ASU Scholarship Showcase

Novel hydride chemistries are employed to deposit light-emitting Ge_1-y Sn_yalloys with y ≤ 0.1 by Ultra-High Vacuum Chemical Vapor Deposition (UHV-CVD) on Ge-buffered Si wafers. The properties of the resultant materials are systematically compared with similar alloys grown directly on Si wafers. The fundamental difference between the two systems is a fivefold (and higher) decrease in lattice mismatch between film and virtual substrate, allowing direct integration of bulk-like crystals with planar surfaces and relatively low dislocation densities. For y ≤ 0.06, the CVD precursors used were digermane Ge₂H₆ and deuterated stannane SnD₄. For y ≥ 0.06, the Ge precursor was changed to trigermane Ge₃H₈, whose higher reactivity enabled the fabrication of supersaturated samples with the target film parameters. In all cases, the Ge wafers were produced using tetragermane Ge₄H₁₀ as the Ge source. The photoluminescence intensity from Ge_1-y Sn_y /Ge films is expected to increase relative to Ge_1-y Sn_y /Si due to the less defected interface with the virtual substrate. However, while Ge_1-y Sn_y /Si films are largely relaxed, a significant amount of compressive strain may be present in the Ge_1-y Sn_y /Ge case. This compressive strain can reduce the emission intensity by increasing the separation between the direct and indirect edges. In this context, it is shown here that the proposed CVD approach to Ge_1-y Sn_y /Ge makes it possible to approach film thicknesses of about 1  μm, for which the strain is mostly relaxed and the photoluminescence intensity increases by one order of magnitude relative to Ge_1-y Sn_y /Si films. The observed strain relaxation is shown to be consistent with predictions from strain-relaxation models first developed for the Si_1-x Ge_x /Si system. The defect structure and atomic distributions in the films are studied in detail using advanced electron-microscopy techniques, including aberration corrected STEM imaging and EELS mapping of the average diamond–cubic lattice.

We develop a general framework to analyze the controllability of multiplex networks using multiple-relation networks and multiple-layer networks with interlayer couplings as two classes of prototypical systems. In the former, networks associated with different physical variables share the same set of nodes and in the latter, diffusion processes take place. We find that, for a multiple-relation network, a layer exists that dominantly determines the controllability of the whole network and, for a multiple-layer network, a small fraction of the interconnections can enhance the controllability remarkably. Our theory is generally applicable to other types of multiplex networks as well, leading to significant insights into the control of complex network systems with diverse structures and interacting patterns.

In this paper, we report on the highly conductive layer formed at the crystalline γ-alumina/SrTiO₃ interface, which is attributed to oxygen vacancies. We describe the structure of thin γ-alumina layers deposited by molecular beam epitaxy on SrTiO3 (001) at growth temperatures in the range of 400–800 °C, as determined by reflection-high-energy electron diffraction, x-ray diffraction, and high-resolution electron microscopy. In situ x-ray photoelectron spectroscopy was used to confirm the presence of the oxygen-deficient layer. Electrical characterization indicates sheet carrier densities of ∼1013 cm−2 at room temperature for the sample deposited at 700 °C, with a maximum electron Hall mobility of 3100 cm²V^-1s^-1 at 3.2 K and room temperature mobility of 22 cm²V^-1s^-1. Annealing in oxygen is found to reduce the carrier density and turn a conductive sample into an insulator.

The development of non-volatile logic through direct coupling of spontaneous ferroelectric polarization with semiconductor charge carriers is nontrivial, with many issues, including epitaxial ferroelectric growth, demonstration of ferroelectric switching and measurable semiconductor modulation. Here we report a true ferroelectric field effect—carrier density modulation in an underlying Ge(001) substrate by switching of the ferroelectric polarization in epitaxial c-axis-oriented BaTiO₃ grown by molecular beam epitaxy. Using the density functional theory, we demonstrate that switching of BaTiO₃ polarization results in a large electric potential change in Ge. Aberration-corrected electron microscopy confirms BaTiO₃ tetragonality and the absence of any low-permittivity interlayer at the interface with Ge. The non-volatile, switchable nature of the single-domain out-of-plane ferroelectric polarization of BaTiO₃ is confirmed using piezoelectric force microscopy. The effect of the polarization switching on the conductivity of the underlying Ge is measured using microwave impedance microscopy, clearly demonstrating a ferroelectric field effect.

We report a study of the magnetic domain structure of nanocrystalline thin films of nickel-zinc ferrite. The ferrite films were synthesized using aqueous spin-spray coating at low temperature (∼90 °C) and showed high complex permeability in the GHz range. Electron microscopy and microanalysis revealed that the films consisted of columnar grains with uniform chemical composition. Off-axis electron holography combined with magnetic force microscopy indicated a multi-grain domain structure with in-plane magnetization. The correlation between the magnetic domain morphology and crystal structure is briefly discussed.

