The design of the front and rear surfaces of Solar Cells has attracted millions of dollars in research and development, sometimes at small incremental increases in performance. The metal contact design involves the analysis of several optical and electrical losses. Optically, the front metal contacts shade the solar cell; hence, you want to keep them as thin as possible. From an electrical point of view, wider fingers have a lower contact resistance, and thicker fingers reduce the series resistance. Similarly, designs for rear metal contacts are just as important, Back Surface Field solar cells currently dominate the worldwide market, however, ITRPV[1] predict that these will be completely phased out due to the advanced architectures of Passivated Emitter and Rear Contact (PERC) technology which has passivated rear contacts as well as the front.

Learning Objectives

  • Understand the implications of front and rear metal contacts on optical and electrical performance
  • Be able to perform main factor response experiments to determine the most important factor of silver printed fingers to optimise
  • Be able to perform a single factor response experiment to optimise the silver screen printed fingers
  • Be able to perform single factor response experiments to find optimum widths in multi-busbar cells and hence modules
  • Explain the implications of interconnecting ribbons in PV modules

Tutorial Exercise

In this tutorial, you will be exploring the optical and electrical effects of different features that make up the metal contacts of solar cells, optimising the metal grid design. You will optimise the height/thickness and width of the metal contacts, analysing several different optical and electrical parameters. As manufacturing technology develops, the option for more busbars as a method to further reduce losses is becoming more viable; therefore, you will also optimise the busbars. With these optimised values, you will then investigate the Cell-to-Module differences. Make sure to read the relevant SunSolve about pages to understand the different settings available and their effects on performance. Refer to screen-printing and co-firing pages for further reading.

Part One – Optimising Front Contacts, Fingers

The silver (Ag) fingers on the front of the wafer affect both the optical and electrical performance of PV cells. There is often a delicate balance between the reduction of shading caused by the fingers and limiting resistive losses in the fingers. Working with the c-Si SSP Cell template, you will be optimising the Height and Width of the fingers.

For these SunSolve exercises, “-“, “0” and “+” are used to indicate “a lower setting”, “the baseline setting” (or “default”) and “a higher setting” for the factors, respectively. The actual values for these simulation settings are provided in Table 1 below. 

Table 1 - Factor settings to be used in the Main Factor Response experiment.
Factor SettingsMain factors for Finger optimisation
Finger Height (um)Finger Width (um)

The responses you will be observing are listed in Table 2 below.

Table 2 - List of responses to be observed throughout the Main Factor Response experiment.
Front reflected photon current density (JR, Front) mA⁄cm2
Front elements, finger series resistance (RS_Grid) Ω.cm2
Short circuit current density (Jsc) mA⁄cm2
Fill factor

Conducting the experiment

  1. Open a new c-Si SSP Cell simulation.
  2. Using the sweep function setup a single simulation to run the main factor experiment. Follow the layout provided in Table 3 below. Use the run summary to check that the sweep is correct before clicking run.
Table 3 - Main factor response experiment layout
Run No.Factor SettingsResponses
Height (um)Width (um)JR,Front
(mA⁄cm2 )
(mA⁄cm2 )
Fill Factor
  1. Produce a main factor response graph for each factor. 
  2. Identify the most important factor to optimise.
  3. Make sure to save your simulations; any unsaved data will be lost once SunSolve is closed. 

Single Factor Response Experiment

After identifying the most important factor to optimise for silver finger contacts in the main factor response experiment, a single factor response experiment is used to find the optimum value for that factor.  Make sure to record the same responses as in the main factor response experiment.

Conducting the experiment

  1. Use the default settings (“0” setting) for the other factor(s). 
  2. Using the sweep function again, run the simulationwith at least 8 steps starting from the “-“ setting and ending at the “+” setting for your factor. SunSolve can create equal intervals automatically. 
  3. Record the 4 responses for each run of the simulation.
  4. Sketch an X-Y scatter plot for each response (y-axis) versus your factor of interest (x-axis). 
  5. Describe the relationships between yourfactor and each of the responses. 
  6. Identify and record the optimum value for yourCreate a new template with this optimised value.  
  7. Make sure you save your completed simulations appropriately (different to creating a template) 


  1. What is the relationship between finger width and front reflected photon current density?
  2. What is the relationship between series resistance in the fingers and fill factor of the cell? How would you expect an I-V curve to change with increasing series resistance? (i.e. describe the shape)

Part Two – Optimising Front Contacts, Busbars

The width of busbars are a significant source of shading, and the number of busbars also affects the flow of electrons across the fingers of the solar cell. As the screen-printing process and module manufacturing improves, both the number and width of busbars are further optimised. In this section, you will explore the optimum width for 4, 5 and 6 busbars using your cell with optimised Ag Fingers. The different widths for different busbar numbers can be found in Table 4 below.

