, that defect clusters typically lower cell efficiency by 3 to 4 absolute percentage 

points. To recover this efficiency loss, it is necessary to getter precipitated impurities.

INTRODUCTION

Multicrystalline silicon (mc-Si) constitutes more that 50% of the total Si for photovoltaic (PV) 

applications and this share is expected to grow rapidly. The techniques for growing mc-Si by 

casting or by shaped crystal growth have been developed in the last 30 years primarily for solar 

cell applications to lower the wafer cost. Multicrystalline Si does not require seeding, and 

furnace designs are simpler that Czochralski (CZ) or float-zone (FZ) methods; therefore, the cost 

of casting and ribbon growth techniques is considerably lower. Also, mc-Si is produced from a 

lower-grade feedstock, consisting primarily of reject and out-of-spec material from the 

microelectronics industry. Consequently, the mc-Si wafers contain high concentrations of 

impurities. The lower material purity does not impact the quality of the ingot to the same degree 

as in CZ and FZ methods. But, because mc-Si material is grown very rapidly, the ingot 

experiences higher thermal stresses, accompanied by high defect densities. Dislocations are the 

primary intragrain defects. The impurities interact with defects during crystal growth, which 

leads to a very strong influence of defects on the cell performance [1]. 

This paper presents theoretical and experimental results of our studies to determine the 

performance limitations set by defect clusters (DCs) in mc-Si solar cells. DCs in mc-Si wafers 

are manifested as spatially localized, large regions of high dislocation density, around grains of 

certain preferred orientations. The presence of DCs has a strong influence on the material 

properties and cell performance. The objective of our comprehensive study on DCs is to 

understand their nature and their influence on cell performance, and to assess the performance 

improvement that can be realized if the influence of DCs can be eliminated. The effect of grain 

orientation on the defect density is also investigated. Finally, we explore possibilities of 

eliminating the formation of defect clusters during crystal growth or treating them during cell 

processing to minimize their electronic influence.

 

*

Employees of the Alliance for Sustainable Energy, LLC, under Contract No. DE-AC36-08G028308 with the US. Dept. of 

Energy have authored this work. The United States Government retains and the publisher, by accepting the article for publication, 

acknowledges that the United States Government retains a non-exclusive, paid-lip, irrevocable, worldwide license to publish or 

reproduce the published form of this work. or allow others to do so, for United States Government purposes.
2 

CHARACTERIZATION OF DEFECT CLUSTERS 

As-grown mc-Si wafers have high concentrations of C and/or O. They also contain transitionmetal impurities (e.g., Fe, Cr) in levels reaching 1014

cm-3, which are detrimental to the minoritycarrier lifetime. Typically, the average minority-carrier lifetime of as-grown material is < 10 μs. 

The average defect density of current mc-Si wafers is about 5x105 cm

-2. But, a unique feature of 

current mc-Si wafers is that they contain “defect clusters”—crystal defects that clump together, 

forming extended defected regions that remain separated from each other. 

A detailed structure of a defect cluster can be delineated after wafer polishing and defect etching 

[2]. Figure 1a is an optical micrograph of a defect-etched, cast mc-Si wafer showing dislocations 

piling up in a defect cluster that extends over several grains. Similar clustering is seen in ribbon 

material. Typically, the fractional area of the wafer covered by defect clusters is about 5%–10% 

for a high-quality material; lower-quality material may have a higher-percentage area covered by 

defect clusters. On a larger scale, clustering of defects can also be observed on defect maps 

generated by the commercial instrument PVSCAN. An example of such a map, acquired for a 

commercial 4.25-in x 4.25-in mc-Si wafer, is shown in Fig. 1b. This map reveals that the 

majority of the wafer has a low (and much of it nearly zero) dislocation density [3]. The average 

value of the dislocation density is about 4 x 105 cm

-2. The presence of defect clusters can be seen 

as light regions in this otherwise very low defect density material. These regions can have defect 

densities as high as 107 cm

-2. 

Defect clustering occurs during crystal growth when local thermal stress exceeds yield stress of 

some preferred grain orientations, causing the stress relief through local generation of defect 

networks. Defect clusters also serve as internal gettering sites for metallic impurities, and they 

often result in impurity precipitation at these sites [4]. Figure 1c depicts a cross-sectional 

transmission electron microscopy (TEM) image of such precipitates in a DC region; other 

researchers also observed similar precipitates. Precipitation of impurities at defect clusters is of 

particular concern, because it is now known that precipitated impurities are difficult to getter by 

the techniques used in the PV industry (namely, P diffusion for junction formation and Al 

Figure 1. (a) Optical micrograph of a DC in a defect-etched wafer, (b) PVSCAN map showing density 

of defects on 4-in. wafer, and (c) TEM image of impurities precipitated in a DC.

a b c

200 Å
3 

alloying for back-contact formation). Hence, defect clusters have an important bearing on the 

development of new impurity-gettering methods that must dissolve the precipitates during 

gettering.

