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- Genre: Doctoral Dissertation
Description
Stress-related failure such as cracking are an important photovoltaic (PV) reliability issue since it accounts for a high percentage of power losses in the midlife-failure and wear-out failure regimes. Cell cracking can only be correlated with module degradation when cracks are of detectable size and detrimental to the performance. Several techniques have been explored to access the deflection and stress status on solar cell, but they have disadvantages such as high surface sensitivity.
This dissertation presents a new and non-destructive method for mapping the deflection on encapsulated solar cells using X-ray topography (XRT). This method is based on Bragg diffraction imaging, where only the areas that meet diffraction conditions will present contrast. By taking XRT images of the solar cell at various sample positions and applying an in-house developed algorithm framework, the cell‘s deflection map is obtained. Error analysis has demonstrated that the errors from the experiment and the data processing are below 4.4 and 3.3%.
Von Karman plate theory has been applied to access the stress state of the solar cells. Under the assumptions that the samples experience pure bending and plain stress conditions, the principal stresses are obtained from the cell deflection data. Results from a statistical analysis using a Weibull distribution suggest that 0.1% of the data points can contribute to critical failure. Both the soldering and lamination processes put large amounts of stress on solar cells. Even though glass/glass packaging symmetry is preferred over glass/backsheet, the solar cells inside the glass/glass packaging experience significantly more stress. Through a series of in-situ four-point bending test, the assumptions behind Von Karman theory are validated for cases where the neutral plane is displaced by the tensile and compressive stresses.
The deflection and stress mapping method is applied to two next generation PV concepts named Flex-circuit and PVMirror. The Flex-circuit module concept replaces traditional metal ribbons with Al foils for electrical contact and PVMirror concept utilizes a curved PV module design with a dichroic film for thermal storage and electrical output. The XRT framework proposed in this dissertation successfully characterized the impact of various novel interconnection and packaging solutions.
This dissertation presents a new and non-destructive method for mapping the deflection on encapsulated solar cells using X-ray topography (XRT). This method is based on Bragg diffraction imaging, where only the areas that meet diffraction conditions will present contrast. By taking XRT images of the solar cell at various sample positions and applying an in-house developed algorithm framework, the cell‘s deflection map is obtained. Error analysis has demonstrated that the errors from the experiment and the data processing are below 4.4 and 3.3%.
Von Karman plate theory has been applied to access the stress state of the solar cells. Under the assumptions that the samples experience pure bending and plain stress conditions, the principal stresses are obtained from the cell deflection data. Results from a statistical analysis using a Weibull distribution suggest that 0.1% of the data points can contribute to critical failure. Both the soldering and lamination processes put large amounts of stress on solar cells. Even though glass/glass packaging symmetry is preferred over glass/backsheet, the solar cells inside the glass/glass packaging experience significantly more stress. Through a series of in-situ four-point bending test, the assumptions behind Von Karman theory are validated for cases where the neutral plane is displaced by the tensile and compressive stresses.
The deflection and stress mapping method is applied to two next generation PV concepts named Flex-circuit and PVMirror. The Flex-circuit module concept replaces traditional metal ribbons with Al foils for electrical contact and PVMirror concept utilizes a curved PV module design with a dichroic film for thermal storage and electrical output. The XRT framework proposed in this dissertation successfully characterized the impact of various novel interconnection and packaging solutions.
ContributorsMeng, Xiaodong (Author) / Bertoni, Marian I (Thesis advisor) / Meier, Rico (Committee member) / Holman, Zachary C (Committee member) / Alford, Terry (Committee member) / Arizona State University (Publisher)
Created2019
Description
Serial femtosecond crystallography (SFX) with X-ray free electron lasers (XFELs) has enabled the determination of damage-free protein structures at ambient temperatures and of reaction intermediate species with time resolution on the order of hundreds of femtoseconds. However, currently available XFEL facility X-ray pulse structures waste the majority of continuously injected crystal sample, requiring a large quantity (up to grams) of crystal sample to solve a protein structure. Furthermore, mix-and-inject serial crystallography (MISC) at XFEL facilities requires fast mixing for short (millisecond) reaction time points (𝑡"), and current sample delivery methods have complex fabrication and assembly requirements.
