The Quantum Socket: Three-Dimensional Wiring for Extensible Quantum Computing

Quantum computing architectures are on the verge of scalability, a key requirement for the implementation of a universal quantum computer. The next stage in this quest is the realization of quantum error correction codes, which will mitigate the impact of faulty quantum information on a quantum computer. Architectures with ten or more quantum bits (qubits) have been realized using trapped ions and superconducting circuits. While these implementations are potentially scalable, true scalability will require systems engineering to combine quantum and classical hardware. One technology demanding imminent efforts is the realization of a suitable wiring method for the control and measurement of a large number of qubits. In this work, we introduce an interconnect solution for solid-state qubits: The quantum socket. The quantum socket fully exploits the third dimension to connect classical electronics to qubits with higher density and better performance than two-dimensional methods based on wire bonding. The quantum socket is based on spring-mounted micro wires the three-dimensional wires that push directly on a micro-fabricated chip, making electrical contact. A small wire cross section (~1 mmm), nearly non-magnetic components, and functionality at low temperatures make the quantum socket ideal to operate solid-state qubits. The wires have a coaxial geometry and operate over a frequency range from DC to 8 GHz, with a contact resistance of ~150 mohm, an impedance mismatch of ~10 ohm, and minimal crosstalk. As a proof of principle, we fabricated and used a quantum socket to measure superconducting resonators at a temperature of ~10 mK.Comment: Main: 31 pages, 19 figs., 8 tables, 8 apps.; suppl.: 4 pages, 5 figs. (HiRes figs. and movies on request). Submitte

Synthesis and chemical modification of carbon nanostructures for materials applications

This dissertation explores the structure, chemical reactivities, electromagnetic response, and materials properties of various carbon nanostructures, including single-walled carbon nanotubes (SWCNTs), multi-walled carbon nanotubes (MWCNTs), graphite, and graphene nanoribbons (GNRs). Efficient production and modification of these unique structures, each with their own distinct properties, will make them more accessible for applications in electronics, materials, and biology. A method is reported for controlling the permittivity from 1–1000 MHz of SWCNT-polymer composites (0.5 wt%) for radio frequency applications including passive RF antenna structures and EMI shielding. The magnitude of the real permittivity varied between 20 and 3.3, decreasing as higher fractions of functionalized-SWCNTs were added. The microwave absorbing properties and subsequent heating of carbon nanotubes were used to rapidly cure ceramic composites. With less than 1 wt% carbon nanotube additives and 30–40 W of directed microwave power (2.45 GHz), bulk composite samples reached temperatures above 500°C within 1 min. Graphite oxide (GO) polymer nanocomposites were developed at 1, 5, and 10 wt% for the purpose of evaluating the flammability reduction and materials properties of the resulting systems. Microscale oxygen consumption calorimetry revealed that addition of GO reduced the total heat release in all systems, and GO-polycarbonate composites demonstrated very fast self-extinguishing times in vertical open flame tests. A simple solution-based oxidative process using potassium permanganate in sulfuric acid was developed for producing nearly 100% yield of graphene nanoribbons (GNRs) by lengthwise cutting and unraveling of MWCNT sidewalls. Subsequent chemical reduction of the GNRs resulted in restoration of electrical conductivity. The GNR synthetic conditions were investigated in further depth, and an improved method which utilized a two-acid reaction medium was found to produce GNRs with fewer defects and/or holes on the basal plane and higher aspect ratio. Two different covalent functionalization methods for GNRs based on diazonium chemistry were developed. The resulting functionalized GNRs (f-GNRs) are readily soluble in organic solvents which increase their solution processability. The f-GNRs were also found to be in a reduced state, with minimal sp2 carbon disruption, while also keeping the ribbon shape

Advancements in Measuring and Modeling the Mechanical and Hydrological Properties of Snow and Firn: Multi-sensor Analysis, Integration, and Algorithm Development

