Efficiency of Dye Sensitized Solar Cells using Titanium Dioxide

This study investigates the efficiency of dye sensitized solar cells using titanium dioxide film. It aims to determine the effect of influence of titanium dioxide on efficiency of dye-sensitized solar cells. The research methodology includes data collection through primary and secondary sources, an experiment, and data analysis using statistical software. The results show the absorbance spectrum of the dye extract, photoelectrochemical performance of the solar cells, and the influence of electrode thickness on cell efficiency.

12/29/2018
EFFICIENCY OF DYE SENSITIZED SOLAR CELLS USING TITANIUM DIOXIDE FILM

Table of Contents
Introduction.................................................................................................................................................2
Aim of the study......................................................................................................................................3
Research methodology................................................................................................................................3
Data collection.........................................................................................................................................3
Primary data sources...........................................................................................................................3
Secondary data sources.......................................................................................................................4
Experiment..............................................................................................................................................4
Data analysis............................................................................................................................................5
Results.........................................................................................................................................................5
Descriptive statistics................................................................................................................................5
Inferential statistics...............................................................................................................................10
Correlation.........................................................................................................................................10
Regression analysis............................................................................................................................12
Discussion..................................................................................................................................................14
Conclusion.................................................................................................................................................16
References.................................................................................................................................................16

Introduction
Energy is an integral aspect of daily life, and the demand for it is expectantly high. Currently,
over 75% of energy consumption is attributed to non-renewable sources such as oil, coal and
natural gas (Carr, 2008). It is anticipated that the non-renewable sources won’t last for more than
200 years. In contrast to these sources of energy, renewable sources are thought to naturally
replenish and do not pollute the environment (Dogan, 2016). As blood is to body power is to
economy of any nation so without it economy will tremble and it will be difficult to run it.
Everywhere throughout the world energy is one of the main issues what's more, every nation is
searching for energy assets as its demand is expanding pointedly. Non-sustainable power sources
are either excessively costly or harming the earth and furthermore they are in the end going to
end in not so distant future. That is the reason the world is moving towards sustainable power
sources which are renewed in a moderately little timeframe.
Due to natural resource depletion and environmental demands, the world has moved to
renewable energy sources. Solar energy has emerged as one of the preferred options in solving
world energy crisis. In spite of the fact that hydroelectric is extremely modest sustainable power
source, however, it isn't accessible to all spots on the planet while on the other hand sunlight
based can possibly assume control over the entire power generation. From time immemorial,
solar energy has been a source of light and heat. In the present-day, solar energy is being used to
produce electricity for domestic and industrial use.
Solar energy harvesting can be done using several technologies (Salim, 2014). Sunlight based
cells are comprised of semiconducting materials, for example, silicon, which are doped with
various impurities. This produces unequal dissemination of free electrons (n-type) on one side of
intersection and abundance of openings (p-type) on opposite side of intersection. Sun based light

has photons which hit the sunlight based board and energize the inexactly bound electrons which
are intended to move just one way in sun based cells and along these lines electron-opening sets
are made in individual intersections and power is acquired in outer circuit (O.V., 2010). As a
result of the environmental demands, there has been a considerable decline in the use of silicon-
based solar cells. Whatever the size is, a typical solar cell produces 0.5-0.6-volt DC under no
load and open circuit condition. The current and voltage (power) ratting of a PV cell mainly
depends on its efficiency, size (surface area) and is proportional to the intensity of light striking
the surface of cell.
Dye-sensitized solar cells are among the options that have emerged to replace silicon-based solar
cells for harvesting solar energy (Pan, 2008). These cells have been largely used due to their
flexibility, low-cost, production ease, environmental friendliness and high efficiency in energy
conversion. The efficiency of the solar cells used in a photovoltaic system, in combination with
latitude and climate, determines the annual energy output of the system (Ito, 2012). Major
improvements such as the introduction of dyes, electrolytes have improved the efficiency of
these types of solar cells. At the current, they are the most efficient solar energy technologies
available (Li, 2011).
For purposes of this research we aim at investigating the efficiency of dye sensitized solar cells
using titanium dioxide film. Dye sensitized solar cells convert solar energy into electricity
consisting of conductive cells with dye and electrolyte sandwiched in between. Dye is absorbed
on the titanium dioxide as it absorbs sunlight. The low cost and efficiency of dye-sensitized solar
cells has made these types of cells a center of attention and worldwide research.

Aim of the study
The aim of the study was to investigate and determine the effect of influence of titanium dioxide
on efficiency of dye-sensitized solar cells.
Schematic diagram of the dye-sensitized solar cell
Research methodology
This section explains the steps that were taken towards collection and analysis of statistical data.
Data collection
Data was collected using both primary and secondary methods.
Primary data sources
For purposes of this research, primary data was collected form results of the experiment. The
data that was collected investigated the efficiency of dye sensitized solar cells.

