Charge and spin transport in nanoscale junction from first principles

Recently nanoscale junctions consisting of 0-D nanostructures (single molecule) or 1-D nanostructures (semiconducting nanowire) sandwiched between two metal electrodes are successfully fabricated and characterized. What lacks in the recent developments is the understanding of the mechanism behind the observed phenomena at the level of atoms and electrons. For example, the origin of observed switching effect in a semiconducting nanowire due to the influence of an external gate bias is not yet understood at the electronic structure level. On the same context, different experimental groups have reported different signs in tunneling magneto-resistance for the same organic spin valve structure, which has baffled researchers working in this field. In this thesis, we present the answers to some of these subtle questions by investigating the charge and spin transport in different nanoscale junctions. A parameter-free, single particle Green’s function approach in conjunction with a posteriori density functional theory (DFT) involving a hybrid orbital dependent functional is used to calculate the tunneling current in the coherent transport limit. The effect of spin polarization is explicitly incorporated to investigate spin transport in a nanoscale junction. Through the electron transport studies in PbS nanowire junction, a new orbital controlled mechanism behind the switching of the current is proposed. It can explain the switching behavior, not only in PbS nanowire, but in other lead-chalcogenide nanowires as well. Beside this, the electronic structure properties of this nanowire are studied using periodic DFT. The quantum confinement effect was investigated by calculating the bandgap of PbS nanowires with different diameters. Subsequently, we explain an observed semiconducting to metallic phase transition of this nanowire by calculating the bandgap of the nanowire under uniform radial strain. The compressive radial strain on the nanowire was found to be responsible for the metallic to semiconducting phase transition. Apart from studying one dimensional nanostructure, we also present transport properties in zero dimensional single molecular junctions. We proposed a new codoping approach in a single molecular carborane junction, where a cation and an anion are simultaneously doped to find the role of a single atom in the device. The main purpose was to build a molecular junction where a single atom can dictate the flow of electrons in a circuit. Recent observations of both positive and negative sign in tunneling magnetoresistance (TMR) the using same organic spin-valve structure hasmystified researchers. From our spin dependent transport studies in a prototypical organic molecular tunneling device, we found that a 3% change in metal-molecule interfacial distance can alter the sign of TMR. Changing the interfacial distance by 3%, the number of participating eigenstates as well as their orbital characteristic changes for anti-parallel configuration of the magnetization at the two electrodes, leading to the sign reversal of the TMR. Apart from this, the magnetic proximity effect under applied bias is investigated quantitatively, which can be used to understand the observed unexpectedmagnetismin carbon basedmaterials when they are in close proximity with magnetic substrates.

Electron transport in molecular systems

The remarkable advances in nanoscience and nanotechnology over the last two decades allow one to manipulate individuals atoms, molecules and nanostructures, make it possible to build devices with only a few nanometers, and enhance the nano-bio fusion in tackling biological and medical problems. It complies with the ever-increasing need for device miniaturization, from magnetic storage devices, electronic building blocks for computers, to chemical and biological sensors. Despite the continuing efforts based on conventional methods, they are likely to reach the fundamental limit of miniaturization in the next decade, when feature lengths shrink below 100 nm. On the one hand, quantum mechanical efforts of the underlying material structure dominate device characteristics. On the other hand, one faces the technical difficulty in fabricating uniform devices. This has posed a great challenge for both the scientific and the technical communities. The proposal of using a single or a few organic molecules in electronic devices has not only opened an alternative way of miniaturization in electronics, but also brought up brand-new concepts and physical working mechanisms in electronic devices. This thesis work stands as one of the efforts in understanding and building of electronic functional units at the molecular and atomic levels. We have explored the possibility of having molecules working in a wide spectrum of electronic devices, ranging from molecular wires, spin valves/switches, diodes, transistors, and sensors. More specifically, we have observed significant magnetoresistive effect in a spin-valve structure where the non-magnetic spacer sandwiched between two magnetic conducting materials is replaced by a self-assembled monolayer of organic molecules or a single molecule (like a carbon fullerene). The diode behavior in donor(D)-bridge(B)-acceptor(A) type of single molecules is then discussed and a unimolecular transistor is designed. Lastly, we have proposed and primarily tested the idea of using functionalized electrodes for rapid nanopore DNA sequencing. In these studies, the fundamental roles of molecules and molecule-electrode interfaces on quantum electron transport have been investigated based on first-principles calculations of the electronic structure. Both the intrinsic properties of molecules themselves and the detailed interfacial features are found to play critical roles in electron transport at the molecular scale. The flexibility and tailorability of the properties of molecules have opened great opportunity in a purpose-driven design of electronic devices from the bottom up. The results that we gained from this work have helped in understanding the underlying physics, developing the fundamental mechanism and providing guidance for future experimental efforts.

