Controlling electronic and magnetic properties of ultra narrow multilayered nanowires

Interest in the study of magnetic/non-magnetic multilayered structures took a giant leap since Grünberg and his group established that the interlayer exchange coupling (IEC) is a function of the non-magnetic spacer width. This interest was further fuelled by the discovery of the phenomenal Giant Magnetoresistance (GMR) effect. In fact, in 2007 Albert Fert and Peter Grünberg were awarded the Nobel Prize in Physics for their contribution to the discovery of GMR. GMR is the key property that is being used in the read-head of the present day computer hard drive as it requires a high sensitivity in the detection of magnetic field. The recent increase in demand for device miniaturization encouraged researchers to look for GMR in nanoscale multilayered structures. In this context, one dimensional(1-D) multilayerd nanowire structure has shown tremendous promise as a viable candidate for ultra sensitive read head sensors. In fact, the phenomenal giant magnetoresistance(GMR) effect, which is the novel feature of the currently used multilayered thin film, has already been observed in multilayered nanowire systems at ambient temperature. Geometrical confinement of the supper lattice along the 2-dimensions (2-D) to construct the 1-D multilayered nanowire prohibits the minimization of magnetic interaction- offering a rich variety of magnetic properties in nanowire that can be exploited for novel functionality. In addition, introduction of non-magnetic spacer between the magnetic layers presents additional advantage in controlling magnetic properties via tuning the interlayer magnetic interaction. Despite of a large volume of theoretical works devoted towards the understanding of GMR and IEC in super lattice structures, limited theoretical calculations are reported in 1-D multilayered systems. Thus to gauge their potential application in new generation magneto-electronic devices, in this thesis, I have discussed the usage of first principles density functional theory (DFT) in predicting the equilibrium structure, stability as well as electronic and magnetic properties of one dimensional multilayered nanowires. Particularly, I have focused on the electronic and magnetic properties of Fe/Pt multilayered nanowire structures and the role of non-magnetic Pt spacer in modulating the magnetic properties of the wire. It is found that the average magnetic moment per atom in the nanowire increases monotonically with an ~1/(N(Fe)) dependance, where N(Fe) is the number of iron layers in the nanowire. A simple model based upon the interfacial structure is given to explain the 1/(N(Fe)) trend in magnetic moment obtained from the first principle calculations. A new mechanism, based upon spin flip with in the layer and multistep electron transfer between the layers, is proposed to elucidate the enhancement of magnetic moment of Iron atom at the Platinum interface. The calculated IEC in the Fe/Pt multilayered nanowire is found to switch sign as the width of the non-magnetic spacer varies. The competition among short and long range direct exchange and the super exchange has been found to play a key role for the non-monotonous sign in IEC depending upon the width of the Platinum spacer layer. The calculated magnetoresistance from Julliere's model also exhibit similar switching behavior as that of IEC. The universality of the behavior of exchange coupling has also been looked into by introducing different non-magnetic spacers like Palladium, Copper, Silver, and Gold in between magnetic Iron layers. The nature of hybridization between Fe and other non-magnetic spacer is found to dictate the inter layer magnetic interaction. For example, in Fe/Pd nanowire the d-p hybridization in two spacer layer case favors anti-ferromagnetic (AFM) configuration over ferromagnetic (FM) configuration. However, the hybridization between half-filled Fe(d) and filled Cu(p) state in Fe/Cu nanowire favors FM coupling in the 2-spacer system.

IDENTIFICATION OF GENES CONTROLLING BIOLOGICAL PROCESSES AND PATHWAYS THROUGH STATISTICAL ANALYSIS AND NETWORK RECONSTRUCTION

The developmental processes and functions of an organism are controlled by the genes and the proteins that are derived from these genes. The identification of key genes and the reconstruction of gene networks can provide a model to help us understand the regulatory mechanisms for the initiation and progression of biological processes or functional abnormalities (e.g. diseases) in living organisms. In this dissertation, I have developed statistical methods to identify the genes and transcription factors (TFs) involved in biological processes, constructed their regulatory networks, and also evaluated some existing association methods to find robust methods for coexpression analyses. Two kinds of data sets were used for this work: genotype data and gene expression microarray data. On the basis of these data sets, this dissertation has two major parts, together forming six chapters. The first part deals with developing association methods for rare variants using genotype data (chapter 4 and 5). The second part deals with developing and/or evaluating statistical methods to identify genes and TFs involved in biological processes, and construction of their regulatory networks using gene expression data (chapter 2, 3, and 6). For the first part, I have developed two methods to find the groupwise association of rare variants with given diseases or traits. The first method is based on kernel machine learning and can be applied to both quantitative as well as qualitative traits. Simulation results showed that the proposed method has improved power over the existing weighted sum method (WS) in most settings. The second method uses multiple phenotypes to select a few top significant genes. It then finds the association of each gene with each phenotype while controlling the population stratification by adjusting the data for ancestry using principal components. This method was applied to GAW 17 data and was able to find several disease risk genes. For the second part, I have worked on three problems. First problem involved evaluation of eight gene association methods. A very comprehensive comparison of these methods with further analysis clearly demonstrates the distinct and common performance of these eight gene association methods. For the second problem, an algorithm named the bottom-up graphical Gaussian model was developed to identify the TFs that regulate pathway genes and reconstruct their hierarchical regulatory networks. This algorithm has produced very significant results and it is the first report to produce such hierarchical networks for these pathways. The third problem dealt with developing another algorithm called the top-down graphical Gaussian model that identifies the network governed by a specific TF. The network produced by the algorithm is proven to be of very high accuracy.

