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An eco-industrial park (EIP) is an industrial ecosystem in which a group of co-located firms are involved in collective resource optimization with each other and with the local community through physical exchanges of energy, water, materials, byproducts and services - referenced in the industrial ecology literature as "industrial symbiosis". EIPs,

An eco-industrial park (EIP) is an industrial ecosystem in which a group of co-located firms are involved in collective resource optimization with each other and with the local community through physical exchanges of energy, water, materials, byproducts and services - referenced in the industrial ecology literature as "industrial symbiosis". EIPs, when compared with standard industrial resource sharing networks, prove to be of greater public advantage as they offer improved environmental and economic benefits, and higher operational efficiencies both upstream and downstream in their supply chain.

Although there have been many attempts to adapt EIP methodology to existing industrial sharing networks, most of them have failed for various factors: geographic restrictions by governmental organizations on use of technology, cost of technology, the inability of industries to effectively communicate their upstream and downstream resource usage, and to diminishing natural resources such as water, land and non-renewable energy (NRE) sources for energy production.

This paper presents a feasibility study conducted to evaluate the comparative environmental, economic, and geographic impacts arising from the use of renewable energy (RE) and NRE to power EIPs. Life Cycle Assessment (LCA) methodology, which is used in a variety of sectors to evaluate the environmental merits and demerits of different kinds of products and processes, was employed for comparison between these two energy production methods based on factors such as greenhouse gas emission, acidification potential, eutrophication potential, human toxicity potential, fresh water usage and land usage. To complement the environmental LCA analysis, levelized cost of electricity was used to evaluate the economic impact. This model was analyzed for two different geographic locations; United States and Europe, for 12 different energy production technologies.

The outcome of this study points out the environmental, economic and geographic superiority of one energy source over the other, including the total carbon dioxide equivalent emissions, which can then be related to the total number of carbon credits that can be earned or used to mitigate the overall carbon emission and move closer towards a net zero carbon footprint goal thus making the EIPs truly sustainable.
ContributorsGupta, Vaibhav (Author) / Calhoun, Ronald J (Thesis advisor) / Dooley, Kevin (Committee member) / Phelan, Patrick (Committee member) / Arizona State University (Publisher)
Created2014
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Description
A method of determining nanoparticle temperature through fluorescence intensity levels is described. Intracellular processes are often tracked through the use of fluorescence tagging, and ideal temperatures for many of these processes are unknown. Through the use of fluorescence-based thermometry, cellular processes such as intracellular enzyme movement can be studied and

A method of determining nanoparticle temperature through fluorescence intensity levels is described. Intracellular processes are often tracked through the use of fluorescence tagging, and ideal temperatures for many of these processes are unknown. Through the use of fluorescence-based thermometry, cellular processes such as intracellular enzyme movement can be studied and their respective temperatures established simultaneously. Polystyrene and silica nanoparticles are synthesized with a variety of temperature-sensitive dyes such as BODIPY, rose Bengal, Rhodamine dyes 6G, 700, and 800, and Nile Blue A and Nile Red. Photographs are taken with a QImaging QM1 Questar EXi Retiga camera while particles are heated from 25 to 70 C and excited at 532 nm with a Coherent DPSS-532 laser. Photographs are converted to intensity images in MATLAB and analyzed for fluorescence intensity, and plots are generated in MATLAB to describe each dye's intensity vs temperature. Regression curves are created to describe change in fluorescence intensity over temperature. Dyes are compared as nanoparticle core material is varied. Large particles are also created to match the camera's optical resolution capabilities, and it is established that intensity values increase proportionally with nanoparticle size. Nile Red yielded the closest-fit model, with R2 values greater than 0.99 for a second-order polynomial fit. By contrast, Rhodamine 6G only yielded an R2 value of 0.88 for a third-order polynomial fit, making it the least reliable dye for temperature measurements using the polynomial model. Of particular interest in this work is Nile Blue A, whose fluorescence-temperature curve yielded a much different shape from the other dyes. It is recommended that future work describe a broader range of dyes and nanoparticle sizes, and use multiple excitation wavelengths to better quantify each dye's quantum efficiency. Further research into the effects of nanoparticle size on fluorescence intensity levels should be considered as the particles used here greatly exceed 2 ìm. In addition, Nile Blue A should be further investigated as to why its fluorescence-temperature curve did not take on a characteristic shape for a temperature-sensitive dye in these experiments.
ContributorsTomforde, Christine (Author) / Phelan, Patrick (Thesis advisor) / Dai, Lenore (Committee member) / Adrian, Ronald (Committee member) / Arizona State University (Publisher)
Created2011
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Description
Nanoparticles are ubiquitous in various fields due to their unique properties not seen in similar bulk materials. Among them, core-shell composite nanoparticles are an important class of materials which are attractive for their applications in catalysis, sensing, electromagnetic shielding, drug delivery, and environmental remediation. This dissertation focuses on the study

Nanoparticles are ubiquitous in various fields due to their unique properties not seen in similar bulk materials. Among them, core-shell composite nanoparticles are an important class of materials which are attractive for their applications in catalysis, sensing, electromagnetic shielding, drug delivery, and environmental remediation. This dissertation focuses on the study of core-shell type of nanoparticles where a polymer serves as the core and inorganic nanoparticles are the shell. This is an interesting class of supramolecular building blocks and can "exhibit unusual, possibly unique, properties which cannot be obtained simply by co-mixing polymer and inorganic particles". The one-step Pickering emulsion polymerization method was successfully developed and applied to synthesize polystyrene-silica core-shell composite particles. Possible mechanisms of the Pickering emulsion polymerization were also explored. The silica nanoparticles were thermodynamically favorable to self-assemble at liquid-liquid interfaces at the initial stage of polymerization and remained at the interface to finally form the shells of the composite particles. More importantly, Pickering emulsion polymerization was employed to synthesize polystyrene/poly(N-isopropylacrylamide) (PNIPAAm)-silica core-shell nanoparticles with N-isopropylacrylamide incorporated into the core as a co-monomer. The composite nanoparticles were temperature sensitive and could be up-taken by human prostate cancer cells and demonstrated effectiveness in drug delivery and cancer therapy. Similarly, by incorporating poly-2-(N,N)-dimethylamino)ethyl methacrylate (PDMA) into the core, pH sensitive core-shell composite nanoparticles were synthesized and applied as effective carriers to release a rheological modifier upon a pH change. Finally, the research focuses on facile approaches to engineer the transition of the temperature-sensitive particles and develop composite core-shell nanoparticles with a metallic shell.
ContributorsSanyal, Sriya (Author) / Dai, Lenore L. (Thesis advisor) / Jiang, Hanqing (Committee member) / Lind, Mary L. (Committee member) / Phelan, Patrick (Committee member) / Rege, Kaushal (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Many expect renewable energy technologies to play a leading role in a sustainable energy supply system and to aid the shift away from an over-reliance on traditional hydrocarbon resources in the next few decades. This dissertation develops environmental, policy and social models to help understand various aspects of photovoltaic (PV)

Many expect renewable energy technologies to play a leading role in a sustainable energy supply system and to aid the shift away from an over-reliance on traditional hydrocarbon resources in the next few decades. This dissertation develops environmental, policy and social models to help understand various aspects of photovoltaic (PV) technologies. The first part of this dissertation advances the life cycle assessment (LCA) of PV systems by expanding the boundary of included processes using hybrid LCA and accounting for the technology-driven dynamics of environmental impacts. Hybrid LCA extends the traditional method combining bottom-up process-sum and top-down economic input-output (EIO) approaches. The embodied energy and carbon of multi-crystalline silicon photovoltaic systems are assessed using hybrid LCA. From 2001 to 2010, the embodied energy and carbon fell substantially, indicating that technological progress is realizing reductions in environmental impacts in addition to lower module price. A variety of policies support renewable energy adoption, and it is critical to make them function cooperatively. To reveal the interrelationships among these policies, the second part of this dissertation proposes three tiers of policy architecture. This study develops a model to determine the specific subsidies required to support a Renewable Portfolio Standard (RPS) goal. The financial requirements are calculated (in two scenarios) and compared with predictable funds from public sources. A main result is that the expected investments to achieve the RPS goal far exceed the economic allocation for subsidy of distributed PV. Even with subsidies there are often challenges with social acceptance. The third part of this dissertation originally develops a fuzzy logic inference model to relate consumers' attitudes about the technology such as perceived cost, maintenance, and environmental concern to their adoption intention. Fuzzy logic inference model is a type of soft computing models. It has the advantage of dealing with imprecise and insufficient information and mimicking reasoning processes of human brains. This model is implemented in a case study of residential PV adoption using data through a survey of homeowners in Arizona. The output of this model is the purchasing probability of PV.
ContributorsZhai, Pei (Author) / Williams, Eric D. (Thesis advisor) / Allenby, Braden (Committee member) / Phelan, Patrick (Committee member) / Arizona State University (Publisher)
Created2010
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Description
Neurological disorders are difficult to treat with current drug delivery methods due to their inefficiency and the lack of knowledge of the mechanisms behind drug delivery across the blood brain barrier (BBB). Nanoparticles (NPs) are a promising drug delivery method due to their biocompatibility and ability to be modified by

Neurological disorders are difficult to treat with current drug delivery methods due to their inefficiency and the lack of knowledge of the mechanisms behind drug delivery across the blood brain barrier (BBB). Nanoparticles (NPs) are a promising drug delivery method due to their biocompatibility and ability to be modified by cell penetrating peptides, such as transactivating transciptor (TAT) peptide, which has been shown to increase efficiency of delivery. There are multiple proposed mechanisms of TAT-mediated delivery that also have size restrictions on the molecules that can undergo each BBB crossing mechanism. The effect of nanoparticle size on TAT-mediated delivery in vivo is an important aspect to research in order to better understand the delivery mechanisms and to create more efficient NPs. NPs called FluoSpheres are used because they come in defined diameters unlike polymeric NPs that have a broad distribution of diameters. Both modified and unmodified 100nm and 200nm NPs were able to bypass the BBB and were seen in the brain, spinal cord, liver, and spleen using confocal microscopy and a biodistribution study. Statistically significant differences in delivery rate of the different sized NPs or between TAT-modified and unmodified NPs were not found. Therefore in future work a larger range of diameter size will be evaluated. Also the unmodified NPs will be conjugated with scrambled peptide to ensure that both unmodified and TAT-modified NPs are prepared in identical fashion to better understand the role of size on TAT targeting. Although all the NPs were able to bypass the BBB, future work will hopefully provide a better representation of how NP size effects the rate of TAT-mediated delivery to the CNS.
ContributorsCeton, Ricki Ronea (Author) / Stabenfeldt, Sarah (Thesis director) / Sirianni, Rachael (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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Description
Concentrating solar thermal power systems gained a wide interest for a long time to serve as a renewable and sustainable alternate source of energy. While the optimization and modification are ongoing, focused generally on solar power systems to provide solar-electrical energy or solar-thermal energy, the production process of Ordinary Portland

Concentrating solar thermal power systems gained a wide interest for a long time to serve as a renewable and sustainable alternate source of energy. While the optimization and modification are ongoing, focused generally on solar power systems to provide solar-electrical energy or solar-thermal energy, the production process of Ordinary Portland Cement (OPC) has not changed over the past century. A linear refractive Fresnel lens application in cement production process is investigated in this research to provide the thermal power required to raise the temperature of lime up to 623 K (350C) with zero carbon emissions for stage two in a new proposed two-stage production process. The location is considered to be Phoenix, Arizona, with a linear refractive Fresnel lens facing south, tilted 33.45 equaling the location latitude, and concentrating solar beam radiation on an evacuated tube collector with tracking system continuously rotating about the north-south axis. The mathematical analysis showed promising results based on averaged monthly values representing an average hourly useful thermal power and receiver temperature during day-light hours for each month throughout the year. The maximum average hourly useful thermal power throughout the year was obtained for June as 33 kWth m-2 with a maximum receiver temperature achieved of 786 K (513C), and the minimum useful thermal power obtained during the month of December with 27 kWth m-2 and a minimum receiver temperature of 701 K (428C).
ContributorsAlkhuwaiteem, Mohammad (Author) / Phelan, Patrick (Thesis advisor) / Shuaib, Abdelrahman (Committee member) / Neithalath, Narayanan (Committee member) / Arizona State University (Publisher)
Created2021
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Description
Ensuring that people across the globe have enough water and electricity are two large issues that continue to grow. This study performs a test on whether using solar photovoltaic modules to shade water can potentially help diminish the issues of water and power. Using the setup of a

Ensuring that people across the globe have enough water and electricity are two large issues that continue to grow. This study performs a test on whether using solar photovoltaic modules to shade water can potentially help diminish the issues of water and power. Using the setup of a PV module shading water, a stand-alone PV module, and unshaded water, it was found that shading water can reduce evaporation and lower PV module operating temperature at the same time. Using averaged data from two days of testing, the volume per unit surface area of water that evaporated per hour was 0.319 cm3/cm2 less for the shaded water compared to the unshaded water. The evaporation rates found in the experiment are compared to those of Lake Mead to see the amount of water lost on a large scale. For the operating temperature of the PV module, the module used for shading had a consistently lower temperature than the stand-alone module. On the first day, the shading module had an average temperature 5.1 C lower than the stand-alone module average temperature. On day two, the shading module had an average temperature 3.4 C lower than the stand-alone module average temperature. Using average temperatures between the two days from 10:30am and 4:45pm, the average daily temperature of the panel used for shading was 4.5C less than the temperature of the stand-alone panel. These results prove water shading by solar PV modules to be effective in reducing evaporation and lowering module operating temperature. Last, suggestions for future studies are discussed, such as performance analysis of the PV modules in this setting, economic analysis of using PV modules as shading, and the isolation of the different factors of evaporation (temperature, wind speed, and humidity).
ContributorsLee, John C (Author) / Phelan, Patrick (Thesis director) / Roedel, Ronald (Committee member) / Dean, W.P. Carey School of Business (Contributor) / Mechanical and Aerospace Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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Description
The applications utilizing nanoparticles have grown in both industrial and academic areas because of the very large surface area to volume ratios of these particles. One of the best ways to process and control these nanoparticles is fluidization. In this work, a new microjet and vibration assisted (MVA) fluidized bed

The applications utilizing nanoparticles have grown in both industrial and academic areas because of the very large surface area to volume ratios of these particles. One of the best ways to process and control these nanoparticles is fluidization. In this work, a new microjet and vibration assisted (MVA) fluidized bed system was developed in order to fluidize nanoparticles. The system was tested and the parameters optimized using two commercially available TiO2 nanoparticles: P25 and P90. The fluidization quality was assessed by determining the non-dimensional bed height as well as the non-dimensional pressure drop. The non-dimensional bed height for the nanosized TiO2 in the MVA system optimized at about 5 and 7 for P25 and P90 TiO2, respectively, at a resonance frequency of 50 Hz. The non-dimensional pressure drop was also determined and showed that the MVA system exhibited a lower minimum fluidization velocity for both of the TiO2 types as compared to fluidization that employed only vibration assistance. Additional experiments were performed with the MVA to characterize the synergistic effects of vibrational intensity and gas velocity on the TiO2 P25 and P90 fluidized bed heights. Mathematical relationships were developed to correlate vibrational intensity, gas velocity, and fluidized bed height in the MVA. The non-dimensional bed height in the MVA system is comparable to previously published P25 TiO2 fluidization work that employed an alcohol in order to minimize the electrostatic attractions within the bed. However, the MVA system achieved similar results without the addition of a chemical, thereby expanding the potential chemical reaction engineering and environmental remediation opportunities for fluidized nanoparticle systems.

In order to aid future scaling up of the MVA process, the agglomerate size distribution in the MVA system was predicted by utilizing a force balance model coupled with a two-fluid model (TFM) simulation. The particle agglomerate size that was predicted using the computer simulation was validated with experimental data and found to be in good agreement.

Lastly, in order to demonstrate the utility of the MVA system in an air revitalization application, the capture of CO2 was examined. CO2 breakthrough time and adsorption capacities were tested in the MVA system and compared to a vibrating fluidized bed (VFB) system. Experimental results showed that the improved fluidity in the MVA system enhanced CO2 adsorption capacity.
ContributorsAn, Keju (Author) / Andino, Jean (Thesis advisor) / Phelan, Patrick (Thesis advisor) / Adrian, Ronald (Committee member) / Emady, Heather (Committee member) / Kasbaoui, Mohamed (Committee member) / Arizona State University (Publisher)
Created2019
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Description
The operating temperature of photovoltaic (PV) modules has a strong impact on the expected performance of said modules in photovoltaic arrays. As the install capacity of PV arrays grows throughout the world, improved accuracy in modeling of the expected module temperature, particularly at finer time scales, requires improvements in the

The operating temperature of photovoltaic (PV) modules has a strong impact on the expected performance of said modules in photovoltaic arrays. As the install capacity of PV arrays grows throughout the world, improved accuracy in modeling of the expected module temperature, particularly at finer time scales, requires improvements in the existing photovoltaic temperature models. This thesis work details the investigation, motivation, development, validation, and implementation of a transient photovoltaic module temperature model based on a weighted moving-average of steady-state temperature predictions.

This thesis work first details the literature review of steady-state and transient models that are commonly used by PV investigators in performance modeling. Attempts to develop models capable of accounting for the inherent transient thermal behavior of PV modules are shown to improve on the accuracy of the steady-state models while also significantly increasing the computational complexity and the number of input parameters needed to perform the model calculations.

The transient thermal model development presented in this thesis begins with an investigation of module thermal behavior performed through finite-element analysis (FEA) in a computer-aided design (CAD) software package. This FEA was used to discover trends in transient thermal behavior for a representative PV module in a timely manner. The FEA simulations were based on heat transfer principles and were validated against steady-state temperature model predictions. The dynamic thermal behavior of PV modules was determined to be exponential, with the shape of the exponential being dependent on the wind speed and mass per unit area of the module.

The results and subsequent discussion provided in this thesis link the thermal behavior observed in the FEA simulations to existing steady-state temperature models in order to create an exponential weighting function. This function can perform a weighted average of steady-state temperature predictions within 20 minutes of the time in question to generate a module temperature prediction that accounts for the inherent thermal mass of the module while requiring only simple input parameters. Validation of the modeling method presented here shows performance modeling accuracy improvement of 0.58%, or 1.45°C, over performance models relying on steady-state models at narrow data intervals.
ContributorsPrilliman, Matthew (Author) / Tamizhmani, Govindasamy (Thesis advisor) / Phelan, Patrick (Thesis advisor) / Wang, Liping (Committee member) / Arizona State University (Publisher)
Created2020