Electrical and optical studies on carbon nanotube arrays

Single-walled carbon nanotubes (SWNTs) have been studied as a prominent class of high performance electronic materials for next generation electronics. Their geometry dependent electronic structure, ballistic transport and low power dissipation due to quasi one dimensional transport, and their capability of carrying high current densities are some of the main reasons for the optimistic expectations on SWNTs. However, device applications of individual SWNTs have been hindered by uncontrolled variations in characteristics and lack of scalable methods to integrate SWNTs into electronic devices. One relatively new direction in SWNT electronics, which avoids these issues, is using arrays of SWNTs, where the ensemble average may provide uniformity from device to device, and this new breed of electronic material can be integrated into electronic devices in a scalable fashion. This dissertation describes (1) methods for characterization of SWNT arrays, (2) how the electrical transport in these two-dimensional arrays depend on length scales and spatial anisotropy, (3) the interaction of aligned SWNTs with the underlying substrate, and (4) methods for scalable integration of SWNT arrays into electronic devices. The electrical characterization of SWNT arrays have been realized by polymer electrolyte-gated SWNT thin film transistors (TFTs). Polymer electrolyte-gating addresses many technical difficulties inherent to electrical characterization by gating through oxide-dielectrics. Having shown polymer electrolyte-gating can be successfully applied on SWNT arrays, we have studied the length scaling dependence of electrical transport in SWNT arrays. Ultrathin films formed by sub-monolayer surface coverage of SWNT arrays are very interesting systems in terms of the physics of two-dimensional electronic transport. We have observed that they behave qualitatively different than the classical conducting films, which obey the Ohm’s law. The resistance of an ultrathin film of SWNT arrays is indeed non-linear with the length of the film, across which the transport occurs. More interestingly, a transition between conducting and insulating states is observed at a critical surface coverage, which is called percolation limit. The surface coverage of conducting SWNTs can be manipulated by turning on and off the semiconductors in the SWNT array, leading to the operation principle of SWNT TFTs. The percolation limit depends also on the length and the spatial orientation of SWNTs. We have also observed that the percolation limit increases abruptly for aligned arrays of SWNTs, which are grown on single crystal quartz substrates. In this dissertation, we also compare our experimental results with a two-dimensional stick network model, which gives a good qualitative picture of the electrical transport in SWNT arrays in terms of surface coverage, length scaling, and spatial orientation, and briefly discuss the validity of this model. However, the electronic properties of SWNT arrays are not only determined by geometrical arguments. The contact resistances at the nanotube-nanotube and nanotube-electrode (bulk metal) interfaces, and interactions with the local chemical groups and the underlying substrates are among other issues related to the electronic transport in SWNT arrays. Different aspects of these factors have been studied in detail by many groups. In fact, I have also included a brief discussion about electron injection onto semiconducting SWNTs by polymer dopants. On the other hand, we have compared the substrate-SWNT interactions for isotropic (in two dimensions) arrays of SWNTs grown on Si/SiO2 substrates and horizontally (on substrate) aligned arrays of SWNTs grown on single crystal quartz substrates. The anisotropic interactions associated with the quartz lattice between quartz and SWNTs that allow near perfect horizontal alignment on substrate along a particular crystallographic direction is examined by Raman spectroscopy, and shown to lead to uniaxial compressive strain in as-grown SWNTs on single crystal quartz. This is the first experimental demonstration of the hard-to-achieve uniaxial compression of SWNTs. Temperature dependence of Raman G-band spectra along the length of individual nanotubes reveals that the compressive strain is non-uniform and can be larger than 1% locally at room temperature. Effects of device fabrication steps on the non-uniform strain are also examined and implications on electrical performance are discussed. Based on our findings, there are discussions about device performances and designs included in this dissertation. The channel length dependences of device mobilities and on/off ratios are included for SWNT TFTs. Time response of polymer-electrolyte gated SWNT TFTs has been measured to be ~300 Hz, and a proof-of-concept logic inverter has been fabricated by using polymer electrolyte gated SWNT TFTs for macroelectronic applications. Finally, I dedicated a chapter on scalable device designs based on aligned arrays of SWNTs, including a design for SWNT memory devices.