FORMATION OF DEFECTS

In a mc-Si casting or ribbon, the grains with orientations of lower yield stress respond to the 

thermal stress by generating dislocations. As the dislocations are generated, the stress is relieved. 

This allows other grains to escape dislocation generation. To study the correlation between 

crystal orientation and dislocation density, we had to acquire grain-orientation maps. We used a 

laser scanner to map grain orientations (Fig. 2) for wafers originating from various sections of an 

ingot. After calibration, such maps are compared with defect density images. Our initial study 

suggests that dislocations are generated in grains represented by blue and violet orientations [5]. 

ELECTRO-OPTICAL RESPONSE OF A CELL WITH DEFECT CLUSTERS

Modeling 

 

The influence of defect clusters on the electro-optical response of a cell can be evaluated using a 

network model. In this model, we consider a defect cluster as a localized, large defect that 

propagates through the entire cell (crossing both the base and emitter regions of the cell), as 

illustrated in Fig. 3a [6]. Because of very high recombination and large size, one can ignore 

internal carrier transport and band bending associated with each defect cluster. The defected 

region acts as a “poor” device in the spatial distribution of the total cell. 

The modeling requires two steps. First, each device is represented in terms of the recombination 

properties associated with its defect density, which yields values of photo-generated current 

density (Jph), minority-carrier lifetime (τ), and dark saturation-current components J01 and J02,

Grain orientations 

maps of 15.6 X 

15.6 cm2 wafers 

with different cell 

performance

Grain orientations 

maps of 15.6 X 

15.6 cm2 wafers 

with different cell 

performance

Figure 2. Orientation distribution maps of 6” wafers taken from 

bottom (left image) and top (right image) section of an ingot. 

Each color represents a specific orientation.
4 

corresponding to the bulk and the junction recombination, respectively. Next, the diode array is 

interconnected using resistive components corresponding to the sheet resistivity of the junction 

and the metallization pattern. The network is solved to yield the terminal characteristics of the 

device, as well as distribution of local currents and voltages for any given terminal voltage. 

In the network model for defect clusters, we basically have two kinds of diodes: a defect-free 

diode and a defected diode. The characteristics of each diode can be expressed in terms of the

photocurrent, Jph, and two exponential components of the dark current, Jdark, in a standard form as

[7,8]: 

Jdark i(V) = J01i.exp{(-eV/kT) - 1} + J02i.{exp (-eV/2kT) - 1}, (1) 

where i denotes a diode index and J01.and J02 represent the saturation currents. The total current

through a diode, Ji, is then given by: 

Ji = Jph i - Jdark i(V) . (2) 

The values of Jph i, J01i, and J02i can be estimated from the experimental measurements. For 

example, we select one cell and make an estimate of Jph values for defect-free and defected cells 

based on laser-beam-induced current (LBIC), or long wavelength, responses and cell currentvoltage (I-V) plots. However, J01 and J02 cannot be determined from the cell itself. We have 

built a library of J01 and J02 values for a variety of different materials and for different defect 

densities, using a diode array technique described in Ref. [9]. Edge-passivated, mesa diode 

arrays are fabricated on wafers and their electrical characteristics are probed. The device 

characteristics and their defect data are compiled and used as input in our model. These data 

result in excellent agreement between calculated and actual terminal characteristics of the largearea cell (as seen in next section). It should be pointed out that the network model we have 

developed assumes no internal carrier transport—the communication between the devices occurs 

via a highly conducting emitter region and the bus bar. 

Solar cells with measured dislocation distributions were simulated using our network model. 

Typically, 3000 individual diodes were used to represent a single large-area solar cell. Figures 4 

Figure 3. (a) Schematic of a defect cluster, and (b) a network model of a solar cell showing voltage and 

current sources corresponding to dark (with subscript d) and illuminated (with subscript L) conditions, 

and the resistive components due to the sheet rho of the junction.

a

N

P

Defect

cluster

b
5 

and 5 show simulation results that were performed for a material provided by a commercial 

vender. Calculated I-V characterisitics of two defected cells and one without defects are 

compared in Fig. 4. As seen, defect clusters have a dominant effect in degrading the voltagerelated parameters.