The current work explores the crystalline perovskite oxide, strontium hafnate, as a potential high-k gate dielectric for Ge-based transistors. SrHfO3 (SHO) is grown directly on Ge by atomic layer deposition and becomes crystalline with epitaxial registry after post-deposition vacuum annealing at ∼700 °C for 5 min. The 2 × 1 reconstructed, clean Ge (001) surface is a necessary template to achieve crystalline films upon annealing. The SHO films exhibit excellent crystallinity, as shown by x-ray diffraction and transmission electron microscopy. The SHO films have favorable electronic properties for consideration as a high-k gate dielectric on Ge, with satisfactory band offsets (>2 eV), low leakage current (<10^-5 A/cm² at an applied field of 1 MV/cm) at an equivalent oxide thickness of 1 nm, and a reasonable dielectric constant (k ∼ 18). The interface trap density (Dit) is estimated to be as low as ∼2 × 10¹² cm^-2 eV^-1 under the current growth and anneal conditions. Some interfacial reaction is observed between SHO and Ge at temperatures above ∼650 °C, which may contribute to increased Dit value. This study confirms the potential for crystalline oxides grown directly on Ge by atomic layer deposition for advanced electronic applications.

Dynamical processes occurring on the edges in complex networks are relevant to a variety of real-world situations. Despite recent advances, a framework for edge controllability is still required for complex networks of arbitrary structure and interaction strength. Generalizing a previously introduced class of processes for edge dynamics, the switchboard dynamics, and exploit- ing the exact controllability theory, we develop a universal framework in which the controllability of any node is exclusively determined by its local weighted structure. This framework enables us to identify a unique set of critical nodes for control, to derive analytic formulas and articulate efficient algorithms to determine the exact upper and lower controllability bounds, and to evaluate strongly structural controllability of any given network. Applying our framework to a large number of model and real-world networks, we find that the interaction strength plays a more significant role in edge controllability than the network structure does, due to a vast range between the bounds determined mainly by the interaction strength. Moreover, transcriptional regulatory networks and electronic circuits are much more strongly structurally controllable (SSC) than other types of real-world networks, directed networks are more SSC than undirected networks, and sparse networks are typically more SSC than dense networks.

Recent works revealed that the energy required to control a complex network depends on the number of driving signals and the energy distribution follows an algebraic scaling law. If one implements control using a small number of drivers, e.g. as determined by the structural controllability theory, there is a high probability that the energy will diverge. We develop a physical theory to explain the scaling behaviour through identification of the fundamental structural elements, the longest control chains (LCCs), that dominate the control energy. Based on the LCCs, we articulate a strategy to drastically reduce the control energy (e.g. in a large number of real-world networks). Owing to their structural nature, the LCCs may shed light on energy issues associated with control of nonlinear dynamical networks.

Given a complex geospatial network with nodes distributed in a two-dimensional region of physical space, can the locations of the nodes be determined and their connection patterns be uncovered based solely on data? We consider the realistic situation where time series/signals can be collected from a single location. A key challenge is that the signals collected are necessarily time delayed, due to the varying physical distances from the nodes to the data collection centre. To meet this challenge, we develop a compressive-sensing-based approach enabling reconstruction of the full topology of the underlying geospatial network and more importantly, accurate estimate of the time delays. A standard triangularization algorithm can then be employed to find the physical locations of the nodes in the network. We further demonstrate successful detection of a hidden node (or a hidden source or threat), from which no signal can be obtained, through accurate detection of all its neighbouring nodes. As a geospatial network has the feature that a node tends to connect with geophysically nearby nodes, the localized region that contains the hidden node can be identified.

Locating sources of diffusion and spreading from minimum data is a significant problem in network science with great applied values to the society. However, a general theoretical framework dealing with optimal source localization is lacking. Combining the controllability theory for complex networks and compressive sensing, we develop a framework with high efficiency and robustness for optimal source localization in arbitrary weighted networks with arbitrary distribution of sources. We offer a minimum output analysis to quantify the source locatability through a minimal number of messenger nodes that produce sufficient measurement for fully locating the sources. When the minimum messenger nodes are discerned, the problem of optimal source localization becomes one of sparse signal reconstruction, which can be solved using compressive sensing. Application of our framework to model and empirical networks demonstrates that sources in homogeneous and denser networks are more readily to be located. A surprising finding is that, for a connected undirected network with random link weights and weak noise, a single messenger node is sufficient for locating any number of sources. The framework deepens our understanding of the network source localization problem and offers efficient tools with broad applications.