Optimization of reactive ion beam sputtered Ta2O5 for III–V compounds

We report the optimization of the process parameters used in ion beam sputtering of dielectric Ta2O5 thin films on III–V semiconductor surfaces, with an aim of minimizing the deterioration of semiconductor surfaces and their opto-electric performance. We demonstrate that linear tuning of the three main sputtering parameters, namely, the primary source radiofrequency power, the ion beam current, and the ion beam voltage, allows optimizing the deposition conditions of Ta2O5 minimizing the damage to the III–V surfaces. The effect of parametrization is evaluated by deposition of a Ta2O5 antireflection coating on GaAs-based multijunction solar cells employing AlGaAs and AlInP window layers. Numerical study reveals that the main source of damage is the scattered primary ions, in this case argon ions, that have not contributed to the sputtering process of the Ta2O5 at the target. Moreover, it is likely that the reactive oxygen atmosphere oxidizes the semiconductor surfaces in the initial phase of the deposition process. A similar optimization procedure should be employed for any other thin film directly deposited by reactive ion beam sputtering on III–V surfaces and optoelectronics devices to avoid deposition induced damage.publishedVersionPeer reviewe

Calculating defects on semiconductor wafer by image analysis program

Tämän kandidaatin työn aiheena on MBE-kasvatettujen puolijohdekiekon kidevirheet ja niiden laskemiseen tarkoitettu kuvantunnistusohjelma. Puolijohteissa ovaaleja pinnan kidevirheitä on tyypillisesti 100 - 100000 kappaletta neliösenttimetrillä. Niitä aiheuttavat hiukkaskontaminaatio ja kasvatusolosuhteet. Kidevirheiden tutkimista varten luotu kuvantunnistusohjelma on MATLAB pohjainen. Käyttäjä syöttää ohjelmalle halutut mikroskooppikuvat, minkä jälkeen ohjelma analysoi ne ja tulokset tallennetaan tekstitiedostoihin. Analyysi kestää noin 0,7 sekuntia per kuva. Kidevirheiden lukumäärätiheyden lisäksi ohjelma osaa selvittää kidevirheiden kokojakauman. Vertailututkimuksessa kuvantunnistusohjelmaa verrattiin manuaaliseen menetelmään tekemällä kidevirheanalyysi neljälle eri näytteelle. Analyysissä tarvittavien kuvien vähimmäismäärän selvittämiseksi mallinnettiin kidevirheiden lukumäärätiheyden laskemista MATLAB-ohjelmalla. Mallinnuksen perusteella 10x-suurennoksella 10 kuvan pitäisi riittää, jos kidevirheitä on noin 400 1/cm2. Tällöin laskettu lukumäärätiheys on yhden sigman todennäköisyydellä (68%) mitatun arvon 400 +- 80 1/cm2 alueella. Kuvantunnistusohjelma on tarkempi ja monipuolisempi, mutta työläämpi kuin manuaalinen menetelmä. Kuvantunnistusohjelma ja manuaalinen menetelmä saavat melko samansuuruisia lukuarvoja näytteiden kidevirheiden määrälle. Kuvantunnistusohjelma ei välttämättä korvaa vanhaa manuaalista menetelmää, mutta sen tarkkuus ja kidevirheiden kokojakauman selvittäminen ovat hyödyllisiä työkaluja.The topic of this Bachelor's thesis is the image analysis program for calculating the amount of crystal defects in epitaxially grown semiconductor wafer. The amount of oval surface defects is around 100 - 100000 pieces in square centimetre. They are caused by contamination particles and growth conditions in MBE chamber. The image analysis program for calculating defects is created by using MATLAB software. The user feeds the microscope images into the program that analyzes them and saves the results to text files. The analysis takes typically 0,7 seconds per image. The program can find out the density of the defects and the size distribution. In a benchmarking study the image analysis program was compared to manual method analyzing defects in four different sample. The minimum amount of images required to the analysis were determined by using MATLAB software to model the calculating of defect density. According to the results ten images should be enough when the image is taken in 10x magnification and there is 400 defects in a square centimetre. Then the calculated defect density is in the area of 400 +- 80 1/cm2 in probability of 68% or within one standard deviation. The image analysis program is more accurate and versatile than the manual method but more burdensome. The defect density results of both methods are quite of the same magnitude. The program will not necessarily replace the old manual method but its accuracy and the ability to determine the defect size distribution are useful instruments