The parameters that were measured were the short circuit current, the voltage for open circuit,
the cell power input, the maximum obtained current, the maximum output and absorbance
spectrum of the flower extract dye.
These parameters were used for calculating the fill factor and efficiency of the dye sensitized
solar cell. The parameters were observed over 10 experimental periods.
Secondary data sources
Secondary data was collected from database sources depicting energy trends over the years.
Secondary data will be accessed through the website https://yearbook.enerdata.net/.
Experiment
An experiment was carried out to investigate the efficiency of dye sensitized solar cells using
titanium dioxide film.
In order to assess the efficiency of dye sensitized solar cells using titanium dioxide, we conduct
an experiment for making a comparison between two dye sensitized solar cells using zinc oxide
and titanium dioxide.
The study used flower extracts as natural organic dye for the dye sensitized solar cell. Ethanol
was used to obtain dye extracts from the flowers. Titanium dioxide was used as the photo
electrode. The electrode was synthesized using techniques of solution extraction and was
deposited on the FTO glass substrate forming a thin layer of titanium oxide film.
The TiO2 film underwent high temperature (about 460 °C) for about 40 minutes to enhance film
strength and compactness. We studied the titanium dioxide infused with electrolyte, under light
and in a dark room for its conductivity. The conductivity of light intensity, wave length and
voltage were observed.

The experiment steps were repeated severally using using titanium dioxide films of different
thicknesses.
Fill factor of the encapsulated dye sensitized solar cell and the energy conversion efficiency was
calculated as i8n the below formulae;
FF= Imax∗Vmax
Isc∗Voc = Pmax
Pin
¿ FF∗Isc∗Voc
Pin
Where FF is the Fill factor, Isc is the short circuit current, Voc is the voltage for open circuit, Pin
is the cell power input Imax is the maximum current obtained and Pmax is the maximum power
output observed.
Data analysis
Data was coded and analyzed using the Statistical Software for Statistics (SPSS).
Results
Descriptive statistics
Descriptive statistics analysis was carried out to provide a description of the data sets that were
obtained during the study.
Absorbance of flower extract dye on titanium dioxide.
The following data were observed from the experiment.
Wavelength (nm) Absorbance (a.u)
200 0.01
240 0.05
250 0.03

300 0.1
320 0.2
350 0.28
400 0.34
420 0.28
500 0.07
520 0.03
The variables wavelength and absorbance exhibit a positive upward association up to 400 nm.
Beyond 400 nm, a negative downward association is exhibited.

The results depict that the absorption spectra of the dye extract were within the wavelength of
300 to 400 nm. The maximum absorption value was observed to be at 400 nm.
Results have shown that the dye absorbs light best at about 400 nm while the titanium dioxide
film best absorbs light within the range 300 to 400 nm.
Photoelectrochemical performance of dye-sensitized solar cell rom flower extracts
The below table depicts the photo-electrochemical performance of de-sensitized solar cells
(DSSCs) using flower extracts as dye sensitizer. The performance was measured by current-
voltage curves under solar irradiation with halogen lamb of 75 mW/cm2.
Voltage (volts) Current (MA)
0 15
0.05 14
0.1 11
0.15 9
0.23 7
0.28 6
0.35 5
0.42 4
0.47 2
0.5 0

The below table presents descriptive statistics for the two variables; voltage and current. The
mean voltage is for the experiment was found to be 0.2550 and the mean current was found to be
7.30.
Statistics
Voltage (volts) Current (MA)
N Valid 10 10
Missing 0 0
Mean .2550 7.30
Median .2550 6.50
Mode .00a 0a
Std. Deviation .17822 4.945
Minimum .00 0
Maximum .50 15
a. Multiple modes exist. The smallest value is shown
Photoelectrochemical performance of dye-sensitized solar cell rom flower extracts line graph

Voltage at maximum power output was found to be 15 with a corresponding open circuit voltage
of 0. Short circuit current was found to be about 0.42 with corresponding maximum current
obtained to be about 4.
The curve shows that voltage and current are inversely associated. There is an inverse
proportionality between voltage and current.
Influence of thickness of electrode on cell efficiency
Thickness (μm) Voc (V) Isc (mA/cm2) FF (%) η(%)
6.3 0.63 3.33 0.73 2.33
5.9 0.65 3.21 0.63 2.25
5.2 0.68 2.97 0.59 2.22
4.4 0.71 2.88 0.61 1.90
4.2 0.72 2.62 0.63 1.72
3.8 0.76 2.45 0.67 1.56
2.9 0.75 2.30 0.71 1.32
1.0 0.73 1.92 0.68 1.17
0.7 0.79 1.34 0.72 0.88
The descriptive statistics for the variables in the above table are presented in the below table;
Descriptive Statistics
N Minimum Maximum Mean Std. Deviation
Thickness (μm) 9 .7 6.3 3.822 1.9810
Voc (V) 9 .63 .79 .7133 .05220

