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Description
With the application of reverse osmosis (RO) membranes in the wastewater treatment and seawater desalination, the limitation of flux and fouling problems of RO have gained more attention from researchers. Because of the tunable structure and physicochemical properties of nanomaterials, it is a suitable material that can be used to

With the application of reverse osmosis (RO) membranes in the wastewater treatment and seawater desalination, the limitation of flux and fouling problems of RO have gained more attention from researchers. Because of the tunable structure and physicochemical properties of nanomaterials, it is a suitable material that can be used to incorporate with RO to change the membrane performances. Silver is biocidal, which has been used in a variety of consumer products. Recent studies showed that fabricating silver nanoparticles (AgNPs) on membrane surfaces can mitigate the biofouling problem on the membrane. Studies have shown that Ag released from the membrane in the form of either Ag ions or AgNP will accelerate the antimicrobial activity of the membrane. However, the silver release from the membrane will lower the silver loading on the membrane, which will eventually shorten the antimicrobial activity lifetime of the membrane. Therefore, the silver leaching amount is a crucial parameter that needs to be determined for every type of Ag composite membrane.

This study is attempting to compare four different silver leaching test methods, to study the silver leaching potential of the silver impregnated membranes, conducting the advantages and disadvantages of the leaching methods. An In-situ reduction Ag loaded RO membrane was examined in this study. A custom waterjet test was established to create a high-velocity water flow to test the silver leaching from the nanocomposite membrane in a relative extreme environment. The batch leaching test was examined as the most common leaching test method for the silver composite membrane. The cross-flow filtration and dead-end test were also examined to compare the silver leaching amounts.

The silver coated membrane used in this experiment has an initial silver loading of 2.0± 0.51 ug/cm2. The mass balance was conducted for all of the leaching tests. For the batch test, water jet test, and dead-end filtration, the mass balances are all within 100±25%, which is acceptable in this experiment because of the variance of the initial silver loading on the membranes. A bad silver mass balance was observed at cross-flow filtration. Both of AgNP and Ag ions leached in the solution was examined in this experiment. The concentration of total silver leaching into solutions from the four leaching tests are all below the Secondary Drinking Water Standard for silver which is 100 ppb. The cross-flow test is the most aggressive leaching method, which has more than 80% of silver leached from the membrane after 50 hours of the test. The water jet (54 ± 6.9% of silver remaining) can cause higher silver leaching than batch test (85 ± 1.2% of silver remaining) in one-hour, and it can also cause both AgNP and Ag ions leaching from the membrane, which is closer to the leaching condition in the cross-flow test.
ContributorsHan, Bingru (Author) / Westerhoff, Paul (Thesis advisor) / Perreault, Francois (Committee member) / Sinha, Shahnawaz (Committee member) / Arizona State University (Publisher)
Created2017
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Description
The volume of end-of-life photovoltaic (PV) modules is increasing as the global PV market increases, and the global PV waste streams are expected to reach 250,000 metric tons by the end of 2020. If the recycling processes are not in place, there would be 60 million tons of end-of-life PV

The volume of end-of-life photovoltaic (PV) modules is increasing as the global PV market increases, and the global PV waste streams are expected to reach 250,000 metric tons by the end of 2020. If the recycling processes are not in place, there would be 60 million tons of end-of-life PV modules lying in the landfills by 2050, that may not become a not-so-sustainable way of sourcing energy since all PV modules could contain certain amount of toxic substances. Currently in the United States, PV modules are categorized as general waste and can be disposed in landfills. However, potential leaching of toxic chemicals and materials, if any, from broken end-of-life modules may pose health or environmental risks. There is no standard procedure to remove samples from PV modules for chemical toxicity testing in the Toxicity Characteristic Leaching Procedure (TCLP) laboratories as per EPA 1311 standard. The main objective of this thesis is to develop an unbiased sampling approach for the TCLP testing of PV modules. The TCLP testing was concentrated only for the laminate part of the modules, as they are already existing recycling technologies for the frame and junction box components of PV modules. Four different sample removal methods have been applied to the laminates of five different module manufacturers: coring approach, cell-cut approach, strip-cut approach, and hybrid approach. These removed samples were sent to two different TCLP laboratories, and TCLP results were tested for repeatability within a lab and reproducibility between the labs. The pros and cons of each sample removal method have been explored and the influence of sample removal methods on the variability of TCLP results has been discussed. To reduce the variability of TCLP results to an acceptable level, additional improvements in the coring approach, the best of the four tested options, are still needed.
ContributorsLeslie, Joswin (Author) / Tamizhmani, Govindasamy (Thesis advisor) / Srinivasan, Devarajan (Committee member) / Kuitche, Joseph (Committee member) / Arizona State University (Publisher)
Created2018
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Description
As the photovoltaic (PV) power plants age in the field, the PV modules degrade and generate visible and invisible defects. A defect and statistical degradation rate analysis of photovoltaic (PV) power plants is presented in two-part thesis. The first part of the thesis deals with the defect analysis and the