Quantum transport in a single molecular junction

The craze for faster and smaller electronic devices has never gone down and this has always kept researchers on their toes. Following Moore’s law, which states that the number of transistors in a single chip will double in every 18 months, today “30 million transistors can fit into the head of a 1.5 mm diameter pin”. But this miniaturization cannot continue indefinitely due to the ‘quantum leakage’ limit in the thickness of the insulating layer between the gate electrode and the current carrying channel. To bypass this limitation, scientists came up with the idea of using vastly available organic molecules as components in an electronic device. One of the primary challenges in this field was the ability to perform conductance measurements across single molecular junctions. Once that was achieved the focus shifted to a deeper understanding of the underlying physics behind the electron transport across these molecular scale devices. Our initial theoretical approach is based on the conventional Non-Equilibrium Green Function(NEGF) formulation, but the self-energy of the leads is modified to include a weighting factor that ensures negligible current in the absence of a molecular pathway as observed in a Mechanically Controlled Break Junction (MCBJ) experiment. The formulation is then made parameter free by a more careful estimation of the self-energy of the leads. The calculated conductance turns out to be atleast an order more than the experimental values which is probably due to a strong chemical bond at the metal-molecule junction unlike in the experiments. The focus is then shifted to a comparative study of charge transport in molecular wires of different lengths within the same formalism. The molecular wires, composed of a series of organic molecules, are sanwiched between two gold electrodes to make a two terminal device. The length of the wire is increased by sequentially increasing the number of molecules in the wire from 1 to 3. In the low bias regime all the molecular devices are found to exhibit Ohmic behavior. However, the magnitude of conductance decreases exponentially with increase in length of the wire. In the next study, the relative contribution of the ‘in-phase’ and the ‘out-of-phase’ components of the total electronic current under the influence of an external bias is estimated for the wires of three different lengths. In the low bias regime, the ‘out-of-phase’ contribution to the total current is minimal and the ‘in-phase’ elastic tunneling of the electrons is responsible for the net electronic current. This is true irrespective of the length of the molecular spacer. In this regime, the current-voltage characteristics follow Ohm’s law and the conductance of the wires is found to decrease exponentially with increase in length which is in agreement with experimental results. However, after a certain ‘off-set’ voltage, the current increases non-linearly with bias and the ‘out-of-phase’ tunneling of electrons reduces the net current substantially. Subsequently, the interaction of conduction electrons with the vibrational modes as a function of external bias in the three different oligomers is studied since they are one of the main sources of phase-breaking scattering. The number of vibrational modes that couple strongly with the frontier molecular orbitals are found to increase with length of the spacer and the external field. This is consistent with the existence of lowest ‘off-set’ voltage for the longest wire under study.

First-principles studies of boron nanostructures

Boron is an 'electron deficient' element which has a rather fascinating chemical versatility. In the solid state, the elemental boron has neither a pure covalent nor a pure metallic character. As a result, its vast structural dimensionally and peculiar bonding features hold a unique place among other elements in the periodic table. In order to understand and properly describe these unusual bonding features, a detailed and systematic theoretical study is needed. In this work, I will show that some of the qualitative features of boron nanostructures, including clusters, sheets and nanotubes can easily be extracted from the results of first principles calculations based on density functional theory. Specifically, the size-dependent evolution of topological structures and bonding characteristics of boron clusters, Bn will be discussed. Based on the scenario observed in the boron clusters, the unique properties of boron sheets and boron nanotubes will be described. Moreover, the ballistic electron transport in single-walled carbon nanotubes will be considered. It is expected that the theoretical results obtained in the present thesis will initiate further studies on boron nanostructures, which will be helpful in understanding, designing and realizing boron-based nanoscale devices.

Genetic association studies under the population stratification, family pedigree and application to genome-wide association studies

This dissertation has three separate parts: the first part deals with the general pedigree association testing incorporating continuous covariates; the second part deals with the association tests under population stratification using the conditional likelihood tests; the third part deals with the genome-wide association studies based on the real rheumatoid arthritis (RA) disease data sets from Genetic Analysis Workshop 16 (GAW16) problem 1. Many statistical tests are developed to test the linkage and association using either case-control status or phenotype covariates for family data structure, separately. Those univariate analyses might not use all the information coming from the family members in practical studies. On the other hand, the human complex disease do not have a clear inheritance pattern, there might exist the gene interactions or act independently. In part I, the new proposed approach MPDT is focused on how to use both the case control information as well as the phenotype covariates. This approach can be applied to detect multiple marker effects. Based on the two existing popular statistics in family studies for case-control and quantitative traits respectively, the new approach could be used in the simple family structure data set as well as general pedigree structure. The combined statistics are calculated using the two statistics; A permutation procedure is applied for assessing the p-value with adjustment from the Bonferroni for the multiple markers. We use simulation studies to evaluate the type I error rates and the powers of the proposed approach. Our results show that the combined test using both case-control information and phenotype covariates not only has the correct type I error rates but also is more powerful than the other existing methods. For multiple marker interactions, our proposed method is also very powerful. Selective genotyping is an economical strategy in detecting and mapping quantitative trait loci in the genetic dissection of complex disease. When the samples arise from different ethnic groups or an admixture population, all the existing selective genotyping methods may result in spurious association due to different ancestry distributions. The problem can be more serious when the sample size is large, a general requirement to obtain sufficient power to detect modest genetic effects for most complex traits. In part II, I describe a useful strategy in selective genotyping while population stratification is present. Our procedure used a principal component based approach to eliminate any effect of population stratification. The paper evaluates the performance of our procedure using both simulated data from an early study data sets and also the HapMap data sets in a variety of population admixture models generated from empirical data. There are one binary trait and two continuous traits in the rheumatoid arthritis dataset of Problem 1 in the Genetic Analysis Workshop 16 (GAW16): RA status, AntiCCP and IgM. To allow multiple traits, we suggest a set of SNP-level F statistics by the concept of multiple-correlation to measure the genetic association between multiple trait values and SNP-specific genotypic scores and obtain their null distributions. Hereby, we perform 6 genome-wide association analyses using the novel one- and two-stage approaches which are based on single, double and triple traits. Incorporating all these 6 analyses, we successfully validate the SNPs which have been identified to be responsible for rheumatoid arthritis in the literature and detect more disease susceptibility SNPs for follow-up studies in the future. Except for chromosome 13 and 18, each of the others is found to harbour susceptible genetic regions for rheumatoid arthritis or related diseases, i.e., lupus erythematosus. This topic is discussed in part III.