Functional ZnO nanostructures for electronic and energy applications

ZnO has proven to be a multifunctional material with important nanotechnological applications. ZnO nanostructures can be grown in various forms such as nanowires, nanorods, nanobelts, nanocombs etc. In this work, ZnO nanostructures are grown in a double quartz tube configuration thermal Chemical Vapor Deposition (CVD) system. We focus on functionalized ZnO Nanostructures by controlling their structures and tuning their properties for various applications. The following topics have been investigated: 1. We have fabricated various ZnO nanostructures using a thermal CVD technique. The growth parameters were optimized and studied for different nanostructures. 2. We have studied the application of ZnO nanowires (ZnONWs) for field effect transistors (FETs). Unintentional n-type conductivity was observed in our FETs based on as-grown ZnO NWs. We have then shown for the first time that controlled incorporation of hydrogen into ZnO NWs can introduce p-type characters to the nanowires. We further found that the n-type behaviors remained, leading to the ambipolar behaviors of hydrogen incorporated ZnO NWs. Importantly, the detected p- and n- type behaviors are stable for longer than two years when devices were kept in ambient conditions. All these can be explained by an ab initio model of Zn vacancy-Hydrogen complexes, which can serve as the donor, acceptors, or green photoluminescence quencher, depend on the number of hydrogen atoms involved. 3. Next ZnONWs were tested for electron field emission. We focus on reducing the threshold field (Eth) of field emission from non-aligned ZnO NWs. As encouraged by our results on enhancing the conductivity of ZnO NWs by hydrogen annealing described in Chapter 3, we have studied the effect of hydrogen annealing for improving field emission behavior of our ZnO NWs. We found that optimally annealed ZnO NWs offered much lower threshold electric field and improved emission stability. We also studied field emission from ZnO NWs at moderate vacuum levels. We found that there exists a minimum Eth as we scale the threshold field with pressure. This behavior is explained by referring to Paschen’s law. 4. We have studied the application of ZnO nanostructures for solar energy harvesting. First, as-grown and (CdSe) ZnS QDs decorated ZnO NBs and ZnONWs were tested for photocurrent generation. All these nanostructures offered fast response time to solar radiation. The decoration of QDs decreases the stable current level produced by ZnONWs but increases that generated by NBs. It is possible that NBs offer more stable surfaces for the attachment of QDs. In addition, our results suggests that performance degradation of solar cells made by growing ZnO NWs on ITO is due to the increase in resistance of ITO after the high temperature growth process. Hydrogen annealing also improve the efficiency of the solar cells by decreasing the resistance of ITO. Due to the issues on ITO, we use Ni foil as the growth substrates. Performance of solar cells made by growing ZnO NWs on Ni foils degraded after Hydrogen annealing at both low (300 °C) and high (600 °C) temperatures since annealing passivates native defects in ZnONWs and thus reduce the absorption of visible spectra from our solar simulator. Decoration of QDs improves the efficiency of such solar cells by increasing absorption of light in the visible region. Using a better electrolyte than phosphate buffer solution (PBS) such as KI also improves the solar cell efficiency. 5. Finally, we have attempted p-type doping of ZnO NWs using various growth precursors including phosphorus pentoxide, sodium fluoride, and zinc fluoride. We have also attempted to create p-type carriers via introducing interstitial fluorine by annealing ZnO nanostructures in diluted fluorine gas. In brief, we are unable to reproduce the growth of reported p-type ZnO nanostructures. However; we have identified the window of temperature and duration of post-growth annealing of ZnO NWs in dilute fluorine gas which leads to suppression of native defects. This is the first experimental effort on post-growth annealing of ZnO NWs in dilute fluorine gas although this has been suggested by a recent theory for creating p-type semiconductors. In our experiments the defect band peak due to native defects is found to decrease by annealing at 300 °C for 10 – 30 minutes. One of the major future works will be to determine the type of charge carriers in our annealed ZnONWs.

UNDERSTANDING PEOPLE'S ADOPTION OF INDIVIDUAL-USE RENEWABLE ENERGY TECHNOLOGY

This thesis attempts to understand why people adopt or reject individual-use renewable energy technologies (IURET). I used factors from Everett Rogers' Diffusion of Innovation Theory to understand how people's perceptions towards the characteristics of a given IURET (such as price, compatibility, complexity, etc.), the characteristics of the individual adopter (such as innovativeness and environmental awareness), and the communication network (inter-personal communications and mass media) can influence adoption. An online questionnaire was sent to 101randomly selected Michigan households (using random digit dialing) to ask people whether or not they had adopted at least one IURET and to assess the above-mentioned factors from Rogers' theory. Data analysis was then conducted in SPSS using Chi-squared and binary logistic regression to determine the relationship between adoption behaviors (the dependent variable) and the factors from Rogers' theory (the independent variables) while controlling for education. The results show that Rogers' factors of price and observability and the control variable of education were all significant in explaining adoption but the other factors of Rogers' theory were not. For example, if individuals perceive the price of IURET to be reasonable or if they observe their neighbors using these technologies, then they are more likely to adopt. These results indicate that, if we want to promote greater adoption of IURET, we should focus our efforts on making the price of IURET more affordable through incentives and other mechanisms. Adopters should also be given some form of reward if they provide free demonstrations of their IURET in use to their neighbors to take advantage of the observability effects.