As the photovoltaic (PV) power plants age in the field, the PV modules degrade and generate visible and invisible defects. A defect and statistical degradation rate analysis of photovoltaic (PV) power plants is presented in two-part thesis. The first part of the thesis deals with the defect analysis and the second part of the thesis deals with the statistical degradation rate analysis. In the first part, a detailed analysis on the performance or financial risk related to each defect found in multiple PV power plants across various climatic regions of the USA is presented by assigning a risk priority number (RPN). The RPN for all the defects in each PV plant is determined based on two databases: degradation rate database; defect rate database. In this analysis it is determined that the RPN for each plant is dictated by the technology type (crystalline silicon or thin-film), climate and age. The PV modules aging between 3 and 19 years in four different climates of hot-dry, hot-humid, cold-dry and temperate are investigated in this study.

In the second part, a statistical degradation analysis is performed to determine if the degradation rates are linear or not in the power plants exposed in a hot-dry climate for the crystalline silicon technologies. This linearity degradation analysis is performed using the data obtained through two methods: current-voltage method; metered kWh method. For the current-voltage method, the annual power degradation data of hundreds of individual modules in six crystalline silicon power plants of different ages is used. For the metered kWh method, a residual plot analysis using Winters’ statistical method is performed for two crystalline silicon plants of different ages. The metered kWh data typically consists of the signal and noise components. Smoothers remove the noise component from the data by taking the average of the current and the previous observations. Once this is done, a residual plot analysis of the error component is performed to determine the noise was successfully separated from the data by proving the noise is random.
ContributorsSundarajan, Prasanna (Author) / Tamizhmani, Govindasamy (Thesis advisor) / Rogers, Bradley (Committee member) / Srinivasan, Devarajan (Committee member) / Arizona State University (Publisher)
Created2016
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Description
This is a two-part thesis:

Part 1 characterizes soiling losses using various techniques to understand the effect of soiling on photovoltaic modules. The higher the angle of incidence (AOI), the lower will be the photovoltaic (PV) module performance. Our research group has already reported the AOI investigation for cleaned modules

This is a two-part thesis:

Part 1 characterizes soiling losses using various techniques to understand the effect of soiling on photovoltaic modules. The higher the angle of incidence (AOI), the lower will be the photovoltaic (PV) module performance. Our research group has already reported the AOI investigation for cleaned modules of five different technologies with air/glass interface. However, the modules that are installed in the field would invariably develop a soil layer with varying thickness depending on the site condition, rainfall and tilt angle. The soiled module will have the air/soil/glass interface rather than air/glass interface. This study investigates the AOI variations on soiled modules of five different PV technologies. It is demonstrated that AOI effect is inversely proportional to the soil density. In other words, the power or current loss between clean and soiled modules would be much higher at a higher AOI than at a lower AOI leading to excessive energy production loss of soiled modules on cloudy days, early morning hours and late afternoon hours. Similarly, the spectral influence of soil on the performance of the module was investigated through reflectance and transmittance measurements. It was observed that the reflectance and transmittances losses vary linearly with soil density variation and the 600-700 nm band was identified as an ideal band for soil density measurements.

Part 2 of this thesis performs statistical risk analysis for a power plant through FMECA (Failure Mode, Effect, and Criticality Analysis) based on non-destructive field techniques and count data of the failure modes. Risk Priority Number is used for the grading guideline for criticality analysis. The analysis was done on a 19-year-old power plant in cold-dry climate to identify the most dominant failure and degradation modes. In addition, a comparison study was done on the current power plant (framed) along with another 18-year-old (frameless) from the same climate zone to understand the failure modes for cold-dry climatic condition.
ContributorsBoppana, Sravanthi (Author) / Tamizhmani, Govindasamy (Thesis advisor) / Srinivasan, Devarajan (Committee member) / Rogers, Bradley (Committee member) / Arizona State University (Publisher)
Created2015