To reduce sample consumption during SFX, a 3D printed T-junction for generating segmented aqueous-in-oil droplets was developed. The device surface properties were characterized both with and without a surface coating for improved droplet generation stability. Additionally, the droplet generation frequency was characterized. The 3D printed device interfaced with gas dynamic virtual nozzles (GDVNs) at the Linac Coherent Light Source (LCLS), and a relationship between the aqueous phase volume and the resulting crystal hit rate was developed. Furthermore, at the European XFEL (EuXFEL) a similar quantity and quality of diffraction data was collected for segmented sample delivery using ~60% less sample volume than continuous injection, and a structure of 3-deoxy-D-manno- octulosonate 8-phosphate synthase (KDO8PS) delivered by segmented injection was solved that revealed new structural details to a resolution of 2.8 Å.
For MISC, a 3D printed hydrodynamic focusing mixer for fast mixing by diffusion was developed to automate device fabrication and simplify device assembly. The mixer was characterized with numerical models and fluorescence microscopy. A variety of devices were developed to reach reaction intermediate time points, 𝑡", on the order of 100 – 103 ms. These devices include 3D printed mixers coupled to glass or 3D printed GDVNs and two designs of mixers with GDVNs integrated into the one device. A 3D printed mixer coupled to a glass GDVN was utilized at LCLS to study the oxidation of cytochrome c oxidase (CcO), and a structure of the CcO Pr intermediate was determined at 𝑡" = 8 s.
To reduce sample consumption during SFX, a 3D printed T-junction for generating segmented aqueous-in-oil droplets was developed. The device surface properties were characterized both with and without a surface coating for improved droplet generation stability. Additionally, the droplet generation frequency was characterized. The 3D printed device interfaced with gas dynamic virtual nozzles (GDVNs) at the Linac Coherent Light Source (LCLS), and a relationship between the aqueous phase volume and the resulting crystal hit rate was developed. Furthermore, at the European XFEL (EuXFEL) a similar quantity and quality of diffraction data was collected for segmented sample delivery using ~60% less sample volume than continuous injection, and a structure of 3-deoxy-D-manno- octulosonate 8-phosphate synthase (KDO8PS) delivered by segmented injection was solved that revealed new structural details to a resolution of 2.8 Å.
For MISC, a 3D printed hydrodynamic focusing mixer for fast mixing by diffusion was developed to automate device fabrication and simplify device assembly. The mixer was characterized with numerical models and fluorescence microscopy. A variety of devices were developed to reach reaction intermediate time points, 𝑡", on the order of 100 – 103 ms. These devices include 3D printed mixers coupled to glass or 3D printed GDVNs and two designs of mixers with GDVNs integrated into the one device. A 3D printed mixer coupled to a glass GDVN was utilized at LCLS to study the oxidation of cytochrome c oxidase (CcO), and a structure of the CcO Pr intermediate was determined at 𝑡" = 8 s.
ContributorsEchelmeier, Austin (Author) / Ros, Alexandra (Thesis advisor) / Levitus, Marcia (Committee member) / Weierstall, Uwe (Committee member) / Arizona State University (Publisher)
Created2019
Description
Robotic lower limb prostheses provide new opportunities to help transfemoral amputees regain mobility. However, their application is impeded by that the impedance control parameters need to be tuned and optimized manually by prosthetists for each individual user in different task environments. Reinforcement learning (RL) is capable of automatically learning from interacting with the environment. It becomes a natural candidate to replace human prosthetists to customize the control parameters. However, neither traditional RL approaches nor the popular deep RL approaches are readily suitable for learning with limited number of samples and samples with large variations. This dissertation aims to explore new RL based adaptive solutions that are data-efficient for controlling robotic prostheses.