Isc (mA/cm2) 9 1.34 3.33 2.5578 .63906
FF (%) 9 .59 .73 .6633 .05074
η(%) 9 .88 2.33 1.7056 .51566
Valid N (listwise) 9
The means for the variables were found to be 3.82, 0.71, 2.56, 0.66 and 1.71 for thickness, Voc,
Isc, FF and efficiency respectively.
Inferential statistics
Correlation and regression analysis were performed to assess the association between variables
of the study.
Correlation
Correlation analysis refers to a statistical tool that determines association between variables
involved in a study.
Results of correlation analysis performed are as shown below;
Correlations
Thickness (μm) Voc (V) Isc (mA/cm2) FF (%) η(%)
Thickness (μm) Pearson Correlation 1 -.852** .976** -.393 .973**
Sig. (2-tailed) .004 .000 .296 .000
N 9 9 9 9 9
Voc (V) Pearson Correlation -.852** 1 -.894** .264 -.917**
Sig. (2-tailed) .004 .001 .492 .001
N 9 9 9 9 9
Isc (mA/cm2) Pearson Correlation .976** -.894** 1 -.432 .977**
Sig. (2-tailed) .000 .001 .245 .000
N 9 9 9 9 9
FF (%) Pearson Correlation -.393 .264 -.432 1 -.477
Sig. (2-tailed) .296 .492 .245 .195
N 9 9 9 9 9

η(%) Pearson Correlation .973** -.917** .977** -.477 1
Sig. (2-tailed) .000 .001 .000 .195
N 9 9 9 9 9
**. Correlation is significant at the 0.01 level (2-tailed).
Association between fill factor and other variables
Fill factor was not found to be significantly statistically associated with other variables as the p-
values exceeded 0.05 thereby we reject any test of correlation between FF and the independent
variables.
Association between efficiency and other variables
Efficiency was found to be significantly statistically associated with the independent variables as
the p-values were less than 0.05. Efficiency was found to be positively and strongly associated
with thickness and Isc. However, there was found a negative association between Isc and cell
efficiency.
Regression analysis
Regression analysis was used to assess the impact that the independent variables had on factor
fill and efficiency.
Factor fill
Model Summary
Model R R Square
Adjusted R
Square
Std. Error of the
Estimate
1 .548a .301 -.119 .05367

a. Predictors: (Constant), Isc (mA/cm2), Voc (V), Thickness (μm)
ANOVAa
Model Sum of Squares df Mean Square F Sig.
1 Regression .006 3 .002 .717 .583b
Residual .014 5 .003
Total .021 8
a. Dependent Variable: FF (%)
b. Predictors: (Constant), Isc (mA/cm2), Voc (V), Thickness (μm)
Coefficientsa
Model
Unstandardized Coefficients
Standardized
Coefficients
t Sig.B Std. Error Beta
1 (Constant) 1.463 .808 1.810 .130
Voc (V) -.686 .830 -.705 -.826 .446
Thickness (μm) .024 .045 .946 .534 .616
Isc (mA/cm2) -.158 .164 -1.987 -.960 .381
a. Dependent Variable: FF (%)
All coefficients for both the ANOVA and regression models had p-values greater than 0.05
implying that it would not be statistically significant to regress Factor fill on Voc, thickness and
Isc.
Efficiency
Model Summary
Model R R Square
Adjusted R
Square
Std. Error of the
Estimate
1 .996a .992 .983 .06627
a. Predictors: (Constant), Isc (mA/cm2), FF (%), Voc (V), Thickness
(μm)

R square equals 0.992 implying that the dependent variables explain about 99.2% of the
dependent variable (efficiency).
The p-vale for the ANOVA model is less than 0.05 implying that it would be statistically
significant to fit an ANOVA model for predicting efficiency.
ANOVAa
Model Sum of Squares df Mean Square F Sig.
1 Regression 2.110 4 .527 120.076 .000b
Residual .018 4 .004
Total 2.127 8
a. Dependent Variable: η(%)
b. Predictors: (Constant), Isc (mA/cm2), FF (%), Voc (V), Thickness (μm)
Coefficientsa
Model
Unstandardized Coefficients
Standardized
Coefficients
t Sig.B Std. Error Beta
1 (Constant) 4.866 1.284 3.790 .019
Voc (V) -3.724 1.093 -.377 -3.408 .027
Thickness (μm) .177 .058 .680 3.073 .037
FF (%) -1.506 .552 -.148 -2.727 .053
Isc (mA/cm2) -.071 .221 -.088 -.322 .763
a. Dependent Variable: η(%)
The constant, Voc and thickness coefficients were found to be statistically significant in the
regression model as their p-vales were less than 0.05. However, factor fill and Isc were not found
to be statistically significant in the model as their p-values were greater than 0.05. We therefore
fail to include the two variables in the regression model.
The regression model that shall be fit for this study for predicting efficiency is;
Efficiency=4.866−3.724∗Voc +0.177∗thickness+ error term

The regression model implies that Voc explains about -3.724 of efficiency. This means that an
increase by 1 unit in Voc results to a corresponding decrease by 3.724 units in efficiency. 0.177
of efficiency is explained by thickness implying that an increase by 1 unit in thickness results to
a 0.177 units increase in efficiency.
Discussion
Based on the obtained variable results, we found a cell performance with energy conversion
efficiency of about 1.71% on average. The low efficiency level could be as a result of the solvent
used during dye extraction. Previous studies have found similar results to this. (Zhou, 2015)
found out that the energy conversion efficiency was around 0.88 per cent and water was utilized
as the extracting solvent. Findings by (Al-Ghamdi, 2014) showed an energy conversion
efficiency of 0.62 % and water was used as the extracting solvent. Taking higher safety on cell
preparation and assessment of methods and experimental materials used could increase
efficiency.
The results have also depicted that cell efficiency is affected by the factors; thickness of
electrode film and the open circuit voltage.
A cell electrode sheet or film with high resistance due to small thickness off the sheet resistance
depicts negative impacts on the performance of the cell. However, as resistance is decreased by
increasing the electrode film thickness, there tends to be experienced increased cell efficiency
(performance). This aspect off thickness is such that current flow in the electrode is lateral
parallel to the surface of the layer. Light would be more absorbed on the electrode with greater
thickness compared to the electrode with thinner thickness. For the case of this study, thickness