Estimating snow mechanical properties – such as elastic modulus, stiffness, and strength – is important for understanding how effectively a vehicle can travel over snow-covered terrain. Vehicle instrumentation data and observations of the snowpack are valuable for improving the estimates of winter vehicle performance. Combining in-situ and remotely-sensed snow observations, driver input, and vehicle performance sensors requires several techniques of data integration. I explored correlations between measurements spanning from millimeter to meter scales, beginning with the SnowMicroPenetrometer (SMP) and instruments applied to snow that were designed for measuring the load bearing capacity and the compressive and shear strengths of roads and soils. The spatial distribution of snow’s mechanical properties is still largely unknown. From this initial work, I determined that snow density remains a useful proxy for snowpack strength. To measure snow density, I applied multi-sensor electromagnetic methods. Using spatially distributed snowpack, terrain, and vegetation information developed in the subsequent chapters, I developed an over-snow vehicle performance model. To measure the vehicle performance, I joined driver and vehicle data in the coined Normalized Difference Mobility Index (NDMI). Then, I applied regression methods to distribute NDMI from spatial snow, terrain, and vegetation properties. Mobility prediction is useful for the strategic advancement of warfighting in cold regions. The security of water resources is climatologically inequitable and water stress causes international conflict. Water resources derived from snow are essential for modern societies in climates where snow is the predominant source of precipitation, such as the western United States. Snow water equivalent (SWE) is a critical parameter for yearly water supply forecasting and can be calculated by multiplying the snow depth by the snow density. In this work, I combined high-spatial resolution light detection and ranging (LiDAR) measured snow depths with ground-penetrating radar (GPR) measurements of two-way travel-time (TWT) to solve for snow density. Then using LiDAR derived terrain and vegetation features as predictors in a multiple linear regression, the density observations are distributed across the SnowEx 2020 study area at Grand Mesa, Colorado. The modeled density resolved detailed patterns that agree with the known interactions of snow with wind, terrain, and vegetation. The integration of radar and LiDAR sensors shows promise as a technique for estimating SWE across entire river basins and evaluating observational- or physics-based snow-density models. Accurate estimation of SWE is a means of water security. In our changing climate, snow and ice mass are being permanently lost from the cryosphere. Mass balance is an indicator of the (in)stability of glaciers and ice sheets. Surface mass balance (SMB) may be estimated by multiplying the thickness of any annual snowpack layer by its density. Though, unlike applications in seasonal snowpack, the ages of annual firn layers are unknown. To estimate SMB, I modeled the firn depth, density, and age using empirical and numerical approaches. The annual SMB history shows cyclical patterns representing the combination of atmospheric, oceanic, and anthropogenic climate forcing, which may serve as evaluation or assimilation data in climate model retrievals of SMB. The advancements made using the SMP, multi-channel GPR arrays, and airborne LiDAR and radar within this dissertation have made it possible to spatially estimate the snow depth, density, and water equivalent in seasonal snow, glaciers, and ice sheets. Open access, process automation, repeatability, and accuracy were key design parameters of the analyses and algorithms developed within this work. The many different campaigns, objectives, and outcomes composing this research documented the successes and limitations of multi-sensor estimation techniques for a broad range of cryosphere applications

Synchrotron X-ray imaging and ultrafast tomography in situ study of the fragmentation and growth dynamics of dendritic microstructures in solidification under ultrasound

High speed synchrotron X-ray imaging and ultrafast tomography were used to study in situ and in real time the fragmentation and growth dynamics of dendritic microstructures of an Al-15%Cu alloy in solidification under ultrasound. An ultrasound of 30 kHz with vibration amplitude of 29 µm was applied into the alloy melt and produced a strong swirling acoustic flow of ~0.3 m/s. Efficient dendrite fragmentation occurred due to the acoustic flow and the dominant mechanism is the thermal perturbation remelting plus mechanical fracture and separation effect. Acoustic flow fatigue impact and phase collision effects were found to play a minor role in causing dendrite fragmentation. Just 10 s of ultrasound application at the early stage of solidification produced ~100% more dendrite fragments compared to the case without ultrasound, resulting in 20~25% reduction in the average grain size in the solidified samples. Furthermore, the dendrite morphology and tip growth velocity were mainly affected by the initial dendrite fragment number density and their distribution. The systematic and real-time datasets obtained in near operando conditions provided valuable 4D information for validation of numerical models and assistance in developing optimisation strategy for ultrasound melt processing in industry