This dissertation begins by proposing a new flexible policy iteration (FPI) framework. To improve sample efficiency, FPI can utilize either on-policy or off-policy learning strategy, can learn from either online or offline data, and can even adopt exiting knowledge of an external critic. Approximate convergence to Bellman optimal solutions are guaranteed under mild conditions. Simulation studies validated that FPI was data efficient compared to several established RL methods. Furthermore, a simplified version of FPI was implemented to learn from offline data, and then the learned policy was successfully tested for tuning the control parameters online on a human subject.
Next, the dissertation discusses RL control with information transfer (RL-IT), or knowledge-guided RL (KG-RL), which is motivated to benefit from transferring knowledge acquired from one subject to another. To explore its feasibility, knowledge was extracted from data measurements of able-bodied (AB) subjects, and transferred to guide Q-learning control for an amputee in OpenSim simulations. This result again demonstrated that data and time efficiency were improved using previous knowledge.
While the present study is new and promising, there are still many open questions to be addressed in future research. To account for human adaption, the learning control objective function may be designed to incorporate human-prosthesis performance feedback such as symmetry, user comfort level and satisfaction, and user energy consumption. To make the RL based control parameter tuning practical in real life, it should be further developed and tested in different use environments, such as from level ground walking to stair ascending or descending, and from walking to running.
This dissertation begins by proposing a new flexible policy iteration (FPI) framework. To improve sample efficiency, FPI can utilize either on-policy or off-policy learning strategy, can learn from either online or offline data, and can even adopt exiting knowledge of an external critic. Approximate convergence to Bellman optimal solutions are guaranteed under mild conditions. Simulation studies validated that FPI was data efficient compared to several established RL methods. Furthermore, a simplified version of FPI was implemented to learn from offline data, and then the learned policy was successfully tested for tuning the control parameters online on a human subject.
Next, the dissertation discusses RL control with information transfer (RL-IT), or knowledge-guided RL (KG-RL), which is motivated to benefit from transferring knowledge acquired from one subject to another. To explore its feasibility, knowledge was extracted from data measurements of able-bodied (AB) subjects, and transferred to guide Q-learning control for an amputee in OpenSim simulations. This result again demonstrated that data and time efficiency were improved using previous knowledge.
While the present study is new and promising, there are still many open questions to be addressed in future research. To account for human adaption, the learning control objective function may be designed to incorporate human-prosthesis performance feedback such as symmetry, user comfort level and satisfaction, and user energy consumption. To make the RL based control parameter tuning practical in real life, it should be further developed and tested in different use environments, such as from level ground walking to stair ascending or descending, and from walking to running.
ContributorsGao, Xiang (Author) / Si, Jennie (Thesis advisor) / Huang, He Helen (Committee member) / Santello, Marco (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Arizona State University (Publisher)
Created2020
Description
Presented is a design approach and test of a novel compact waveguide that demonstrated the outer dimensions of a rectangular waveguide through the introduction of parallel raised strips, or flanges, which run the length of the rectangular waveguide along the direction of wave propagation. A 10GHz waveguide was created with outer dimensions of a=9.0mm and b=3.6mm compared to a WR-90 rectangular waveguide with outer dimensions of a=22.86mm and b=10.16mm which the area is over 7 times the area. The first operating bandwidth for a hollow waveguide of dimensions a=9.0mm and b=3.6mm starts at 16.6GHz a 40% reduction in cutoff frequency.
The prototyped and tested compact waveguide demonstrated an operating close to the predicted 2GHz with predicted vs measured injection loss generally within 0.25dB and an overall measured injection loss of approximately 4.67dB/m within the operating bandwidth.