of the titanium dioxide electrode explained about 0.177 of the cell performance. An increase by
one unit in electrode thickness would result to a corresponding 0.177 units increase in the cell
efficiency. A study conducted by (Xiao, 2015) showed that the regression coefficient of
electrode thickness on cell efficiency was 0.234 implying a positive effect of electrode thickness
on cell performance.
Findings of the regression analysis have shown that open circuit voltage has a negative impact on
energy conversion efficiency. The higher the open circuit current, the greater the negative effect
on cell efficiency and the lower the open circuit current, the lower the negative effect on cell
efficiency. Similar findings were found by (Masanobu Yoshida, 2011). He argued that increasing
open circuit voltage would result to decreased cell efficiency. Masanobu found out that
increasing open circuit voltage b one percentage point would decrease cell conversion efficiency
by about 0.3 percentage points. However, contradicting findings have been found by
(S.NarayananM.A.Green, 2016). He carried out an experimentation with aluminium treatments
for silicon cells. He found out that processing silicon solar cells under higher open circuit voltage
resulted to increased photo generated carrier collection for medium resistivity substrates, and
improved energy conversion efficiency for both high and medium resistivity.
Conclusion
Efficiency of sun powered cell is enormously influenced by the measure of sun oriented
irradiance. It is a standout amongst the most powerful factors which change the sun based exhibit
execution. It is measure of amount of solar radiation from the sun striking on particular surface.
In the production of dye-sensitized solar cells each stage of the manufacturing process has a
significant impact on final product outcome and quality. Among many reasons for such
occurrence are the thickness of the electrode and screen printing method.

Dye-sensitized solar cells using titanium dioxide was successfully fabricated. An energy
conversion efficiency of about 0.24% was observed for the flower extract cell. The flower dye
absorbs observable light in the range of 300nm to 400nm with maximum peak absorbance at 400
nm. The tests carried out in a dark room under a lamp emitting all wavelengths in the visible
spectrum were not found to provide consistent data due to substantial heating of the cell. The
tests carried out in natural illumination exhibited stable voltage at much higher level.
Efficiency of the solar panel can further be enhanced by stopping cooling of the solar panel in
the early and last hours of the day. Efficiency of solar panel can also be increased by increasing
solar irradiation on solar panel.
References
Al-Ghamdi, A. A.-T. (2014). Improved solar efficiency by introducing graphene oxide in purple cabbage
dye sensitized TiO2 based solar cell. Solid State Communications, 183, 4.
Carr, J. A. (2008). A Survey of Systems to Integrate Distributed Energy Resources and Energy Storage on
the Utility Grid. 14.
Dogan, E. S. (2016). The influence of real output, renewable and non-renewable energy, trade and
financial development on carbon emissions in the top renewable energy countries. Renewable
and Sustainable Energy Reviews, 12.
Ito, S. O. (2012). Near-infrared DyeSensitization in Bulk Heterojunction Polymer Solar Cells. 8.
Li, H. J. (2011). Phosphonium iodide as a donor liquid electrolyte for dyesensitized solar cells. Journal of
the Serbian Chemical Society, 76, 6.

Masanobu Yoshida, T. U. (2011). Measures to reduce surge voltages on low-voltage circuits in
substations. 8.
O.V., M. (2010). ANALYSIS OF THE PROSPECTS OF SOLAR ENERGY AND OTHER ALTERNATIVE ENERGY
SOURCES IN UKRAINE. 14.
Pan, A. L. (2008). New Materials and Nanostructured Devices for High Efficiency - Semiconductor Alloy
Nanowires with Spatially Graded Compositions for Full-Spectrum Solar Cell . 3.
S.NarayananM.A.Green. (2016). Improvement in the open-circuit voltage and efficiency of silicon solar
cells by rear aluminium treatment. 26, 31.
Salim, R. A. (2014). Renewable and non-renewable energy consumption and economic activities: Further
evidence from OECD countries. Energy Economics, 11.
Xiao, Y. H. (2015). Efficient titanium foil based perovskite solar cell: Using titanium dioxide nanowire
arrays anode and transparent poly(3,4-ethylenedioxythiophene) electrode. 24.
Zhou, L. L. (2015). Comparison in net solar efficiency between the use of concentrating and non-
concentrating solar collectors in solar aided power generation systems. Applied Thermal
Engineering, 75, 6.
Appendix
Primary data for the experiment
Wavelengt
h (nm)
Absorbanc
e (a.u)
Voltag
e
(volts)
Curren
t (MA)
Thicknes
s (μm)
Voc
(V)
Isc
(mA/cm2
)
FF (%) η(%)
200 0.01 0 15 6.3 0.63 3.33 0.73 2.33