In Fig. 5, open-circuit voltage (Voc) and short-circuit current density (Jsc) are presented as a 

function of the relative area covered by defect clusters. For comparison, measured values of Voc

and Jsc are also included. The parameters of an ideal solar cell, which does not exhibit any active 

defect clusters, were extrapolated from the obtained data points of Fig. 5. We found that the 

extrapolated ultimate values for an ideal cell were Voc = 615–620 mV and Jsc = 31 mA/cm2. It is 

important to point out that these values depend strongly on the initial material properties and cell 

processing. 

Our network model provided detailed information on the spatial distribution of voltage and 

current over the entire cell for a given terminal voltage. Figure 6 depicts results of our 

simulation for a 4-in. x 4-in. cell whose LBIC map (at λ = 0.98 μm) is shown in Fig. 6a 

(identifying defect clusters). Figures 6b, 6c, 6d, and 6e present spatial distribution of the 

direction-of-current flow at forward terminal voltages of 0.500, 0.505, 0.515, and 0.525 V,

respectively. The green color indicates a forward current and red color indicated a reversal in the 

current flow. Thus, defect clusters can cause a local current to flow in the opposite direction, 

causing net internal energy dissipation at the DC sites. 

0.04 

0.03

0.02 

0.01

0% no defects

15%

6%

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Volts

I [A/cm

2

]

Figure 4. A comparison of calculated I-V characteristics of three cells

with 0%, 6%, and 15% of area covered by defects.
6 

 

Experimental studies

To measure the effect of defect clusters on cell response, the following experimental procedure 

was used. Sequential mc-Si wafers were obtained from different vendors, and alternate wafers 

were processed into cells. The unprocessed wafers were used to obtain dislocation/grain 

boundary maps by PVSCAN, and grain orientation maps. This information was used to 

determine average area coverage by DCs and to establish a relationship between DC locations 

and grain orientations. The processed solar cells were characterized by dark and illuminated I-V 

plots, and by photoresponse mapping. These results confiremd that defect clusters can produce 

shunts in the device. To further investigate shunting mechanisms, we performed thermal and 

electroluminescent imaging of the cells and compared them with defect and LBIC maps. Some 

Figure 5. A comparison of theoretical Voc and Jsc and 

experimental data on 134-cm2 cells. 

Voc

Jsc

Area covered by precipitate-containing defects

Figure 6. (a) LBIC map (at λ = 0.98 μm) of a 4-in. cell, showing the bulk response of the map 

and the presence of defect clusters. The main defect clusters are labeled. (b–e) Spatial 

distribution of the direction of current flow at various forward terminal voltages. Green color 

indicates a forward current and red color indicates a reversal in the current flow.

a c d e

b

b
7 

samples were used to perform cross-sectional analyses by TEM, atomic force microscopy (AFM), 

and capacitive atomic force microscopy (CFM). 

A comparison of two 6-in. cells labeled A and B is presented in Figs. 7 and 8. These two cells 

were chosen because they belong to two different efficiency categories. The efficiency of cells 

A and B are 14.3% and 15.7%, respectively. Figure 7 includes light and dark I-V response, basic 

cell parameters, LBIC maps for wavelength of 980 nm, as well as thermal and 

electroluminescent images. It can be observed that all three cell parameters—Voc, Jsc, and fill 

factor (FF)—are lower in the case of cell A. Further investigation of LBIC maps clearly 

revealed the structural difference between the cells. Cell B yielded a very uniform response over 

the entire area, with only a few spots with active defects. Contrary to cell B, cell A contains 

extensive active defect clusters that reveal themselves as regions of lower response. In general, 

thermal images show shunting areas where the energy radiates outward in the form of heat. For 

cell A, much heat is generated in various areas of the cell. The locations of these hot spots 

overlap with areas of low LBIC response. Therefore, it is clear that active defect clusters are 

responsible for poor performance of this cell. For higher-efficiency cell B, there are much fewer 

hot spots. Comparing the figures, it can also be observed that the hot spots and active defect 

clusters are not coincident. This means that some other mechanisms dominate in shunting 

generation in cell B. 

Electroluminescent maps in Fig. 7 clearly revealed the material’s nonuniformities. The location 

and size of active defect clusters can easily be determined. A very good correlation between 

LBIC and electroluminescent maps was found for cells with both good and bad performance. 