The prototyped and tested compact waveguide demonstrated an operating close to the predicted 2GHz with predicted vs measured injection loss generally within 0.25dB and an overall measured injection loss of approximately 4.67dB/m within the operating bandwidth.
ContributorsJones, Jimmy, Ph.D (Author) / Pan, George (Thesis advisor) / Palais, Joseph (Committee member) / Aberle, James T., 1961- (Committee member) / Young, William (Committee member) / Arizona State University (Publisher)
Created2019
Description
This dissertation explores thermal effects and electrical characteristics in metal-oxide-semiconductor field effect transistor (MOSFET) devices and circuits using a multiscale dual-carrier approach. Simulating electron and hole transport with carrier-phonon interactions for thermal transport allows for the study of complementary logic circuits with device level accuracy in electrical characteristics and thermal effects. The electrical model is comprised of an ensemble Monte Carlo solution to the Boltzmann Transport Equation coupled with an iterative solution to two-dimensional (2D) Poisson’s equation. The thermal model solves the energy balance equations accounting for carrier-phonon and phonon-phonon interactions. Modeling of circuit behavior uses parametric iteration to ensure current and voltage continuity. This allows for modeling of device behavior, analyzing circuit performance, and understanding thermal effects.
The coupled electro-thermal approach, initially developed for individual n-channel MOSFET (NMOS) devices, now allows multiple devices in tandem providing a platform for better comparison with heater-sensor experiments. The latest electro-thermal solver allows simulation of multiple NMOS and p-channel MOSFET (PMOS) devices, providing a platform for the study of complementary MOSFET (CMOS) circuit behavior. Modeling PMOS devices necessitates the inclusion of hole transport and hole-phonon interactions. The analysis of CMOS circuits uses the electro-thermal device simulation methodology alongside parametric iteration to ensure current continuity. Simulating a CMOS inverter and analyzing the extracted voltage transfer characteristics verifies the efficacy of this methodology. This work demonstrates the effectiveness of the dual-carrier electro-thermal solver in simulating thermal effects in CMOS circuits.
The coupled electro-thermal approach, initially developed for individual n-channel MOSFET (NMOS) devices, now allows multiple devices in tandem providing a platform for better comparison with heater-sensor experiments. The latest electro-thermal solver allows simulation of multiple NMOS and p-channel MOSFET (PMOS) devices, providing a platform for the study of complementary MOSFET (CMOS) circuit behavior. Modeling PMOS devices necessitates the inclusion of hole transport and hole-phonon interactions. The analysis of CMOS circuits uses the electro-thermal device simulation methodology alongside parametric iteration to ensure current continuity. Simulating a CMOS inverter and analyzing the extracted voltage transfer characteristics verifies the efficacy of this methodology. This work demonstrates the effectiveness of the dual-carrier electro-thermal solver in simulating thermal effects in CMOS circuits.
ContributorsDaugherty, Robin (Author) / Vasileska, Dragica (Thesis advisor) / Aberle, James T., 1961- (Committee member) / Ferry, David (Committee member) / Goodnick, Stephen (Committee member) / Arizona State University (Publisher)
Created2019
Description
Over the last decade, deep neural networks also known as deep learning, combined with large databases and specialized hardware for computation, have made major strides in important areas such as computer vision, computational imaging and natural language processing. However, such frameworks currently suffer from some drawbacks. For example, it is generally not clear how the architectures are to be designed for different applications, or how the neural networks behave under different input perturbations and it is not easy to make the internal representations and parameters more interpretable. In this dissertation, I propose building constraints into feature maps, parameters and and design of algorithms involving neural networks for applications in low-level vision problems such as compressive imaging and multi-spectral image fusion, and high-level inference problems including activity and face recognition. Depending on the application, such constraints can be used to design architectures which are invariant/robust to certain nuisance factors, more efficient and, in some cases, more interpretable. Through extensive experiments on real-world datasets, I demonstrate these advantages of the proposed methods over conventional frameworks.