240 0.05 0.05 14 5.9 0.65 3.21 0.63 2.25
250 0.03 0.1 11 5.2 0.68 2.97 0.59 2.22
300 0.1 0.15 9 4.4 0.71 2.88 0.61 1.9
320 0.2 0.23 7 4.2 0.72 2.62 0.63 1.72
350 0.28 0.28 6 3.8 0.76 2.45 0.67 1.56
400 0.34 0.35 5 2.9 0.75 2.3 0.71 1.32
420 0.28 0.42 4 1 0.73 1.92 0.68 1.17
500 0.07 0.47 2 0.7 0.79 1.34 0.72 0.88
Secondary data
1
9
9
8
1
9
9
9
2
0
0
0
2
0
0
1
2
0
0
2
2
0
0
3
2
0
0
4
2
0
0
5
2
0
0
6
2
0
0
7
2
0
0
8
2
0
0
9
2
0
1
0
2
0
1
1
2
0
1
2
2
0
1
3
2
0
1
4
2
0
1
5
2
0
1
6
2
0
1
7
2
0
1
6
-
2
0
1
7
(
%
)
20
00
-
20
17
(%
/y
ea
r)
Wo
rld
9
7
1
7
9
7
2
6
1
0
0
1
6
1
0
1
7
7
1
0
2
5
3
1
0
6
7
0
1
1
1
8
2
1
1
5
4
2
1
1
8
7
7
1
2
0
7
3
1
2
3
1
1
1
2
2
1
0
1
2
7
8
3
1
3
1
0
4
1
3
2
9
3
1
3
4
8
6
1
3
7
1
4
1
3
7
9
6
1
3
7
5
6
1
4
0
8
0
2
.
4
2.
0
OE
CD
3
8
2
1
3
7
9
7
3
8
4
0
3
8
8
4
3
8
6
6
3
8
3
8
3
8
6
9
3
8
5
0
3
8
7
5
3
8
6
5
3
8
7
4
3
8
1
4
3
8
9
8
3
8
7
5
3
9
0
9
4
0
0
0
4
1
6
2
4
1
8
0
4
1
0
0
4
2
0
1
2
.
4
0.
5
G7
2
7
3
5
2
7
1
4
2
7
1
2
2
7
2
5
2
6
9
4
2
6
5
3
2
6
6
8
2
6
4
2
2
6
6
5
2
6
5
7
2
6
6
8
2
6
1
9
2
6
7
1
2
6
7
1
2
6
8
7
2
7
5
8
2
9
1
7
2
9
3
8
2
8
5
3
2
9
6
4
3
.
9
0.
5
BRI
CS
2
6
3
9
2
6
6
7
2
7
4
6
2
8
3
8
2
9
5
1
3
2
0
5
3
4
3
7
3
6
3
0
3
7
9
9
3
9
6
2
4
0
5
8
4
1
1
5
4
4
2
3
4
6
0
8
4
6
5
4
4
7
4
0
4
7
9
5
4
8
3
4
4
8
0
6
4
9
7
4
3
.
5
3.
6