Another useful and complementary approach to investigate the influence of DCs is to examine 

the electronic characteristics of the entire cell by dissecting the dark and illuminated I-V plots. 

Here, we show some results of deriving important parameters that characterize the behavior of a 

cell by fitting the experimentally measured dark I-V plots with the theoretical two-diode model 

(i.e., applying Eq.[1] to the entire cell). It is important to recognize that we are obtaining lumped 

parameters of a distributed device. This procedure yields J01, J02, series resistance, and shunt 

resistance of each device. The quality of the fit can be determined by regenerating a theoretical 

I-V plot and comparing it with the experimental plot. Figures 8a and 8b show the values of the 

parameter values determined by this procedure for two cells described in Fig. 7. Figure 8 also 

shows that the theoretical and experimental I-V plots have excellent agreement. One can see that 

the higher-efficiency device, which contains a lower density of DCs, has lower values of J01 and 

J02, a lower series resistance, and higher shunt resistance.

CONCLUSIONS

This paper presents a combination of numerical and experimental methods that were used to 

characterize defect clusters in mc-Si solar cells. In particular, we described a defect-generation 

mechanism, grain-orientation effect, interaction of defects with impurities, effect of defect 

distribution on cell performance, and shunting mechanisms associated with defect clusters.
8 

Cell A (Lower efficiency) 

Voc= 590.1 mV, Jsc = 32.54 mA/cm2

FF = 73.9 %, Efficiency = 14.3 %

Cell B (Higher efficiency) 

Voc = 619mV, Jsc = 33.83 mA/cm2

FF= 74.6, Efficiency = 15.7 %

I-V

response 

LBIC

map

Thermal

image

Electroluminescent

image

Figure 7. I-V response, 980-nm LBIC, thermal, and electroluminescent image of 6-in. x 6-in. cells. Two cells of lower

efficiency (left column) and higher efficiency (right column) are compared.
9 

The dependence of dislocation density on grain orientation is very interesting and lends itself to a 

well-known observation: cell performance depends on the location of the wafer within the ingot. 

A comparison of the orientation and dislocation maps shows that dislocation distribution mimics 

the orientation distribution. This result has very important implications on potential methods to 

minimize the formation of dislocation clusters. 

Experimental and numerical results both show that defect clusters are regions of low minoritycarrier diffusion length and local shunts that cause dissipation of energy internally within the cell. 

There is good agreement between theoretically predicted parameters of cells with defects and 

corresponding experimental data. We also found that the best solar cells from commercial 

vendors performed nearly as well as predicted by the theoretical model that does not have any 

active defects. The best cell performance was limited by the impurities in the material.

The salient results of our analysis are the following: (i) Defect clusters are the primary sites of 

impurity precipitation, and hence, are not gettered by conventional gettering treatments of P 

diffusion and Al alloying. (ii) Defect clusters act as shunts, creating “internal sinks” that

dissipate power within the cell. (iii) The loss depends on several factors—the nature of the 

impurity precipitates, distribution and total area of defects compared to the cell area, quality of 

the base material (the regions with no defects, in which cell performance is limited by the 

dissolved impurities only), and cell processing technology. (vi) In a typical cell, the defect 

clusters produce an efficiency loss of 3 to 4 absolute percentage points in efficiency. 

Figure 8. Illustration of fitting measured I-V characteristics to determine J01, J02, Rs (series 

resistance), and Rp (shunt resistance).
10 

To recover the efficiency loss caused by cluster defects, it is necessary to either eliminate them 

during crystal growth or getter precipitated impurities at DC sites. The information gathered on 

defect clusters suggests potential techniques that can minimize defect cluster formation and/or 

dissolve precipitated impurities at temperatures and times that are compatible with solar cell 

fabrication; these techniques offer the potential to raise efficiency of mc-Si solar cells to >20%.

An intuitive approach to mitigating the influence of defect clusters would be to dissolve the 

precipitates by a high-temperature treatment prior to or during gettering. A new approach, 

recently developed at the National Renewable Energy Laboratory, dissolves impurity precipitates 

by using vacancy injection to lower the temperature needed for precipitate dissolution.

REFERENCES

1. B.L. Sopori, Proc. ICDS-19, Trans Tech Pub., edited by G. Davies and M.H. Nazare, 527 

(1997). 