ContributorsLohit, Suhas Anand (Author) / Turaga, Pavan (Thesis advisor) / Spanias, Andreas (Committee member) / Li, Baoxin (Committee member) / Jayasuriya, Suren (Committee member) / Arizona State University (Publisher)
Created2019
Description
The advent of commercial inexpensive sensors and the advances in information and communication technology (ICT) have brought forth the era of pervasive Quantified-Self. Automatic diet monitoring is one of the most important aspects for Quantified-Self because it is vital for ensuring the well-being of patients suffering from chronic diseases as well as for providing a low cost means for maintaining the health for everyone else. Automatic dietary monitoring consists of: a) Determining the type and amount of food intake, and b) Monitoring eating behavior, i.e., time, frequency, and speed of eating. Although there are some existing techniques towards these ends, they suffer from issues of low accuracy and low adherence. To overcome these issues, multiple sensors were utilized because the availability of affordable sensors that can capture the different aspect information has the potential for increasing the available knowledge for Quantified-Self. For a), I envision an intelligent dietary monitoring system that automatically identifies food items by using the knowledge obtained from visible spectrum camera and infrared spectrum camera. This system is able to outperform the state-of-the-art systems for cooked food recognition by 25% while also minimizing user intervention. For b), I propose a novel methodology, IDEA that performs accurate eating action identification within eating episodes with an average F1-score of 0.92. This is an improvement of 0.11 for precision and 0.15 for recall for the worst-case users as compared to the state-of-the-art. IDEA uses only a single wrist-band which includes four sensors and provides feedback on eating speed every 2 minutes without obtaining any manual input from the user.
ContributorsLee, Junghyo (Author) / Gupta, Sandeep K.S. (Thesis advisor) / Banerjee, Ayan (Committee member) / Li, Baoxin (Committee member) / Chiou, Erin (Committee member) / Kudva, Yogish C. (Committee member) / Arizona State University (Publisher)
Created2019
Description
A critical problem for airborne, ship board, and land based radars operating in maritime or littoral environments is the detection, identification and tracking of targets against backscattering caused by the roughness of the sea surface. Statistical models, such as the compound K-distribution (CKD), were shown to accurately describe two separate structures of the sea clutter intensity fluctuations. The first structure is the texture that is associated with long sea waves and exhibits long temporal decorrelation period. The second structure is the speckle that accounts for reflections from multiple scatters and exhibits a short temporal decorrelation period from pulse to pulse. Existing methods for estimating the CKD model parameters do not include the thermal noise power, which is critical for real sea clutter processing. Estimation methods that include the noise power are either computationally intensive or require very large data records.
This work proposes two new approaches for accurately estimating all three CKD model parameters, including noise power. The first method integrates, in an iterative fashion, the noise power estimation, using one-dimensional nonlinear curve fitting,
with the estimation of the shape and scale parameters, using closed-form solutions in terms of the CKD intensity moments. The second method is similar to the first except it replaces integer-based intensity moments with fractional moments which have been shown to achieve more accurate estimates of the shape parameter. These new methods can be implemented in real time without requiring large data records. They can also achieve accurate estimation performance as demonstrated with simulated and real sea clutter observation datasets. The work also investigates the numerically computed Cram\'er-Rao lower bound (CRLB) of the variance of the shape parameter estimate using intensity observations in thermal noise with unknown power. Using the CRLB, the asymptotic estimation performance behavior of the new estimators is studied and compared to that of other estimators.
This work proposes two new approaches for accurately estimating all three CKD model parameters, including noise power. The first method integrates, in an iterative fashion, the noise power estimation, using one-dimensional nonlinear curve fitting,
with the estimation of the shape and scale parameters, using closed-form solutions in terms of the CKD intensity moments. The second method is similar to the first except it replaces integer-based intensity moments with fractional moments which have been shown to achieve more accurate estimates of the shape parameter. These new methods can be implemented in real time without requiring large data records. They can also achieve accurate estimation performance as demonstrated with simulated and real sea clutter observation datasets. The work also investigates the numerically computed Cram\'er-Rao lower bound (CRLB) of the variance of the shape parameter estimate using intensity observations in thermal noise with unknown power. Using the CRLB, the asymptotic estimation performance behavior of the new estimators is studied and compared to that of other estimators.