Depth profiling of composition in MBE grown III--V/Ge solar cells

Multijunction solar cells have shown their ability to achieve very high solar energy conversion efficiencies, making them optimal for energy production on Earth and in space. Many multijunction solar cell architectures use III–V semiconductor materials, like gallium arsenide, on top of a germanium bottom cell. Germanium has a narrow band gap making it suitable for harvesting long wavelengths up to 1800 nm and it can simplify the solar cell fabrication process. One challenge with germanium is, that there is inevitable cross-diffusion between the germanium and III–V layers, which can lead to a formation of a compensated region or an unintentional pn-junction. This problem lowers the efficiency of the multijunction solar cell. There are many possible fabrication methods to minimize the unintentional diffusion between germanium and III–V layers, but to evaluate their effectiveness we need to obtain the depth profile of the solar cell composition. In this thesis, inductively coupled plasma mass spectrometry (ICP-MS) was used to measure the composition depth profiles of germanium bottom cells and III–V layers on top of them. In ICP-MS the sample material (in liquid or gas form) is turned to a plasma and then analysed in a mass spectrometer. For depth profiling semiconductor samples, a custom-made wet etching flow cell was integrated to the unit. In the flow cell, a flowing etchant is used to etch the sample surface and the dissolved material is then fed to the ICP-MS. This method is compared to secondary ion mass spectrometry (SIMS) and electrochemical capacitance-voltage profiling (ECV), that are commonly used for depth profiling. A series of samples of gallium arsenide, germanium and III–V/Ge heterostructures were measured with ICP-MS. A working measurement procedure and a post-analysis program were developed. Comparing the results measured with ICP-MS to SIMS and ECV results showed that ICP-MS with the wet etching flow cell does not produce as accurate diffusion profiles as SIMS for gallium and arsenic in germanium. The shape of etched crater was irregular instead of preferred flat profile. The shape of the etch crater also prevented the measurement of germanium diffusion in gallium arsenide layer. The interference caused by germanium isotopes also affected substantially the measurement of gallium and arsenic compositions. The depth profiles were attempted to reconstruct computationally with an evolution algorithm from the ICP-MS measurement signal and etch crater shape, but the method did not produce reliable results except for one measurement. The SIMS and ECV results were in good agreement and showed the junction formation and cross-diffusion of gallium that was less than 100 nm deep in germanium. In some cases gallium diffused more than arsenic resulting an unintentional junction. It could be possible to obtain similar results with the ICP-MS if its wet etching process would be more uniform, which would require redesigning the flow cell

