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Open Access Publications from the University of California

Scholarly Works (14 results)

  • Thesis
  • Peer Reviewed
UCLA Electronic Theses and Dissertations (2017)

The goal of this dissertation is to propose, elaborate, and validate a modeling, simulation and design tool for magnetic RF devices that encompasses the fields of electrodynamics, micromagnetics and other possible physics such as elastodynamics. Comparing to conventional approach based on magnetostatic approximations, our solution with full dynamics can provide a correct prediction to the electromagnetic power flow which determine the impedance match and radiation efficiency of a thin film magnetic filter or antenna.

First, we introduce both one-dimensional (1-D) and three-dimensional (3-D) modeling frameworks, with the former serving as the proof of the concept and the latter as a comprehensive modeling tool. The 1-D algorithm is based on an unknown reduction strategy to overcome the multiscale problem. The 3-D modeling is based on modified alternating-direction-implicit finite-difference time-domain methods (ADI FDTD) with unconditional stability. It has the capability of modeling the anisotropic and dispersive properties of magnetic material. The proposed algorithms solve Maxwell’s equations and Landau-Lifshitz-Gilbert (LLG) equation jointly and simultaneously, with verified accuracy and efficiency.

Second, we propose a novel antenna radiation mechanism, bulk-acoustic-wave (BAW) mediated multiferroic antenna. Such multiferroic antennas compose of piezoelectric material and magnetostrictive material, in which time-varying magnetic flux can be induced from the dynamic mechanical strain of acoustic waves. The BAW mediated multiferroic antenna can be used to create electromagnetic radiation and to alleviate the platform effect associated with low-profile conformal antennas. Its potential for efficient radiation of electromagnetic waves is evaluated by analytically deriving the lower bound of its radiation quality factor (Q factor). Moreover, the performance of the antenna is predicted by both the 1-D and 3-D modeling tools that we have developed. The study concludes that efficient antennas may be realized at GHz frequencies with thin film multiferroic material that has dimensions on the order of 10-5 wavelength.

Finally, we summarize the research results and discuss future potential research opportunities and challenges in this field. There are still many unresolved questions in this new research field. Nevertheless, the multiphysics time-domain solver that we proposed has shown the potential of an unprecedented ability to accurately model and design next-generation magnetic RF systems and components.

    Cover page: A Multiscale, Unconditionally Stable Multiphysics Time-Domain (MUST) Solver Unifying Electrodynamics, Elastodynamics and Spin Dynamics
    • Thesis
    • Peer Reviewed
    UCLA Electronic Theses and Dissertations (2014)

    A bulk acoustic wave (BAW) based multiferroic antenna structure is proposed, to overcome the platform effect associated with low-profile antennas. Numerical analysis based on the one-dimensional finite-difference time-domain (1D FDTD) technique, as well as analytical analysis is applied. The dynamic stress profile within the resonator and the radiation quality factors (Q factors) are simulated. The radiation of the electromagnetic waves acting as a damping load to the acoustic resonances is represented. In addition, both electrical conductive loss of nickel and magnetic damping loss of yttrium iron garnet (YIG) are considered and simulated with full dynamics via the coupling of Maxwell's equations and Landau-Lifshitz-Gilbert (LLG) equations. In the LLG/Maxwell modeling, the simulated relative permeability curves match the theoretical plot obtained by classical analysis. Furthermore, the radiated power is simulated, which increases as the thickness of the film increases or the line width of the material decreases. It should be noted that the normalized radiation power is maximum at the ferromagnetic resonance frequency (FMR), which opens up a new antenna design strategy to make the antenna work at FMR to enhance the radiation. The agreement between the numerical solutions and the analytical solutions provides a validation to the operating principle of the proposed antenna.