Processing, Characterization And Performance Of Carbon Nanopaper Based Multifunctional Nanocomposites

Carbon nanofibers (CNFs) used as nano-scale reinforcement have been extensively studied since they are capable of improving the physical and mechanical properties of conventional fiber reinforced polymer composites. However, the properties of CNFs are far away from being fully utilized in the composites due to processing challenges including the dispersion of CNFs and the viscosity increase of polymer matrix. To overcome these issues, a unique approach was developed by making carbon nanopaper sheet through the filtration of well-dispersed carbon nanofibers under controlled processing conditions, and integrating carbon nanopaper sheets into composite laminates using autoclave process and resin transfer molding (RTM). This research aims to fundamentally study the processing-structure-property-performance relationship of carbon nanopaper-based nanocomposites multifunctional applications: a) Vibrational damping. Carbon nanofibers with extremely high aspect ratios and low density present an ideal candidate as vibrational damping material; specifically, the large specific area and aspect ratio of carbon nanofibers promote significant interfacial friction between carbon nanofiber and polymer matrix, causing higher energy dissipation in the matrix. Polymer composites with the reinforcement of carbon nanofibers in the form of a paper sheet have shown significant vibration damping improvement with a damping ratio increase of 300% in the nanocomposites. b) Wear resistance. In response to the iv observed increase in toughness of the nanocomposites, tribological properties of the nanocomposite coated with carbon nanofiber/ceramic particles hybrid paper have been studied. Due to high strength and toughness, carbon nanofibers can act as microcrack reducer; additionally, the composites coated with such hybrid nanopaper of carbon nanofiber and ceramic particles shown an improvement of reducing coefficient of friction (COF) and wear rate. c) High electrical conductivity. A highly conductive coating material was developed and applied on the surface of the composites for the electromagnetic interference shielding and lightning strike protection. To increase the conductivity of the carbon nanofiber paper, carbon nanofibers were modified with nickel nanostrands. d) Electrical actuation of SMP composites. Compared with other methods of SMP actuation, the use of electricity to induce the shape-memory effect of SMP is desirable due to the controllability and effectiveness. The electrical conductivity of carbon fiber reinforced SMP composites can be significantly improved by incorporating CNFs and CNF paper into them. A vision-based system was designed to control the deflection angle of SMP composites to desired values. The funding support from National Science Foundation and FAA Center of Excellence for Commercial Space Transportation (FAA COE CST) is acknowledged

Surface Magneto Plasmons and Their Applications

Due to their promising properties, surface magneto plasmons have attracted great interests in the field of plasmonics. Apart from flexible modulation of the plasmonic properties by an external magnetic field, surface magneto plasmons also promise nonreciprocal effect and multi-bands of propagation, which can be applied into the design of integrated plasmonic devices for biosensing and telecommunication applications. In the visible frequencies, hybrid nanodevices consisting of metals and magnetic materials based on surface magneto plasmon are proposed. In the infrared frequencies, highly-doped semiconductors can replace metals, owning to the lower incident wave frequencies and lower plasma frequencies. Furthermore, a promising 2D material-graphene shows great potential in infrared magnetic plasmonics. In this book chapter, we will review the magneto plasmonics with a focus on device designs and applications. We will give the basic theory of surface magneto plasmons propagating in different structures, including plane surface structures and slot waveguides. Based on the fundamental investigation and theoretical studies, we will illustrate various magneto plasmonic micro/nanodevices, such as tunable waveguides, filters, and beam-splitters. Novel plasmonic devices such as one-way waveguides and broad-band waveguides will also be introduced