STATISTICAL METHODS FOR RARE AND COMMON VARIANT ASSOCIATION STUDIES

Complex human diseases are a major challenge for biological research. The goal of my research is to develop effective methods for biostatistics in order to create more opportunities for the prevention and cure of human diseases. This dissertation proposes statistical technologies that have the ability of being adapted to sequencing data in family-based designs, and that account for joint effects as well as gene-gene and gene-environment interactions in the GWA studies. The framework includes statistical methods for rare and common variant association studies. Although next-generation DNA sequencing technologies have made rare variant association studies feasible, the development of powerful statistical methods for rare variant association studies is still underway. Chapter 2 demonstrates two adaptive weighting methods for rare variant association studies based on family data for quantitative traits. The results show that both proposed methods are robust to population stratification, robust to the direction and magnitude of the effects of causal variants, and more powerful than the methods using weights suggested by Madsen and Browning [2009]. In Chapter 3, I extended the previously proposed test for Testing the effect of an Optimally Weighted combination of variants (TOW) [Sha et al., 2012] for unrelated individuals to TOW &ndash F, TOW for Family &ndash based design. Simulation results show that TOW &ndash F can control for population stratification in wide range of population structures including spatially structured populations, is robust to the directions of effect of causal variants, and is relatively robust to percentage of neutral variants. In GWA studies, this dissertation consists of a two &ndash locus joint effect analysis and a two-stage approach accounting for gene &ndash gene and gene &ndash environment interaction. Chapter 4 proposes a novel two &ndash stage approach, which is promising to identify joint effects, especially for monotonic models. The proposed approach outperforms a single &ndash marker method and a regular two &ndash stage analysis based on the two &ndash locus genotypic test. In Chapter 5, I proposed a gene &ndash based two &ndash stage approach to identify gene &ndash gene and gene &ndash environment interactions in GWA studies which can include rare variants. The two &ndash stage approach is applied to the GAW 17 dataset to identify the interaction between KDR gene and smoking status.

STOCHASTIC CHARGE TRANSPORT IN MULTI-ISLAND SINGLE-ELECTRON TUNNELING DEVICES

The physics of the operation of singe-electron tunneling devices (SEDs) and singe-electron tunneling transistors (SETs), especially of those with multiple nanometer-sized islands, has remained poorly understood in spite of some intensive experimental and theoretical research. This computational study examines the current-voltage (IV) characteristics of multi-island single-electron devices using a newly developed multi-island transport simulator (MITS) that is based on semi-classical tunneling theory and kinetic Monte Carlo simulation. The dependence of device characteristics on physical device parameters is explored, and the physical mechanisms that lead to the Coulomb blockade (CB) and Coulomb staircase (CS) characteristics are proposed. Simulations using MITS demonstrate that the overall IV characteristics in a device with a random distribution of islands are a result of a complex interplay among those factors that affect the tunneling rates that are fixed a priori (e.g. island sizes, island separations, temperature, gate bias, etc.), and the evolving charge state of the system, which changes as the source-drain bias (VSD) is changed. With increasing VSD, a multi-island device has to overcome multiple discrete energy barriers (up-steps) before it reaches the threshold voltage (Vth). Beyond Vth, current flow is rate-limited by slow junctions, which leads to the CS structures in the IV characteristic. Each step in the CS is characterized by a unique distribution of island charges with an associated distribution of tunneling probabilities. MITS simulation studies done on one-dimensional (1D) disordered chains show that longer chains are better suited for switching applications as Vth increases with increasing chain length. They are also able to retain CS structures at higher temperatures better than shorter chains. In sufficiently disordered 2D systems, we demonstrate that there may exist a dominant conducting path (DCP) for conduction, which makes the 2D device behave as a quasi-1D device. The existence of a DCP is sensitive to the device structure, but is robust with respect to changes in temperature, gate bias, and VSD. A side gate in 1D and 2D systems can effectively control Vth. We argue that devices with smaller island sizes and narrower junctions may be better suited for practical applications, especially at room temperature.