ContributorsNorthrop, Judith (Author) / Papandreou-Suppappola, Antonia (Thesis advisor) / Chakrabarti, Chaitali (Committee member) / Tepedelenlioğlu, Cihan (Committee member) / Maurer, Alexander (Committee member) / Arizona State University (Publisher)
Created2019
Description
The open nature of the wireless communication medium makes it inherently vulnerable to an active attack, wherein a malicious adversary (or jammer) transmits into the medium to disrupt the operation of the legitimate users. Therefore, developing techniques to manage the presence of a jammer and to characterize the effect of an attacker on the fundamental limits of wireless communication networks is important. This dissertation studies various Gaussian communication networks in the presence of such an adversarial jammer.
First of all, a standard Gaussian channel is considered in the presence of a jammer, known as a Gaussian arbitrarily-varying channel, but with list-decoding at the receiver. The receiver decodes a list of messages, instead of only one message, with the goal of the correct message being an element of the list. The capacity is characterized, and it is shown that under some transmitter's power constraints the adversary is able to suspend the communication between the legitimate users and make the capacity zero.
Next, generalized packing lemmas are introduced for Gaussian adversarial channels to achieve the capacity bounds for three Gaussian multi-user channels in the presence of adversarial jammers. Inner and outer bounds on the capacity regions of Gaussian multiple-access channels, Gaussian broadcast channels, and Gaussian interference channels are derived in the presence of malicious jammers. For the Gaussian multiple-access channels with jammer, the capacity bounds coincide. In this dissertation, the adversaries can send any arbitrary signals to the channel while none of the transmitter and the receiver knows the adversarial signals' distribution.
Finally, the capacity of the standard point-to-point Gaussian fading channel in the presence of one jammer is investigated under multiple scenarios of channel state information availability, which is the knowledge of exact fading coefficients. The channel state information is always partially or fully known at the receiver to decode the message while the transmitter or the adversary may or may not have access to this information. Here, the adversary model is the same as the previous cases with no knowledge about the user's transmitted signal except possibly the knowledge of the fading path.
First of all, a standard Gaussian channel is considered in the presence of a jammer, known as a Gaussian arbitrarily-varying channel, but with list-decoding at the receiver. The receiver decodes a list of messages, instead of only one message, with the goal of the correct message being an element of the list. The capacity is characterized, and it is shown that under some transmitter's power constraints the adversary is able to suspend the communication between the legitimate users and make the capacity zero.
Next, generalized packing lemmas are introduced for Gaussian adversarial channels to achieve the capacity bounds for three Gaussian multi-user channels in the presence of adversarial jammers. Inner and outer bounds on the capacity regions of Gaussian multiple-access channels, Gaussian broadcast channels, and Gaussian interference channels are derived in the presence of malicious jammers. For the Gaussian multiple-access channels with jammer, the capacity bounds coincide. In this dissertation, the adversaries can send any arbitrary signals to the channel while none of the transmitter and the receiver knows the adversarial signals' distribution.
Finally, the capacity of the standard point-to-point Gaussian fading channel in the presence of one jammer is investigated under multiple scenarios of channel state information availability, which is the knowledge of exact fading coefficients. The channel state information is always partially or fully known at the receiver to decode the message while the transmitter or the adversary may or may not have access to this information. Here, the adversary model is the same as the previous cases with no knowledge about the user's transmitted signal except possibly the knowledge of the fading path.