Superconducting Transition-Edge Sensor Physics

Despite record-setting performance demonstrated by superconducting Transition Edge Sensors (TESs) and growing utilization of the technology, a theoretical model of the physics governing TES devices superconducting phase transition has proven elusive. Earlier attempts to describe TESs assumed them to be uniform superconductors. Sadleir et al. 2010 shows that TESs are weak links and that the superconducting order parameter strength has significant spatial variation. Measurements are presented of the temperature T and magnetic field B dependence of the critical current Ic measured over 7 orders of magnitude on square Mo/Au bilayers ranging in length from 8 to 290 microns. We find our measurements have a natural explanation in terms of a spatially varying order parameter that is enhanced in proximity to the higher transition temperature superconducting leads (the longitudinal proximity effect) and suppressed in proximity to the added normal metal structures (the lateral inverse proximity effect). These in-plane proximity effects and scaling relations are observed over unprecedentedly long lengths (in excess of 1000 times the mean free path) and explained in terms of a Ginzburg-Landau model. Our low temperature Ic(B) measurements are found to agree with a general derivation of a superconducting strip with an edge or geometric barrier to vortex entry and we also derive two conditions that lead to Ic rectification. At high temperatures the Ic(B) exhibits distinct Josephson effect behavior over long length scales and following functional dependences not previously reported. We also investigate how film stress changes the transition, explain some transition features in terms of a nonequilibrium superconductivity effect, and show that our measurements of the resistive transition are not consistent with a percolating resistor network model.

Scheduling of track inspection and maintenance activities in railroad networks

The U.S. railroad companies spend billions of dollars every year on railroad track maintenance in order to ensure safety and operational efficiency of their railroad networks. Besides maintenance costs, other costs such as train accident costs, train and shipment delay costs and rolling stock maintenance costs are also closely related to track maintenance activities. Optimizing the track maintenance process on the extensive railroad networks is a very complex problem with major cost implications. Currently, the decision making process for track maintenance planning is largely manual and primarily relies on the knowledge and judgment of experts. There is considerable potential to improve the process by using operations research techniques to develop solutions to the optimization problems on track maintenance. In this dissertation study, we propose a range of mathematical models and solution algorithms for three network-level scheduling problems on track maintenance: track inspection scheduling problem (TISP), production team scheduling problem (PTSP) and job-to-project clustering problem (JTPCP). TISP involves a set of inspection teams which travel over the railroad network to identify track defects. It is a large-scale routing and scheduling problem where thousands of tasks are to be scheduled subject to many difficult side constraints such as periodicity constraints and discrete working time constraints. A vehicle routing problem formulation was proposed for TISP, and a customized heuristic algorithm was developed to solve the model. The algorithm iteratively applies a constructive heuristic and a local search algorithm in an incremental scheduling horizon framework. The proposed model and algorithm have been adopted by a Class I railroad in its decision making process. Real-world case studies show the proposed approach outperforms the manual approach in short-term scheduling and can be used to conduct long-term what-if analyses to yield managerial insights. PTSP schedules capital track maintenance projects, which are the largest track maintenance activities and account for the majority of railroad capital spending. A time-space network model was proposed to formulate PTSP. More than ten types of side constraints were considered in the model, including very complex constraints such as mutual exclusion constraints and consecution constraints. A multiple neighborhood search algorithm, including a decomposition and restriction search and a block-interchange search, was developed to solve the model. Various performance enhancement techniques, such as data reduction, augmented cost function and subproblem prioritization, were developed to improve the algorithm. The proposed approach has been adopted by a Class I railroad for two years. Our numerical results show the model solutions are able to satisfy all hard constraints and most soft constraints. Compared with the existing manual procedure, the proposed approach is able to bring significant cost savings and operational efficiency improvement. JTPCP is an intermediate problem between TISP and PTSP. It focuses on clustering thousands of capital track maintenance jobs (based on the defects identified in track inspection) into projects so that the projects can be scheduled in PTSP. A vehicle routing problem based model and a multiple-step heuristic algorithm were developed to solve this problem. Various side constraints such as mutual exclusion constraints and rounding constraints were considered. The proposed approach has been applied in practice and has shown good performance in both solution quality and efficiency.