Introduction

Solar energy is one of the most promising renewable energies. Its applications are broad, from poweringsmall automated electronics which require low power delivery, to rural electrification that require toassemble several solar cells in solar panels to deliver larger quantities of energy. One of the newestapplications of solar energy is its use on powering reverse osmosis devices in developing countries,hydrogen generation (called «solar hydrogen») and «solar cooling».

Cell efficiency depends on the silicon dopant, light density and wavelength, optical thickness andsurface texture. Efficiency of current solar cells is around 20% but some texturing processes canboost it up to 50%. The manufacturing difficulty of such processes implies a higher cost, making themprohibitive. Space and solar car racing applications demand the highest efficiency solar cells.

Mono-crystalline and Poly-crystalline silicon

Solar cell surface characterization

The greater part of solar cells aremanufactured using mono-crystallineor large-grained poly-crystallinesilicon.

To reduce manufacturing costs thesilicon used has a lower quality thanthe used in the micro-electronics industry. It iscalled metallurgicalgrade silicon and hasabout 98% purity.The silicon lightabsorption effi-ciency is verylow. Therehave beenseveral at-tempts toincrease cellefficiency, likelight concen-tration usingF r e s n e llenses, solar concentrators,antireflection coatings, among others.

The most effective way to increaselight absorption is by increasing theeffective optical thickness of thesilicon surface. Such increase iscalled surface texturing and dependslargely on the nature of the silicon.

Mono-crystalline silicon texturing isaccomplished by a wet

a n i s o t r o p i ce t c h i n gp r o c e s sbased ons o d i u m

h y d r o x i d esolution. The

process iscarried out by

slowly etchingcrysta l lographic

silicon plane {111}.Randomly distributed

square base pyramidsare obtained. The quality of

the surface and the amount ofpyramids depend on the temperature

Figure 1: Solar cellbased on mono-

crystalline silicon wafer.

Solar cell surface characterization

Surface texture characterization

Solar cell quality control is done at theend of the production chain, testingeach individual cell for efficiency in asolar air mass 1.5G simulator.Sensofar offers a solution for qualitycontrol and production control forsome of the key steps during themanufacturing line. The dualtechnology PLμ 2300 Optical ImagingProfiler offers the possibility to con-trol silicon surfacetexture, roughness,pyramid statisticalcharacterization andmetal contact in fewseconds.

Figure 2 shows a 3Dmeasurement of amono-c rys ta l l i nesilicon wafer afterpyramidal etching. Incontrast to the time,consuming ScanningElectron Microscopemeasurement, thewafer is placed under

the PLμ 2300 and a 3D measurementis obtained in less than 10 seconds.The high local slope of the pyramidfaces requires the use high numericalaperture objectives, only available inconfocal technology. For such 3Dmeasure a 150X objective with a 0.95numerical aperture was used,reducing the field of view to few tensof microns, similar to the field of view

and the solution composition. The«light trapping» effect is very effectivewith such surface texture, increasingthe amount of internal reflections, andthus the cell light absorption efficiency,from 10 to 50 times.

In contrast, multi-crystalline silicontexturing is not so effective becausemost of the grains have incorrectorientation. Surface texturing on this

wafers have the disadvantage thatdifferent grains etch at different ratesgiving steps at grain boundaries, thisbeing a problem for the subsequentprocess for metal screening.

Current driving on the silicon surfaceis accomplished by differenttechnologies. The most typical arescreen printed metal, buried contactsand metal insulators.

Figure 2: Mono-crystalline silicon surface aftercrystallographic {111} wet etching. The pyramidal

surface texture increases «light trapping» up to 50 times,increasing the cell efficiency.

Solar cell surface characterization

of a SEM. The surface is scanned fewmicrons along the focus position ofthe objective, collecting the confocalimages plane by plane. The result isa SEM like image with infinite focusand 3D information of the heights ofthe pyramids.In figure 3 a profile cut show a single

pyramid characterization for height,base area and face angles. For thestatistical pyramid characterization, aspecial watershed segmentationalgorithm is used. This segmentationseparates each individual pyramid bythe use of the height information andcalculates area, volume, averageheight and maximum height for each

one of the segmented regions.

Figure 4 shows the segmentedtopography and figure 5 the statisticalpyramid height distribution. Thehistogram distribution is a keyparameter that gives informationabout the number of pyramids, its

uniformity, if there are non-texturedregions and if the texturing processhas created regions with different sizepyramids.

In contrast to pyramidal mono-crystalline silicon texturing, a multi-crystalline silicon surface is muchsmoother. Heights and angles of each

Figure 4: Pyramid topographical segmentationusing a water-shed algorithm. Each pyramid is

isolated and its volume, area and height arecalculated.

Figure 3: Profile cut of the pyramids on a mono-crystalline silicon surface.

Figure 5: Statistical heightdistribution of the pyramids.

Sensofar-Tech, S.L.Ctra. N-150, km. 14,5Mòdul TR20 - IPCTE-08227 TerrassaT. +34 93 739 89 45F. + 34 93 786 01 16info@sensofar.comwww.sensofar.com

Solar cell surface characterization

individual grain are on the sub-micronrange, while size is several timesbigger.

Figure 6 show the result of a 3Dmeasurement on a mono-crystalline

(left) and multi-crystalline (right)surfaces with the same field of view.Surface roughness parameters areshown for comparison. Figure 7 showa metal contact on a mono-crystallinesilicon surface. The height, area andvolume are retrieved from the 3Dinformation.

Figure 7: Conductor made byscreen printed metal.

Figure 6: Mono-crystalline (left) and multi-crystalline (right) surface texture.Surface roughness are compared for both texturing processes.

The small and compact size of thePLμ 2300 sensorhead make it theideal tool to be assembled in theproduction chain for production con-trol.

The easy to use and programmablesoftware allows the possibility to con-trol statistical texturing parameters indifferent regions of single wafers, aswell as metal contact characterizationduring the same scanning process.