ContributorsHosseinigoki, Fatemeh (Author) / Kosut, Oliver (Thesis advisor) / Zhang, Junshan (Committee member) / Sankar, Lalitha (Committee member) / Bliss, Daniel (Committee member) / Arizona State University (Publisher)
Created2019
Description
The emergence of perovskite and practical efficiency limit to silicon solar cells has opened door for perovskite and silicon based tandems with the possibility to achieve >30% efficiency. However, there are material and optical challenges that have to be overcome for the success of these tandems. In this work the aim is to understand and improve the light management issues in silicon and perovskite based tandems through comprehensive optical modeling and simulation of current state of the art tandems and by characterizing the optical properties of new top and bottom cell materials. Moreover, to propose practical solutions to mitigate some of the optical losses.
Highest efficiency single-junction silicon and bottom silicon sub-cell in silicon based tandems employ monocrystalline silicon wafer textured with random pyramids. Therefore, the light trapping performance of random pyramids in silicon solar cells is established. An accurate three-dimensional height map of random pyramids is captured and ray-traced to record the angular distribution of light inside the wafer which shows random pyramids trap light as well as Lambertian scatterer.
Second, the problem of front-surface reflectance common to all modules, planar solar cells and to silicon and perovskite based tandems is dealt. A nano-imprint lithography procedure is developed to fabricate polydimethylsiloxane (PDMS) scattering layer carrying random pyramids that effectively reduces the reflectance. Results show it increased the efficiency of planar semi-transparent perovskite solar cell by 10.6% relative.
Next a detailed assessment of light-management in practical two-terminal perovskite/silicon and perovskite/perovskite tandems is performed to quantify reflectance, parasitic and light-trapping losses. For this first a methodology based on spectroscopic ellipsometry is developed to characterize new absorber materials employed in tandems. Characterized materials include wide-bandgap (CH3NH3I3, CsyFA1-yPb(BrxI1-x)3) and low-bandgap (Cs0.05FA0.5MA0.45(Pb0.5Sn0.5)I3) perovskites and wide-bandgap CdTe alloys (CdZnSeTe). Using this information rigorous optical modeling of two-terminal perovskite/silicon and perovskite/perovskite tandems with varying light management schemes is performed. Thus providing a guideline for further development.
Highest efficiency single-junction silicon and bottom silicon sub-cell in silicon based tandems employ monocrystalline silicon wafer textured with random pyramids. Therefore, the light trapping performance of random pyramids in silicon solar cells is established. An accurate three-dimensional height map of random pyramids is captured and ray-traced to record the angular distribution of light inside the wafer which shows random pyramids trap light as well as Lambertian scatterer.
Second, the problem of front-surface reflectance common to all modules, planar solar cells and to silicon and perovskite based tandems is dealt. A nano-imprint lithography procedure is developed to fabricate polydimethylsiloxane (PDMS) scattering layer carrying random pyramids that effectively reduces the reflectance. Results show it increased the efficiency of planar semi-transparent perovskite solar cell by 10.6% relative.
Next a detailed assessment of light-management in practical two-terminal perovskite/silicon and perovskite/perovskite tandems is performed to quantify reflectance, parasitic and light-trapping losses. For this first a methodology based on spectroscopic ellipsometry is developed to characterize new absorber materials employed in tandems. Characterized materials include wide-bandgap (CH3NH3I3, CsyFA1-yPb(BrxI1-x)3) and low-bandgap (Cs0.05FA0.5MA0.45(Pb0.5Sn0.5)I3) perovskites and wide-bandgap CdTe alloys (CdZnSeTe). Using this information rigorous optical modeling of two-terminal perovskite/silicon and perovskite/perovskite tandems with varying light management schemes is performed. Thus providing a guideline for further development.
ContributorsManzoor, Salman (Author) / Holman, Zachary C (Thesis advisor) / King, Richard (Committee member) / Goryll, Michael (Committee member) / Zhao, Yuji (Committee member) / Arizona State University (Publisher)
Created2019