Eur
op
e
1
2
2
7
1
2
2
8
1
2
3
9
1
2
3
7
1
2
4
5
1
2
3
7
1
2
2
6
1
1
9
2
1
1
6
8
1
1
4
6
1
1
5
2
1
1
1
3
1
1
2
3
1
0
8
1
1
0
7
6
1
0
6
4
1
0
4
5
1
0
5
2
1
0
4
9
1
0
5
9
1
.
0
-
0.
9
Eur
op
ean
Uni
on
9
6
0
9
6
1
9
5
2
9
5
3
9
5
2
9
4
4
9
3
9
9
1
1
8
9
1
8
6
8
8
6
3
8
2
7
8
4
4
8
1
0
8
0
3
7
9
8
7
7
9
7
7
3
7
6
2
7
5
8
-
0
.
6
-
1.
3
Bel
giu
m
1
3
1
4
1
4
1
3
1
3
1
4
1
4
1
4
1
4
1
4
1
4
1
5
1
6
1
6
1
4
1
5
1
3
1
1
1
5
1
5
-
0
.
6
0.
6
Cz
ech
Re
p.
3
2
2
9
3
1
3
2
3
2
3
4
3
5
3
3
3
4
3
4
3
3
3
2
3
2
3
3
3
3
3
1
3
0
2
9
2
8
2
9
2
.
6
-
0.
4
Fra
nce
1
2
5
1
2
7
1
3
1
1
3
2
1
3
4
1
3
6
1
3
7
1
3
7
1
3
6
1
3
4
1
3
6
1
2
8
1
3
5
1
3
6
1
3
4
1
3
6
1
3
7
1
3
8
1
3
1
1
3
1
-
0
.
2
0.
0
Ger
ma
ny
1
3
7
1
3
8
1
3
6
1
3
5
1
3
4
1
3
5
1
3
7
1
3
7
1
3
9
1
3
6
1
3
3
1
2
6
1
2
9
1
2
3
1
2
3
1
2
1
1
2
0
1
2
0
1
1
7
1
2
2
4
.
5
-
0.
6
Ital
y
3
1
2
9
2
8
2
7
2
9
3
0
2
9
3
1
3
0
3
1
3
3
3
2
3
3
3
2
3
5
3
7
3
7
3
6
3
5
3
5
-
0
.
8
1.
2
Net
herl
and
s
6
4
6
0
5
8
6
2
6
1
5
9
6
8
6
3
6
1
6
1
6
7
6
3
7
0
6
4
6
5
6
9
5
9
4
8
4
4
4
0
-
1
0
.
0
-
2.
2
Pol
and
8
7
8
4
8
0
8
1
8
0
8
0
7
9
7
9
7
8
7
2
7
1
6
7
6
7
6
8
7
2
7
1
6
8
6
8
6
9
6
4
-
6
.
7
-
1.
3
Por
tug
al 4 3 4 4 4 4 4 4 4 5 4 5 6 6 5 6 6 5 6 5
-
1
4
.
3
1.
7
Ro
ma
nia
2
9
2
8
2
8
2
8
2
9
2
9
2
8
2
8
2
8
2
8
2
9
2
8
2
8
2
8
2
7
2
6
2
7
2
7
2
5
2
6
2
.
8
-
0.
5
Sp
ain
3
3
3
1
3
2
3
4
3
2
3
3
3
3
3
1
3
2
3
1
3
0
3
0
3
5
3
2
3
4
3
5
3
5
3
4
3
4
3
2
-
5
.
2
0.
0
Sw
ede
n
3
4
3
3
3
0
3
4
3
2
3
1
3
4
3
5
3
3
3
4
3
3
3
0
3
3
3
3
3
6
3
5
3
5
3
4
3
5
3
7
4
.
8
1.
1
Uni
ted
Kin
gdo
m
2
7
2
2
8
2
2
7
2
2
6
2
2
5
9
2
4
7
2
2
6
2
0
5
1
8
7
1
7
6
1
6
7
1
5
9
1
5
0
1
3
1
1
1
8
1
1
1
1
0
9
1
1
9
1
2
1
1
2
1
0
.
2
-
4.
7
Nor
wa
y
2
0
7
2
1
0
2
2
8
2
2
7
2
3
6
2
3
5
2
2
9
2
2
4
2
1
6
2
1
5
2
2
2
2
1
7
2
0
8
1
9
9
2
0
3
1
9
4
1
9
6
2
0
8
2
1
0
2
1
6
2
.
7
-
0.
3
Tur
key
2
9
2
8
2
6
2
5
2
4
2
4
2
4
2
4
2
6
2
7
2
9
3
0
3
2
3
2
3
1
3
2
3
1
3
2
3
7
4
3
1
8
3.
0