Depth profiling of composition in MBE grown III--V/Ge solar cells

Multijunction solar cells have shown their ability to achieve very high solar energy conversion efficiencies, making them optimal for energy production on Earth and in space. Many multijunction solar cell architectures use III–V semiconductor materials, like gallium arsenide, on top of a germanium bottom cell. Germanium has a narrow band gap making it suitable for harvesting long wavelengths up to 1800 nm and it can simplify the solar cell fabrication process. One challenge with germanium is, that there is inevitable cross-diffusion between the germanium and III–V layers, which can lead to a formation of a compensated region or an unintentional pn-junction. This problem lowers the efficiency of the multijunction solar cell. There are many possible fabrication methods to minimize the unintentional diffusion between germanium and III–V layers, but to evaluate their effectiveness we need to obtain the depth profile of the solar cell composition. In this thesis, inductively coupled plasma mass spectrometry (ICP-MS) was used to measure the composition depth profiles of germanium bottom cells and III–V layers on top of them. In ICP-MS the sample material (in liquid or gas form) is turned to a plasma and then analysed in a mass spectrometer. For depth profiling semiconductor samples, a custom-made wet etching flow cell was integrated to the unit. In the flow cell, a flowing etchant is used to etch the sample surface and the dissolved material is then fed to the ICP-MS. This method is compared to secondary ion mass spectrometry (SIMS) and electrochemical capacitance-voltage profiling (ECV), that are commonly used for depth profiling. A series of samples of gallium arsenide, germanium and III–V/Ge heterostructures were measured with ICP-MS. A working measurement procedure and a post-analysis program were developed. Comparing the results measured with ICP-MS to SIMS and ECV results showed that ICP-MS with the wet etching flow cell does not produce as accurate diffusion profiles as SIMS for gallium and arsenic in germanium. The shape of etched crater was irregular instead of preferred flat profile. The shape of the etch crater also prevented the measurement of germanium diffusion in gallium arsenide layer. The interference caused by germanium isotopes also affected substantially the measurement of gallium and arsenic compositions. The depth profiles were attempted to reconstruct computationally with an evolution algorithm from the ICP-MS measurement signal and etch crater shape, but the method did not produce reliable results except for one measurement. The SIMS and ECV results were in good agreement and showed the junction formation and cross-diffusion of gallium that was less than 100 nm deep in germanium. In some cases gallium diffused more than arsenic resulting an unintentional junction. It could be possible to obtain similar results with the ICP-MS if its wet etching process would be more uniform, which would require redesigning the flow cell

Calculating defects on semiconductor wafer by image analysis program

Tämän kandidaatin työn aiheena on MBE-kasvatettujen puolijohdekiekon kidevirheet ja niiden laskemiseen tarkoitettu kuvantunnistusohjelma. Puolijohteissa ovaaleja pinnan kidevirheitä on tyypillisesti 100 - 100000 kappaletta neliösenttimetrillä. Niitä aiheuttavat hiukkaskontaminaatio ja kasvatusolosuhteet. Kidevirheiden tutkimista varten luotu kuvantunnistusohjelma on MATLAB pohjainen. Käyttäjä syöttää ohjelmalle halutut mikroskooppikuvat, minkä jälkeen ohjelma analysoi ne ja tulokset tallennetaan tekstitiedostoihin. Analyysi kestää noin 0,7 sekuntia per kuva. Kidevirheiden lukumäärätiheyden lisäksi ohjelma osaa selvittää kidevirheiden kokojakauman. Vertailututkimuksessa kuvantunnistusohjelmaa verrattiin manuaaliseen menetelmään tekemällä kidevirheanalyysi neljälle eri näytteelle. Analyysissä tarvittavien kuvien vähimmäismäärän selvittämiseksi mallinnettiin kidevirheiden lukumäärätiheyden laskemista MATLAB-ohjelmalla. Mallinnuksen perusteella 10x-suurennoksella 10 kuvan pitäisi riittää, jos kidevirheitä on noin 400 1/cm2. Tällöin laskettu lukumäärätiheys on yhden sigman todennäköisyydellä (68%) mitatun arvon 400 +- 80 1/cm2 alueella. Kuvantunnistusohjelma on tarkempi ja monipuolisempi, mutta työläämpi kuin manuaalinen menetelmä. Kuvantunnistusohjelma ja manuaalinen menetelmä saavat melko samansuuruisia lukuarvoja näytteiden kidevirheiden määrälle. Kuvantunnistusohjelma ei välttämättä korvaa vanhaa manuaalista menetelmää, mutta sen tarkkuus ja kidevirheiden kokojakauman selvittäminen ovat hyödyllisiä työkaluja.The topic of this Bachelor's thesis is the image analysis program for calculating the amount of crystal defects in epitaxially grown semiconductor wafer. The amount of oval surface defects is around 100 - 100000 pieces in square centimetre. They are caused by contamination particles and growth conditions in MBE chamber. The image analysis program for calculating defects is created by using MATLAB software. The user feeds the microscope images into the program that analyzes them and saves the results to text files. The analysis takes typically 0,7 seconds per image. The program can find out the density of the defects and the size distribution. In a benchmarking study the image analysis program was compared to manual method analyzing defects in four different sample. The minimum amount of images required to the analysis were determined by using MATLAB software to model the calculating of defect density. According to the results ten images should be enough when the image is taken in 10x magnification and there is 400 defects in a square centimetre. Then the calculated defect density is in the area of 400 +- 80 1/cm2 in probability of 68% or within one standard deviation. The image analysis program is more accurate and versatile than the manual method but more burdensome. The defect density results of both methods are quite of the same magnitude. The program will not necessarily replace the old manual method but its accuracy and the ability to determine the defect size distribution are useful instruments