      Cover page: Dynamic Analysis of Thin Film Multiferroic Radiation via FDTD Methods
      • Article
      • Peer Reviewed
      LBL Publications (2023)
        Cover page: Two-fluid physical modeling of superconducting resonators in the ARTEMIS frameworkCreative Commons 'BY' version 4.0 license
        • Article
        • Peer Reviewed
        LBL Publications (2022)
        We present a high-performance coupled electrodynamics–micromagnetics solver for full physical modeling of signals in microelectronic circuitry. The overall strategy couples a finite-difference time-domain approach for Maxwell’s equations to a magnetization model described by the Landau–Lifshitz–Gilbert equation. The algorithm is implemented in the Exascale Computing Project software framework, AMReX, which provides effective scalability on manycore and GPU-based supercomputing architectures. Furthermore, the code leverages ongoing developments of the Exascale Application Code, WarpX, which is primarily being developed for plasma wakefield accelerator modeling. Our temporal coupling scheme provides second-order accuracy in space and time by combining the integration steps for the magnetic field and magnetization into an iterative sub-step that includes a trapezoidal temporal discretization for the magnetization. The performance of the algorithm is demonstrated by the excellent scaling results on NERSC multicore and GPU systems, with a significant (59×) speedup on the GPU using a node-by-node comparison. We demonstrate the utility of our code by performing simulations of an electromagnetic waveguide and a magnetically tunable filter.
          Cover page: A massively parallel time-domain coupled electrodynamics–micromagnetics solver
          • Article
          • Peer Reviewed
          UC Berkeley Previously Published Works (2024)
          HfO2– and ZrO2–based ferroelectric thin films have emerged as promising candidates for the gate oxides of next-generation electronic devices. Recent work has experimentally demonstrated that a tetragonal/orthorhombic (t/o-) phase mixture with partially in-plane polarization can lead to negative capacitance (NC) stabilization. However, there is a discrepancy between experiments and the theoretical understanding of domain formation and domain wall motion in these multi-phase, polycrystalline materials. Furthermore, the effect of anisotropic domain wall coupling on NC has not been studied so far. Here, 3D phase field simulations of HfO2– and ZrO2–based mixed-phase ultra-thin films on silicon are applied to understand the necessary and beneficial conditions for NC stabilization. It is found that smaller ferroelectric grains and a larger angle of the polar axis with respect to the out-of-plane direction enhances the NC effect. Furthermore, it is shown that theoretically predicted negative domain wall coupling even along only one axis prevents NC stabilization. Therefore, it is concluded that topological domain walls play a critical role in experimentally observed NC phenomena in HfO2– and ZrO2–based ferroelectrics.
            Cover page: 3D Ferroelectric Phase Field Simulations of Polycrystalline Multi‐Phase Hafnia and Zirconia Based Ultra‐Thin FilmsCreative Commons 'BY' version 4.0 license
            • Article
            • Peer Reviewed
            LBL Publications (2023)
            Modeling and characterization of electromagnetic wave interactions with microelectronic devices to derive network parameters has been a widely used practice in the electronic industry. However, as these devices become increasingly miniaturized with finer-scale geometric features, computational tools must make use of manycore/GPU architectures to efficiently resolve length and time scales of interest. This has been the focus of our open-source solver, ARTEMIS (Adaptive mesh Refinement Time-domain ElectrodynaMIcs Solver), which is performant on modern GPU-based supercomputing architectures while being amenable to additional physics coupling. This work demonstrates its use for characterizing network parameters of transmission lines using established techniques. A rigorous verification and validation of the workflow is carried out, followed by its application for analyzing a transmission line on a CMOS chip designed for a photon-detector application. Simulations are performed for millions of timesteps on state-of-the-art GPU resources to resolve nanoscale features at gigahertz frequencies. The network parameters are used to obtain phase delay and characteristic impedance that serve as inputs to SPICE models. The code is demonstrated to exhibit ideal weak scaling efficiency up to 1024 GPUs and 84% efficiency for 2048 GPUs, which underscores its use for network analysis of larger, more complex circuit devices in the future.
              Cover page: Characterization of Transmission Lines in Microelectronic Circuits Using the ARTEMIS SolverCreative Commons 'BY' version 4.0 license
              • Article
              • Peer Reviewed
              UC Berkeley Previously Published Works (2023)