.
0
CIS
1
1
7
6
1
2
0
8
1
2
5
6
1
2
9
7
1
3
4
7
1
4
4
0
1
5
0
8
1
5
5
6
1
6
0
3
1
6
4
1
1
6
8
0
1
5
8
9
1
6
9
2
1
7
3
7
1
7
5
9
1
7
8
6
1
7
6
5
1
7
6
5
1
7
9
0
1
8
5
9
3
.
9
2.
3
Kaz
akh
sta
n
6
5
6
6
7
9
8
4
9
1
1
0
2
1
1
5
1
1
9
1
2
8
1
3
2
1
4
4
1
4
8
1
5
7
1
6
0
1
6
5
1
6
9
1
6
6
1
6
4
1
6
1
1
7
8
1
0
.
1
4.
9
Ru
ssi
a
9
4
4
9
6
2
9
7
8
1
0
0
8
1
0
4
6
1
1
1
9
1
1
7
2
1
2
0
3
1
2
2
7
1
2
3
9
1
2
5
4
1
1
9
0
1
2
7
9
1
2
9
9
1
3
1
6
1
3
3
1
1
3
1
9
1
3
3
4
1
3
6
2
1
4
1
8
4
.
2
2.
2
Ukr
ain
e
7
1
7
2
7
2
7
2
7
3
7
5
7
6
8
1
8
3
8
3
8
4
7
9
7
9
8
6
8
5
8
6
7
7
6
2
6
4
6
3
-
2
.
1
-
0.
8
Uz
bek
ista
n
5
5
5
5
5
5
5
6
5
6
5
7
5
8
5
7
5
9
6
0
6
2
5
7
5
5
5
7
5
7
5
4
5
6
5
6
5
7
5
7
0
.
3
0.
2
Am
eri
ca
2
8
8
8
2
8
5
3
2
8
8
5
2
9
2
0
2
9
0
5
2
9
0
4
2
9
8
5
3
0
0
3
3
0
7
3
3
0
6
3
3
0
8
6
3
0
5
8
3
1
2
3
3
2
2
1
3
2
8
0
3
3
5
7
3
5
2
5
3
5
1
7
3
4
2
2
3
4
9
5
2
.
1
1.
1
Nor
th
Am
eri
ca
2
0
6
2
2
0
3
5
2
0
4
0
2
0
6
6
2
0
4
2
2
0
2
3
2
0
4
6
2
0
3
3
2
0
7
3
2
0
8
9
2
1
1
2
2
0
8
0
2
1
2
5
2
1
9
9
2
2
4
9
2
3
2
6
2
4
8
8
2
4
9
5
2
4
2
0
2
5
2
2
4
.
2
1.
3
Ca
nad
a
3
7
1
3
6
9
3
7
7
3
8
1
3
8
6
3
8
8
4
0
0
4
0
1
4
1
8
4
1
9
4
0
9
3
9
4
4
0
1
4
1
4
4
2
5
4
4
5
4
6
9
4
7
0
4
8
1
5
0
4
4
.
8
1.
7
Uni
ted
Sta
tes
1
6
9
1
1
6
6
5
1
6
6
3
1
6
8
4
1
6
5
6
1
6
3
5
1
6
4
6
1
6
3
2
1
6
5
5
1
6
7
0
1
7
0
2
1
6
8
6
1
7
2
4
1
7
8
5
1
8
2
4
1
8
8
1
2
0
1
9
2
0
2
5
1
9
3
9
2
0
1
8
4
.
1
1.
1
Lat
in
Am
eri
ca
8
2
6
8
1
8
8
4
5
8
5
4
8
6
3
8
8
2
9
3
9
9
7
0
1
0
0
0
9
7
3
9
7
4
9
7
8
9
9
8
1
0
2
2
1
0
3
1
1
0
3
1
1
0
3
7
1
0
2
2
1
0
0
2
9
7
3
-
2
.
9
0.
8
Arg
enti
na
8
0
8
1
8
3
8
5
8
3
8
6
8
6
8
5
8
6
8
3
8
3
8
1
8
0
7
8
7
6
7
2
7
3
7
4
7
5
7
4
-
2
.
6
-
0.
7
Bra
zil
1
3
4
1
4
2
1
4
8
1
5
2
1
6
8
1
7
8
1
8
3
1
9
5
2
0
7
2
1
7
2
2
9
2
3
1
2
4
7
2
5
0
2
5
3
2
5
4
2
6
8
2
8
0
2
8
8
2
9
3
1
.
7
4.
1
Chil
e 8 8 9 9 9 9 9 9
1
0 9
1
0
1
0 9
1
0
1
3
1
5
1
3
1
3
1
3
1
4
7
.
0
2.
9
Col
om
bia
7
3
7
6
7
2
7
2
6
8
7
3
7
5
7
9
8
4
8
7
9
3
9
8
1
0
6
1
2
0
1
2
5
1
2
4
1
2
7
1
2
5
1
2
3
1
2
2
-
0
.
4
3.
1
Me
xic
o
2
2
6
2
2
5
2
2
8
2
3
4
2
3
7
2
5
1
2
5
4
2
5
9
2
5
9
2
4
8
2
2
8
2
2
4
2
1
5
2
1
7
2
1
9
2
1
7
2
0
9
1
9
2
1
8
1
1
6
7
-
7
.
9
-
1.
8
Ve 2 2 2 2 2 1 2 2 2 1 2 2 1 1 1 1 1 1 1 1 - -