Lattice‐matched four‐junction tandem solar cell including two dilute nitride bottom junctions

Monolithic four‐junction solar cells incorporating two dilute nitride (GaInNAsSb) bottom junctions are reported. The dilute nitride junctions have band gaps of 0.9 and 1.2 eV, while the top junctions have band gaps of 1.4 and 1.9 eV. By using experimental‐based parametrization, it was estimated that the four‐junction solar cell could theoretically exhibit efficiency levels of 34.7% at one sun, 43.2% at 100 suns, and 46.4% at 1000 suns for AM1.5D illumination. The most challenging subcell in terms of fabrication is the GaInNAsSb bottom junction with 0.9 eV band gap. For this subcell, a background doping level down to 5 × 1014 cm−3 and a high charge carrier lifetime up to 2 to 4 nanoseconds are reported, which reflects high values for current and voltage. An experimental AlGaAs/GaAs/GaInNAsSb/GaInNAsSb solar cell structure was fabricated by molecular beam epitaxy. At one‐sun AM1.5D illumination, the experimental cell exhibited an efficiency of 25%, an average quantum efficiency of 91%, and an open circuit voltage, which is about 87% of the estimated potential. The cell exhibited maximum efficiency of 37% at 100‐sun concentration.acceptedVersionPeer reviewe

Lattice‐matched four‐junction tandem solar cell including two dilute nitride bottom junctions

Monolithic four‐junction solar cells incorporating two dilute nitride (GaInNAsSb) bottom junctions are reported. The dilute nitride junctions have band gaps of 0.9 and 1.2 eV, while the top junctions have band gaps of 1.4 and 1.9 eV. By using experimental‐based parametrization, it was estimated that the four‐junction solar cell could theoretically exhibit efficiency levels of 34.7% at one sun, 43.2% at 100 suns, and 46.4% at 1000 suns for AM1.5D illumination. The most challenging subcell in terms of fabrication is the GaInNAsSb bottom junction with 0.9 eV band gap. For this subcell, a background doping level down to 5 × 1014 cm−3 and a high charge carrier lifetime up to 2 to 4 nanoseconds are reported, which reflects high values for current and voltage. An experimental AlGaAs/GaAs/GaInNAsSb/GaInNAsSb solar cell structure was fabricated by molecular beam epitaxy. At one‐sun AM1.5D illumination, the experimental cell exhibited an efficiency of 25%, an average quantum efficiency of 91%, and an open circuit voltage, which is about 87% of the estimated potential. The cell exhibited maximum efficiency of 37% at 100‐sun concentration.acceptedVersionPeer reviewe

Performance Study of Lattice-Matched Multijunction Solar Cells Incorporating GaInNAsSb Junctions with 0.7 – 1.4 eV Bandgap

We report on the progress made in the development of lattice-matched multijunction solar cells employing dilute nitride sub-cells. In particular, we report on upright four-junction architecture with bandgaps of 0.9 eV, 1.2 eV, 1.4 eV and 1.9 eV The four-junction solar cell includes two dilute nitride sub-junctions. This structure exhibited an efficiency of 29% at 1-sun AM1.5D illumination, which is the highest level reported for such architecture so far. In addition, we report on the progress in developing lattice-matched solar cell materials with a bandgap down to 0.7 eV, which enable the fabrication of highly efficient five- or six-junction solar cells on GaAs. We estimate that under 1000 suns illumination these five- or six-junction cells could reach over 50% efficiencies.acceptedVersionPeer reviewe