              We present a massively parallel, 3D phase-field simulation framework for modeling ferroelectric materials based scalable logic devices. This code package, FerroX, self-consistently solves the time-dependent Ginzburg Landau (TDGL) equation for ferroelectric polarization, Poisson's equation for electric potential, and charge equation for carrier densities in semiconductor regions. The algorithm is implemented using the AMReX software framework [1], which provides effective scalability on manycore and GPU-based supercomputing architectures. We demonstrate the performance of the algorithm with excellent scaling results on NERSC multicore and GPU systems, with a significant (15×) speedup on the GPU using a node-by-node comparison. We further demonstrate the applicability of the code in simulations of ferroelectric domain-wall induced negative capacitance (NC) effect in Metal-Ferroelectric-Insulator-Metal (MFIM) and Metal-Ferroelectric-Insulator-Semiconductor-Metal (MFISM) devices. The charge (Q) v.s. voltage (V) responses for these 3D structures clearly indicate stabilized negative capacitance with multidomain formation, which is corroborated by amplification of the voltage at the interface between the ferroelectric and dielectric layers.
                Cover page: FerroX: A GPU-accelerated, 3D phase-field simulation framework for modeling ferroelectric devicesCreative Commons 'BY' version 4.0 license
                • Article
                • Peer Reviewed
                Applied Math & Comp Sci (2021)
                This paper presents an innovative way of quantum circuit optimization; we propose an automated superconducting circuit calibration using deep reinforcement learning (ASCC-DRL). A simplified model of a transmon qubit coupled to a cavity resonator is used to demonstrate a quantum circuit. We analyzed the circuit through its equivalent two-mode lumped-element representation of the distributed circuit and derived the equivalent Hamiltonian translation of the circuit with the non-linearity of the Josephson Junctions. We adopted the parametrized qubit junctions and used the component physical value to tune the circuits to maximize the fidelity of the desired entangle state and the resulting quantum circuit state. However, quantum systems are susceptible to environmental parasitics and noise; therefore, a reliable optimization technique is essential to maintain high fidelity across the system. For optimization, we integrate deep reinforcement learning using deep deterministic policy gradient techniques as our mechanism for our AI module to optimize the fidelity of the superconducting quantum circuit. We demonstrate the feasibility of this approach by training the agent in three distinct environments to achieve the highest possible best rewards. We achieved an average fidelity (best rewards) of 0.92, which is 94% of the statically tuned circuit.
                  • Article
                  • Peer Reviewed
                  UC Irvine Previously Published Works (2013)
                  Traditional Chinese Medicine (TCM) is a complete medical system that has been practiced for more than 3000 years. Prescription number 1 (PN-1) consists of several Chinese medicines and is designed according to TCM theories to treat patients with neuropsychiatric disorders. The evidence of clinical practice suggests the benefit effects of PN-1 on cognitive deficits of dementia patients. We try to prove and explain this by using contemporary methodology and transgenic animal models of Alzheimer's disease (AD). The behavioral studies were developed to evaluate the memory of transgenic animals after intragastric administration of PN-1 for 3 months. Amyloid beta-protein (A β ) neuropathology was quantified using immunohistochemistry and ELISA. The western blotting was used to detect the levels of plasticity associated proteins. The safety of PN-1 on mice was also assessed through multiple parameters. Results showed that PN-1 could effectively relieve learning and memory impairment of transgenic animals. Possible mechanisms showed that PN-1 could significantly reduce plaque burden and A β levels and boost synaptic plasticity. Our observations showed that PN-1 could improve learning and memory ability through multiple mechanisms without detectable side effects on mice. We propose that PN-1 is a promising alternative treatment for AD in the future.
                    Cover page: The effect of PN-1, a Traditional Chinese Prescription, on the Learning and Memory in a Transgenic Mouse Model of Alzheimer’s Disease
                    • Article
                    • Peer Reviewed
                    UC Berkeley Previously Published Works (2024)
                    Spin waves in magnetic materials are promising information carriers for future computing technologies due to their ultra-low energy dissipation and long coherence length. Antiferromagnets are strong candidate materials due, in part, to their stability to external fields and larger group velocities. Multiferroic antiferromagnets, such as BiFeO3 (BFO), have an additional degree of freedom stemming from magnetoelectric coupling, allowing for control of the magnetic structure, and thus spin waves, with the electric field. Unfortunately, spin-wave propagation in BFO is not well understood due to the complexity of the magnetic structure. In this work, long-range spin transport is explored within an epitaxially engineered, electrically tunable, 1D magnonic crystal. A striking anisotropy is discovered in the spin transport parallel and perpendicular to the 1D crystal axis. Multiscale theory and simulation suggest that this preferential magnon conduction emerges from a combination of a population imbalance in its dispersion, as well as anisotropic structural scattering. This work provides a pathway to electrically reconfigurable magnonic crystals in antiferromagnets.
                      Cover page: Designed Spin‐Texture‐Lattice to Control Anisotropic Magnon Transport in AntiferromagnetsCreative Commons 'BY' version 4.0 license
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