Table 4 - List of Factor Settings to be used in the optimisation of Busbar widths.
Factor SettingsDifferent Busbar Numbers and Width
Width of 4 Busbars (um)Width of 5 Busbars (um)Width of 6 Busbars (um)

The responses you will be observing are listed in Table 5 below.

Table 5 - List of responses to be observed when optimising busbar widths.
Busbar Series Resistance (RG, Grid) Ω.cm2
Short circuit current density (Jsc) mA⁄cm2
Maximum Power Point (PmpW
Fill factor

Conducting the Experiment

  1. Using the template with optimised Ag Fingers you created in Part One, open a new simulation. Make sure to leave the other settings at their default values.
  2. Set both the front and rear Busbar numbers to 4.
  3. Using the sweep function again, run a simulation with at least 8 steps starting from the “-“ setting and ending at the “+” setting of the Busbar widths outlined in Table 4.
  4. Record the 4 responses as outlined above for each run.
  5. Identify and record the optimum width for 4 Create a new template with this optimised value.
  6. For the optimised width, record the total volume (cm3) of silver used in the production of the cell, this is the front metal total volume
  7. Repeat Steps 1-6 but with 5 and 6 busbars, making sure to use the correct width values as found in Table 4.
  8. Plot a bar graph comparing the number of busbars to the volume of silver used in the optimised cases.
  9. Make sure you save your completed simulations appropriately (different to ‘create template’).


  1. What is the manufacturing significance of keeping the number of front and rear busbars the same and their widths similar?
  2. Why do we not consider the rear electrode layer in Step 6 of Part Two?
  3. Which front grid design required the least amount of silver?
  4. Considering the difference between performance in 5 and 6 busbars, would you recommend investing in new manufacturing equipment to produce 6 busbar cells?

Part Three – Further Understanding of Metallisation

  1. List the 4 sources of parasitic series resistance in Silicon Solar Cells.
  2. Describe and explain the expected relationship between the volume of silver used and the parasitic series resistance.
  3. Does the number of busbars affect the relationship identified above? If so, what is the most important source of series resistance that will affect this relationship?
  4. You now have 3 optimised cells with differing Busbar numbers. Which of these cells has the greatest overall performance? Calculate its efficiency.
  5. Does this cell have the best Optical or Electrical performance? Explain why it might not be optimal for both.
  6. Investigate the other parameters in the “Electrode” tab of SunSolve, suggest possible advances to the screen-printing process that would further optimise both optical and electrical performance.

Part Four – Cell to Module Performance

Using the c-Si SSP Module template, create a module with the same optimised fingers and 6 busbar cells you created in earlier sections. Make sure to consider the number of ribbons required for module fabrication. Run a single simulation recording the responses shown in Table 6 below.

Table 6 - List of responses to be observed throughout the CTM experiment.
Front reflected photon current density (JR, Front) mA⁄cm2
Total series resistance for a cell(RS_Grid) Ω.cm2
Short circuit current density (Jsc) mA⁄cm2
Fill factor
  1. Calculate the CELL efficiency of this module and compare this value to the one calculated in Part Three. Calculate the Module-Cell to the Cell efficiency ratio.
  2. Using the responses from Table 6 above, describe any Cell to Module (CTM) losses (or gains) that can be attributed to the metallisation of the module.
  3. Similarly, what are some aspects of the metallisation process that could be further advanced to obtain CTM gains?
  4. What is a limitation of cell interconnection (ribbons) on cell thickness?


[1] – International Technology Roadmap for Photovoltaics, 10th Edition, 2019, p. 43, fig. 41(a). Available: