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Description
Photosynthesis, one of the most important processes in nature, has provided an energy basis for nearly all life on Earth, as well as the fossil fuels we use today to power modern society. This research aims to mimic the photosynthetic process of converting incident solar energy into chemical potential energy in the form of a fuel via systems capable of carrying out photo-induced electron transfer to drive the production of hydrogen from water. Herein is detailed progress in using photo-induced stepwise electron transfer to drive the oxidation of water and reduction of protons to hydrogen. In the design, use of more blue absorbing porphyrin dyes to generate high-potential intermediates for oxidizing water and more red absorbing phthalocyanine dyes for forming the low potential charge needed for the production of hydrogen have been utilized. For investigating water oxidation at the photoanode, high potential porphyrins such as, bis-pyridyl porphyrins and pentafluorophenyl porphyrins have been synthesized and experiments have aimed at the co-immobilization of this dye with an IrO2-nH2O catalyst on TiO2. To drive the cathodic reaction of the water splitting photoelectrochemical cell, utilization of silicon octabutoxy-phthalocyanines have been explored, as they offer good absorption in the red to near infrared, coupled with low potential photo-excited states. Axially and peripherally substituted phthalocyanines bearing carboxylic anchoring groups for the immobilization on semiconductors such as TiO2 has been investigated. Ultimately, this work should culminate in a photoelectrochemical cell capable of splitting water to oxygen and hydrogen with the only energy input from light. A series of perylene dyes bearing multiple semi-conducting metal oxide anchoring groups have been synthesized and studied. Results have shown interfacial electron transfer between these perylenes and TiO2 nanoparticles encapsulated within reverse micelles and naked nanoparticles. The binding process was followed by monitoring the hypsochromic shift of the dye absorption spectra over time. Photoinduced electron transfer from the singlet excited state of the perylenes to the TiO2 conduction band is indicated by emission quenching of the TiO2-bound form of the dyes and confirmed by transient absorption measurements of the radical cation of the dyes and free carriers (injected electrons) in the TiO2.
ContributorsBergkamp, Jesse J (Author) / Moore, Ana L (Thesis advisor) / Mariño-Ochoa, Ernesto (Thesis advisor) / Gust, Devens J (Committee member) / Gould, Ian (Committee member) / Arizona State University (Publisher)
Created2013
Description
Our research focuses on finding answers through decentralized search, for complex, imprecise queries (such as "Which is the best hair salon nearby?") in situations where there is a spatiotemporal constraint (say answer needs to be found within 15 minutes) associated with the query. In general, human networks are good in answering imprecise queries. We try to use the social network of a person to answer his query. Our research aims at designing a framework that exploits the user's social network in order to maximize the answers for a given query. Exploiting an user's social network has several challenges. The major challenge is that the user's immediate social circle may not possess the answer for the given query, and hence the framework designed needs to carry out the query diffusion process across the network. The next challenge involves in finding the right set of seeds to pass the query to in the user's social circle. One other challenge is to incentivize people in the social network to respond to the query and thereby maximize the quality and quantity of replies. Our proposed framework is a mobile application where an individual can either respond to the query or forward it to his friends. We simulated the query diffusion process in three types of graphs: Small World, Random and Preferential Attachment. Given a type of network and a particular query, we carried out the query diffusion by selecting seeds based on attributes of the seed. The main attributes are Topic relevance, Replying or Forwarding probability and Time to Respond. We found that there is a considerable increase in the number of replies attained, even without saturating the user's network, if we adopt an optimal seed selection process. We found the output of the optimal algorithm to be satisfactory as the number of replies received at the interrogator's end was close to three times the number of neighbors an interrogator has. We addressed the challenge of incentivizing people to respond by associating a particular amount of points for each query asked, and awarding the same to people involved in answering the query. Thus, we aim to design a mobile application based on our proposed framework so that it helps in maximizing the replies for the interrogator's query by diffusing the query across his/her social network.
ContributorsSwaminathan, Neelakantan (Author) / Sundaram, Hari (Thesis advisor) / Davulcu, Hasan (Thesis advisor) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2013
Description
Developing a system capable of using solar energy to drive the conversion of an abundant and available precursor to fuel would profoundly impact humanity's energy use and thereby the condition of the global ecosystem. Such is the goal of artificial photosynthesis: to convert water to hydrogen using solar radiation as the sole energy input and ideally do so with the use of low cost, abundant materials. Constructing photoelectrochemical cells incorporating photoanodes structurally reminiscent of those used in dye sensitized photovoltaic solar cells presents one approach to establishing an artificial photosynthetic system. The work presented herein describes the production, integration, and study of water oxidation catalysts, molecular dyes, and metal oxide based photoelectrodes carried out in the pursuit of developing solar water splitting systems.
ContributorsSherman, Benjamin D (Author) / Moore, Thomas (Thesis advisor) / Moore, Ana (Committee member) / Buttry, Daniel (Committee member) / Arizona State University (Publisher)
Created2013
Description
With the advent of social media (like Twitter, Facebook etc.,) people are easily sharing their opinions, sentiments and enforcing their ideologies on others like never before. Even people who are otherwise socially inactive would like to share their thoughts on current affairs by tweeting and sharing news feeds with their friends and acquaintances. In this thesis study, we chose Twitter as our main data platform to analyze shifts and movements of 27 political organizations in Indonesia. So far, we have collected over 30 million tweets and 150,000 news articles from RSS feeds of the corresponding organizations for our analysis. For Twitter data extraction, we developed a multi-threaded application which seamlessly extracts, cleans and stores millions of tweets matching our keywords from Twitter Streaming API. For keyword extraction, we used topics and perspectives which were extracted using n-grams techniques and later approved by our social scientists. After the data is extracted, we aggregate the tweet contents that belong to every user on a weekly basis. Finally, we applied linear and logistic regression using SLEP, an open source sparse learning package to compute weekly score for users and mapping them to one of the 27 organizations on a radical or counter radical scale. Since, we are mapping users to organizations on a weekly basis, we are able to track user's behavior and important new events that triggered shifts among users between organizations. This thesis study can further be extended to identify topics and organization specific influential users and new users from various social media platforms like Facebook, YouTube etc. can easily be mapped to existing organizations on a radical or counter-radical scale.
ContributorsPoornachandran, Sathishkumar (Author) / Davulcu, Hasan (Thesis advisor) / Sen, Arunabha (Committee member) / Woodward, Mark (Committee member) / Arizona State University (Publisher)
Created2013
Description
Statistics is taught at every level of education, yet teachers often have to assume their students have no knowledge of statistics and start from scratch each time they set out to teach statistics. The motivation for this experimental study comes from interest in exploring educational applications of augmented reality (AR) delivered via mobile technology that could potentially provide rich, contextualized learning for understanding concepts related to statistics education. This study examined the effects of AR experiences for learning basic statistical concepts. Using a 3 x 2 research design, this study compared learning gains of 252 undergraduate and graduate students from a pre- and posttest given before and after interacting with one of three types of augmented reality experiences, a high AR experience (interacting with three dimensional images coupled with movement through a physical space), a low AR experience (interacting with three dimensional images without movement), or no AR experience (two dimensional images without movement). Two levels of collaboration (pairs and no pairs) were also included. Additionally, student perceptions toward collaboration opportunities and engagement were compared across the six treatment conditions. Other demographic information collected included the students' previous statistics experience, as well as their comfort level in using mobile devices. The moderating variables included prior knowledge (high, average, and low) as measured by the student's pretest score. Taking into account prior knowledge, students with low prior knowledge assigned to either high or low AR experience had statistically significant higher learning gains than those assigned to a no AR experience. On the other hand, the results showed no statistical significance between students assigned to work individually versus in pairs. Students assigned to both high and low AR experience perceived a statistically significant higher level of engagement than their no AR counterparts. Students with low prior knowledge benefited the most from the high AR condition in learning gains. Overall, the AR application did well for providing a hands-on experience working with statistical data. Further research on AR and its relationship to spatial cognition, situated learning, high order skill development, performance support, and other classroom applications for learning is still needed.
ContributorsConley, Quincy (Author) / Atkinson, Robert K (Thesis advisor) / Nguyen, Frank (Committee member) / Nelson, Brian C (Committee member) / Arizona State University (Publisher)
Created2013
Description
The biological and chemical diversity of protein structure and function can be greatly expanded by position-specific incorporation of non-natural amino acids bearing a variety of functional groups. Non-cognate amino acids can be incorporated into proteins at specific sites by using orthogonal aminoacyl-tRNA synthetase/tRNA pairs in conjunction with nonsense, rare, or 4-bp codons. There has been considerable progress in developing new types of amino acids, in identifying novel methods of tRNA aminoacylation, and in expanding the genetic code to direct their position. Chemical aminoacylation of tRNAs is accomplished by acylation and ligation of a dinucleotide (pdCpA) to the 3'-terminus of truncated tRNA. This strategy allows the incorporation of a wide range of natural and unnatural amino acids into pre-determined sites, thereby facilitating the study of structure-function relationships in proteins and allowing the investigation of their biological, biochemical and biophysical properties. Described in Chapter 1 is the current methodology for synthesizing aminoacylated suppressor tRNAs. Aminoacylated suppressor tRNACUAs are typically prepared by linking pre-aminoacylated dinucleotides (aminoacyl-pdCpAs) to 74 nucleotide (nt) truncated tRNAs (tRNA-COH) via a T4 RNA ligase mediated reaction. Alternatively, there is another route outlined in Chapter 1 that utilizes a different pre-aminoacylated dinucleotide, AppA. This dinucleotide has been shown to be a suitable substrate for T4 RNA ligase mediated coupling with abbreviated tRNA-COHs for production of 76 nt aminoacyl-tRNACUAs. The synthesized suppressor tRNAs have been shown to participate in protein synthesis in vitro, in an S30 (E. coli) coupled transcription-translation system in which there is a UAG codon in the mRNA at the position corresponding to Val10. Chapter 2 describes the synthesis of two non-proteinogenic amino acids, L-thiothreonine and L-allo-thiothreonine, and their incorporation into predetermined positions of a catalytically competent dihydrofolate reductase (DHFR) analogue lacking cysteine. Here, the elaborated proteins were site-specifically derivitized with a fluorophore at the thiothreonine residue. The synthesis and incorporation of phosphorotyrosine derivatives into DHFR is illustrated in Chapter 3. Three different phosphorylated tyrosine derivatives were prepared: bis-nitrobenzylphosphoro-L-tyrosine, nitrobenzylphosphoro-L-tyrosine, and phosphoro-L-tyrosine. Their ability to participate in a protein synthesis system was also evaluated.
ContributorsNangreave, Ryan Christopher (Author) / Hecht, Sidney M. (Thesis advisor) / Yan, Hao (Committee member) / Gould, Ian (Committee member) / Arizona State University (Publisher)
Created2013
Description
The thesis studies new methods to fabricate optoelectronic Ge1-ySny/Si(100) alloys and investigate their photoluminescence (PL) properties for possible applications in Si-based photonics including IR lasers. The work initially investigated the origin of the difference between the PL spectrum of bulk Ge, dominated by indirect gap emission, and the PL spectrum of Ge-on-Si films, dominated by direct gap emission. It was found that the difference is due to the supression of self-absorption effects in Ge films, combined with a deviation from quasi-equilibrium conditions in the conduction band of undoped films. The latter is confirmed by a model suggesting that the deviation is caused by the shorter recombination lifetime in the films relative to bulk Ge. The knowledge acquired from this work was then utilized to study the PL properties of n-type Ge1-ySny/Si (y=0.004-0.04) samples grown via chemical vapor deposition of Ge2H6/SnD4/P(GeH3)3. It was found that the emission intensity (I) of these samples is at least 10x stronger than observed in un-doped counterparts and that the Idir/Iind ratio of direct over indirect gap emission increases for high-Sn contents due to the reduced gamma-L valley separation, as expected. Next the PL investigation was expanded to samples with y=0.05-0.09 grown via a new method using the more reactive Ge3H8 in place of Ge2H6. Optical quality, 1-um thick Ge1-ySny/Si(100) layers were produced using Ge3H10/SnD4 and found to exhibit strong, tunable PL near the threshold of the direct-indirect bandgap crossover. A byproduct of this study was the development of an enhanced process to produce Ge3H8, Ge4H10, and Ge5H12 analogs for application in ultra-low temperature deposition of Group-IV semiconductors. The thesis also studies synthesis routes of an entirely new class of semiconductor compounds and alloys described by Si5-2y(III-V)y (III=Al, V= As, P) comprising of specifically designed diamond-like structures based on a Si parent lattice incorporating isolated III-V units. The common theme of the two thesis topics is the development of new mono-crystalline materials on ubiquitous silicon platforms with the objective of enhancing the optoelectronic performance of Si and Ge semiconductors, potentially leading to the design of next generation optical devices including lasers, detectors and solar cells.
ContributorsGrzybowski, Gordon (Author) / Kouvetakis, John (Thesis advisor) / Chizmeshya, Andrew (Committee member) / Menéndez, Jose (Committee member) / Arizona State University (Publisher)
Created2013
Description
Automating aspects of biocuration through biomedical information extraction could significantly impact biomedical research by enabling greater biocuration throughput and improving the feasibility of a wider scope. An important step in biomedical information extraction systems is named entity recognition (NER), where mentions of entities such as proteins and diseases are located within natural-language text and their semantic type is determined. This step is critical for later tasks in an information extraction pipeline, including normalization and relationship extraction. BANNER is a benchmark biomedical NER system using linear-chain conditional random fields and the rich feature set approach. A case study with BANNER locating genes and proteins in biomedical literature is described. The first corpus for disease NER adequate for use as training data is introduced, and employed in a case study of disease NER. The first corpus locating adverse drug reactions (ADRs) in user posts to a health-related social website is also described, and a system to locate and identify ADRs in social media text is created and evaluated. The rich feature set approach to creating NER feature sets is argued to be subject to diminishing returns, implying that additional improvements may require more sophisticated methods for creating the feature set. This motivates the first application of multivariate feature selection with filters and false discovery rate analysis to biomedical NER, resulting in a feature set at least 3 orders of magnitude smaller than the set created by the rich feature set approach. Finally, two novel approaches to NER by modeling the semantics of token sequences are introduced. The first method focuses on the sequence content by using language models to determine whether a sequence resembles entries in a lexicon of entity names or text from an unlabeled corpus more closely. The second method models the distributional semantics of token sequences, determining the similarity between a potential mention and the token sequences from the training data by analyzing the contexts where each sequence appears in a large unlabeled corpus. The second method is shown to improve the performance of BANNER on multiple data sets.
ContributorsLeaman, James Robert (Author) / Gonzalez, Graciela (Thesis advisor) / Baral, Chitta (Thesis advisor) / Cohen, Kevin B (Committee member) / Liu, Huan (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Created2013
Description
Chemistry as a subject is difficult to learn and understand, due in part to the specific language used by practitioners in their professional and scientific communications. The language and ways of representing chemical interactions have been grouped into three modes of representation used by chemistry instructors, and ultimately by students in understanding the discipline. The first of these three modes of representation is the symbolic mode, which uses a standard set of rules for chemical nomenclature set out by the IUPAC. The second mode of representation is that of microscopic, which depicts chemical compounds as discrete units made up of atoms and molecules, with a particular ratio of atoms to a molecule or formula unit. The third mode of representation is macroscopic, what can be seen, experienced, or measured directly, like ice melting or a color change during a chemical reaction. Recent evidence suggests that chemistry instructors can assist their students in making the connections between the modes of representation by incorporating all three modes into their teaching and discussions, and overtly connecting the modes during instruction. In this research, chemistry teachers at the community college level were observed over the course of an entire semester, to evaluate their instructional use of mode of representation. The students of these teachers were tested prior to and after a semester's worth of instruction, and changes in the basic chemistry conceptual knowledge of these students were compared. Additionally, a subset of the overall population that was pre- and post-tested was interviewed at length using demonstrations of chemical phenomenon that students were asked to translate using all three modes of representation. Analysis of the instruction of three community college teachers shows there were significant differences among these teachers in their instructional use of mode of representation. Additionally, the students of these three teachers had differential and statistically significant achievement over the course of the semester. This research supports results of other similar studies, as well as providing some unexpected results from the students involved.
ContributorsWood, Lorelei (Author) / Baker, Dale (Thesis advisor) / Ganesh, Tirupalavanam G. (Committee member) / Colleen, Megowan (Committee member) / Sujatha, Krishnaswamy (Committee member) / Arizona State University (Publisher)
Created2013
Description
It is commonly known that High Performance Computing (HPC) systems are most frequently used by multiple users for batch job, parallel computations. Less well known, however, are the numerous HPC systems servicing data so sensitive that administrators enforce either a) sequential job processing - only one job at a time on the entire system, or b) physical separation - devoting an entire HPC system to a single project until recommissioned. The driving forces behind this type of security are numerous but share the common origin of data so sensitive that measures above and beyond industry standard are used to ensure information security. This paper presents a network security solution that provides information security above and beyond industry standard, yet still enabling multi-user computations on the system. This paper's main contribution is a mechanism designed to enforce high level time division multiplexing of network access (Time Division Multiple Access, or TDMA) according to security groups. By dividing network access into time windows, interactions between applications over the network can be prevented in an easily verifiable way.
ContributorsFerguson, Joshua (Author) / Gupta, Sandeep Ks (Thesis advisor) / Varsamopoulos, Georgios (Committee member) / Ball, George (Committee member) / Arizona State University (Publisher)
Created2013