nez
uel
a
2
7
0
6
1
6
1
2
0
3
7
9
1
8
2
3
2
6
9
9
0
1
0
0
9
8
9
9
9
4
9
2
8
6
8
3
7
1
5
4
9
.
6
2.
0
Asi
a
2
0
8
1
2
1
0
3
2
1
8
2
2
2
5
0
2
3
2
3
2
4
9
9
2
7
1
9
2
9
1
5
3
0
9
1
3
2
2
9
3
3
1
0
3
4
6
1
3
7
1
2
3
8
7
6
3
8
9
9
3
9
9
6
4
0
5
3
4
0
5
5
3
9
8
6
4
1
2
9
3
.
6
3.
8
Chi
na
1
0
7
9
1
0
7
4
1
1
2
4
1
1
7
6
1
2
2
7
1
3
7
5
1
5
3
4
1
6
7
1
1
7
9
3
1
9
1
7
1
9
6
7
2
0
5
2
2
2
3
6
2
3
8
5
2
4
0
0
2
4
6
6
2
4
9
6
2
4
9
8
2
4
1
5
2
4
9
9
3
.
5
4.
8
Indi
a
3
3
7
3
4
4
3
5
1
3
5
7
3
6
7
3
7
9
3
9
1
4
0
2
4
1
6
4
3
1
4
4
7
4
8
1
4
9
7
5
1
0
5
2
0
5
2
5
5
4
3
5
5
4
5
7
5
5
9
6
3
.
6
3.
2
Ind
one
sia
2
2
9
2
3
8
2
3
7
2
4
2
2
4
8
2
5
5
2
6
5
2
8
0
3
1
3
3
1
8
3
2
3
3
5
1
3
7
8
4
2
1
4
3
3
4
5
3
4
4
8
4
2
6
4
0
5
4
2
9
5
.
9
3.
5
Jap
an
1
0
8
1
0
3
1
0
5
1
0
3
9
5
8
2
9
3
9
9
1
0
0
8
9
8
7
9
3
9
9
5
1
2
8
2
8
2
6
3
0
3
0
3
5
1
6
.
3
-
6.
3
Mal
ays
ia
7
5
7
4
7
8
7
9
8
2
8
5
9
3
9
7
9
4
9
4
9
7
9
1
9
0
8
8
8
8
9
4
9
5
9
7
9
9
1
0
2
3
.
0
1.
6
So
uth
Kor
ea
2
8
3
2
3
6
3
7
3
8
4
1
4
2
4
7
4
8
4
7
5
0
4
9
5
1
5
3
5
3
5
1
5
8
6
1
6
2
6
2
0
.
0
3.
2
Tai
wa
n
1
1
1
2
1
2
1
1
1
2
1
2
1
2
1
2
1
2
1
3
1
3
1
3
1
3
1
4
1
3
1
4
1
4
1
2
1
1 8
-
2
3
.
1
-
2.
0
Tha
ilan
d
4
0
4
2
4
4
4
3
4
6
4
9
5
1
5
5
5
7
6
0
6
6
6
5
7
1
6
9
7
5
7
8
7
9
7
5
7
6
7
4
-
2
.
7
3.
1
Pa
cifi
c
2
3
6
2
3
4
2
5
4
2
6
9
2
7
3
2
7
0
2
7
1
2
8
3
2
8
8
3
0
5
3
0
6
3
1
5
3
4
3
3
3
2
3
4
0
3
6
5
3
9
0
4
0
9
4
1
6
4
1
5
-
0
.
3
2.
9
Aus
trali
a
2
1
7
2
1
4
2
3
4
2
4
9
2
5
4
2
5
2
2
5
3
2
6
5
2
7
0
2
8
6
2
8
7
2
9
5
3
2
4
3
1
3
3
2
1
3
4
5
3
6
6
3
8
1
3
8
8
3
8
6
-
0
.
6
3.
0
Ne
w
Zea
lan
d
1
4
1
4
1
4
1
5
1
5
1
3
1
3
1
3
1
3
1
4
1
5
1
6
1
7
1
6
1
6
1
6
1
7
1
7
1
6
1
6
-
1
.
4
0.
7
Afri
ca
8
4
1
8
5
2
8
7
5
8
9
0
8
9
8
9
6
0
1
0
2
0
1
0
7
6
1
1
0
1
1
1
3
5
1
1
5
1
1
1
2
7
1
1
6
2
1
0
9
0
1
1
4
9
1
1
0
7
1
1
0
0
1
1
0
1
1
0
9
4
1
1
2
2
2
.
5
1.
5
Alg
eria
1
2
7
1
3
7
1
4
2
1
3
7
1
4
3
1
5
5
1
5
8
1
6
7
1
6
5
1
6
4
1
6
2
1
5
3
1
5
1
1
4
6
1
4
4
1
3
8
1
4
3
1
4
3
1
5
4
1
4
8
-
3
.
7
0.
2
Egy
pt
5
7
5
9
5
3
5
7
5
9
6
2
6
2
7
8
8
1
8
5
8
9
8
8
8
4
8
4
8
2
7
7
7
4
6
9
6
8
7
3
7
.
5
1.
9
Nig 1 1 1 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1.

eria
8
5
8
3
9
8
0
8
9
2
1
6
3
0
3
4
3
3
3
6
3
2
2
5
5
4
5
9
6
6
5
0
5
4
5
4
4
3
5
0
.
6 4
So
uth
Afri
ca
1
4
5
1
4
5
1
4
6
1
4
5
1
4
4
1
5
3
1
5
8
1
5
8
1
5
8
1
5
9
1
6
2
1
6
1
1
6
4
1
6
3
1
6
6
1
6
6
1
6
8
1
6
7
1
6
7
1
6
8
0
.
6
0.
8
Mid
dle
-
Ea
st
1
2
6
8
1
2
4
7
1
3
2
5
1
3
1
5
1
2
6
1
1
3
6
0
1
4
5
2
1
5
1
8
1
5
5
2
1
5
5
4
1
6
2
5
1
5
4
8
1
6
2
9
1
7
6
8
1
7
9
2
1
8
1
1
1
8
3
6
1
8
9
8
1
9
9
9
2
0
0
2
0
.
1
2.
5
Iran
2
4
1
2
4
4
2
5
4
2
4
8
2
5
4
2
8
1
2
9
3
3
1
1
3
2
3
3
3
7
3
3
8
3
3
4
3
4
2
3
4
6
2
9
7
2
9
8
3
1
6
3
2
4
3
6
8
4
0
1
8
.
9
2.
7
Ku
wai
t
1
1
7
1
0
8
1
1
4
1
1
2
1
0
1
1
2
1
1
3
1
1
4
7
1
5
1
1
4
7
1
5
3
1
3
0
1
3
5
1
5
4
1
7
3
1
7
0
1
6
6
1
6
8
1
7
6
1
6
8
-
4
.
7
2.
3
Sa
udi
Ara
bia
4
7
9
4
4
2
4
7
6
4
6
4
4
3
5
5
0
6
5
4
3
5
7
1
5
6
5
5
4
6
5
7
3
5
1
9
5
3
1
5
9
3
6
2
5
6
1
4
6
2
2
6
4
9
6
6
9
6
5
2
-
2
.
6
1.
9
Uni
ted
Ara
b
Emi
rate
s
1
5
0
1
4
2
1
5
4
1
5
5
1
4
8
1
6
2
1
7
0
1
7
5
1
8
5
1
8
3
1
8
6
1
7
2
1
7
8
1
9
7
2
0
5
2
1
2
2
1
5
2
3
0
2
3
6
2
2
9
-
3
.
2
2.
4