2. B.L. Sopori, J. Electrochem. Soc. 131, 667 (1984). 

3. PVSCAN uses optical scattering from a defect-etched wafer to statistically count defects. It 

is also fitted with capabilities to make LBIC and reflectance measurements at 0.63 and 0.98 

μm. It is available from GT Solar Technologies, Nashua, NH 03054. Also see B.L. Sopori, 

U.S. Patent 5,581,346. 

4. T. Buonassisi, O.F. Vyvenko, A.A. Istratov, E.R. Weber, G. Hahn, D. Sontag, J.P. 

Rakotoniaina, O. Breitenstein, J. Isenberg, and R. Schindler, J. Appl. Phys. 95, 1556 (2004). 

5. B. Sopori, P. Rupnowski, D. Balzar, P. Sheldon, “Dislocation Generation in Si: A ThermoMechanical Model Based on Measurable Parameters”, Conference Record of the 2006 IEEE 

4th World Conference on Photovoltaic Energy Conversion, May 7-12, 2006, 936 - 939 

6. B.L. Sopori and R.A. Murphy, Proceedings of 12th European Photovoltaic Solar Energy 

Conference, April 1994, Amsterdam, The Netherlands, 1797. 

7. J.G. Fossum and F.A. Lindholm., IEEE Trans. ED-27 692(1980). 

8. B.L. Sopori, R.A. Murphy, and C. Marshall, Proceedings of the 23rd IEEE Photovoltaic 

Specialists Conference, Louisville, Kentucky, May 10–14, 1993, 190. 

9. B.L. Sopori, Appl. Phys. Lett. 52, 1718 (1988). 
F1147-E(10/2008) 

REPORT DOCUMENTATION PAGE Form Approved

OMB No. 0704-0188

The public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, 

gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this 

collection of information, including suggestions for reducing the burden, to Department of Defense, Executive Services and Communications Directorate (0704-0188). Respondents 

should be aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a 

currently valid OMB control number.

PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ORGANIZATION.

1. REPORT DATE (DD-MM-YYYY)

February 2009

2. REPORT TYPE

Conference Paper

3. DATES COVERED (From - To)

17-19 March 2009

4. TITLE AND SUBTITLE

Performance Limitations of mc-Si Solar Cells Caused by Defect 

Clusters: Preprint

5a. CONTRACT NUMBER

DE-AC36-08-GO28308

5b. GRANT NUMBER

5c. PROGRAM ELEMENT NUMBER

6. AUTHOR(S)

B. Sopori. P. Rupnowski, V. Mehta, V. Budhraja, S. Johnston, 

N. Call, H. Moutinho, M. Al-Jassim, A. Shaikh, M. Seacrist, and

D. Carlson

5d. PROJECT NUMBER

NREL/CP-520-45012

5e. TASK NUMBER

PVA93110

5f. WORK UNIT NUMBER

7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES)

National Renewable Energy Laboratory

1617 Cole Blvd.

Golden, CO 80401-3393

8. PERFORMING ORGANIZATION

REPORT NUMBER

NREL/CP-520-45012

9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSOR/MONITOR'S ACRONYM(S)

NREL

11. SPONSORING/MONITORING

AGENCY REPORT NUMBER

12. DISTRIBUTION AVAILABILITY STATEMENT

National Technical Information Service

U.S. Department of Commerce

5285 Port Royal Road

Springfield, VA 22161

13. SUPPLEMENTARY NOTES

14. ABSTRACT (Maximum 200 Words)

Multicrystalline silicon wafers used for solar cells exhibit defect clusters—localized crystal defects in and near grains 

of some specific orientations. Defect clusters are also dominant sites for impurity precipitation, and they remain 

ungettered and unpassivated through the solar cell processing. This paper describes characteristics of defect 

clusters, and shows, through theory and experiment, that defect clusters typically lower cell efficiency by 3 to 4 

absolute percentage points. To recover this efficiency loss, it is necessary to getter precipitated impurities.

15. SUBJECT TERMS

PV; multicrystalline silicon; solar cells; defect clusters; photogenerated current density; minority-carrier lifetime; dark 

saturation current; grain orientation; 

16. SECURITY CLASSIFICATION OF: 17. LIMITATION 

OF ABSTRACT

UL

18. NUMBER 

OF PAGES

19a. NAME OF RESPONSIBLE PERSON

a. REPORT

Unclassified

b. ABSTRACT

Unclassified

c. THIS PAGE

Unclassified 19b. TELEPHONE NUMBER (Include area code)

Standard Form 298 (Rev. 8/98)

Prescribed by ANSI Std. Z39.18