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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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We present metamaterial-like aerogels that provide broadband low-frequency vibration mitigation through their self-assembled locally resonant microstructures. Simulations confirm the presence of a negative dynamic stiffness for the aerogels.
We place metamaterials in the context of underpinning physical phenomena, including negative refraction, bandgaps, wave focusing, and negative Poisson’s ratio. The designs, mechanisms, governing equations, and effective parameters are discussed.
Metamaterials present great potential in the applications of solar cells and nanophotonics, such as super lenses and other meta devices, owing to their superior optical properties.
We show that sub-wavelength nanostructured systems with tunable electromagnetic properties, such as hyperbolic metamaterials (HMMs), provide a useful platform to tailor spontaneous emission processes. Here, we investigate a system comprising Eu 3+ (NO 3 ) 3 ·6H 2 O nanocrystals on an HMM structure featuring a hexagonal array of Ag nanowires in a porous Al2O 3 matrix. The HMM-coupled Eu 3+ ions exhibit up to a 2.4 fold increase in their decay rate, accompanied by an enhancement of the emission rate of the 5 D 0 → 7 F 2 transition. Using finite-difference time-domain modeling, we corroborate these observations with the increase in the photonic density of states seen by the Eu 3+ ions in the proximity of the HMM. Our results indicate that HMMs can serve as a valuable tool to control the emission from weak transitions and, hence, hint at a route toward more practical applications of rare-earth ions in nanoscale optoelectronics and quantum devices.
Significance Plasmons, collective electron density oscillations in metals or doped semiconductors, provide an efficient way to couple light and matter at subwavelength scales. Usually, plasmons are carrier density ( n ) dependent, which may cause unstable functionalities of plasmons, especially for cutting-edge terahertz technology. Here, we reveal a unified mechanism for generating unusual n -independent plasmons (DIPs), where terahertz DIPs can be excited in some low-dimensional topological semimetals. Stable terahertz spectroscopy from narrowband to broadband and even a quantization can be achieved in topological metamaterials. Our study not only broadens the concept of plasmons by combining with exotic topological states but also paves a way to designing a compact device for stable terahertz applications.
The adaptive and surprising emergent properties of biological materials self-assembled in far-from-equilibrium environments serve as an inspiration for efforts to design nanomaterials. In particular, controlling the conditions of self-assembly can modulate material properties, but there is no systematic understanding of either how to parameterize external control or how controllable a given material can be. Here, we demonstrate that branched actin networks can be encoded with metamaterial properties by dynamically controlling the applied force under which they grow and that the protocols can be selected using multi-task reinforcement learning. These actin networks have tunable responses over a large dynamic range depending on the chosen external protocol, providing a pathway to encoding “memory” within these structures. Interestingly, we obtain a bound that relates the dissipation rate and the rate of “encoding” that gives insight into the constraints on control—both physical and information theoretical. Taken together, these results emphasize the utility and necessity of nonequilibrium control for designing self-assembled nanostructures.
A new regime in radiofrequency (rf) breakdown, named the breakdown insensitive acceleration regime (BIAR), was observed in an 11.7 GHz metamaterial structure for wakefield acceleration driven by rf pulses with a duration of a few nanoseconds. In the BIAR, rf breakdown occurs without interrupting potential beam acceleration, resulting in greater resilience to breakdown. We have investigated the possibility that BIAR can support higher gradients by characterizing the breakdown in a high-power test. The peak gradient reached 190 MV / m when the structure was powered by 6 ns long rf pulses with 115 MW peak power. The short rf pulses were extracted from 65 MeV electron bunch trains with a total charge of up to 210 nC. This work has revealed the benefits of short-pulse acceleration by characterizing rf breakdown in the previously unexplored parameter space. Published by the American Physical Society 2024
Symmetries crucially underlie the classification of topological phases of matter. Most materials, both natural as well as architectured, possess crystalline symmetries. Recent theoretical works unveiled that these crystalline symmetries can stabilize fragile Bloch bands that challenge our very notion of topology: Although answering to the most basic definition of topology, one can trivialize these bands through the addition of trivial Bloch bands. Here, we fully characterize the symmetry properties of the response of an acoustic metamaterial to establish the fragile nature of the low-lying Bloch bands. Additionally, we present a spectral signature in the form of spectral flow under twisted boundary conditions.
Synthesizing many-body quantum systems with various ranges of interactions facilitates the study of quantum chaotic dynamics. Such extended interaction range can be enabled by using nonlocal degrees of freedom such as photonic modes in an otherwise locally connected structure. Here, we present a superconducting quantum simulator in which qubits are connected through an extensible photonic-bandgap metamaterial, thus realizing a one-dimensional Bose-Hubbard model with tunable hopping range and on-site interaction. Using individual site control and readout, we characterize the statistics of measurement outcomes from many-body quench dynamics, which enables in situ Hamiltonian learning. Further, the outcome statistics reveal the effect of increased hopping range, showing the predicted crossover from integrability to ergodicity. Our work enables the study of emergent randomness from chaotic many-body evolution and, more broadly, expands the accessible Hamiltonians for quantum simulation using superconducting circuits.
Terahertz (THz) waves have gained considerable attention in the rising 6G communication due to their large bandwidth. However, the cost and power consumption become the major constraints for the commercialization of 6G THz systems as the frequency increases. Reconfigurable intelligent surface (RIS) comprising active metasurfaces and digital controllers has been proposed for beamforming in the 6G multiple-input-multiple-output systems, showing good potential to suppress the system size, weight, and power consumption (SWaP). Currently, their controlling diodes can hardly work up to THz frequencies. Therefore, several active stimuli have been investigated as alternatives. Among them, chalcogenide phase-change material Ge 2 Sb 2 Te 5 (GST) addresses large modulation depth, picosecond switching speed, and non-volatile properties. Notably, the non-volatile GST may enable RIS systems with memory and low control power. This work briefly reviews the advances of GST-tuned THz metamaterials (MTMs), discusses the current obstacles to overcome, and gives a perspective of GST applications in the rising 6G communications.
Abstract We demonstrate transfer learning as a tool to improve the efficacy of training deep learning models based on residual neural networks (ResNets). Specifically, we examine its use for study of multi-scale electrically large metasurface arrays under open boundary conditions in electromagnetic metamaterials. Our aim is to assess the efficiency of transfer learning across a range of problem domains that vary in their resemblance to the original base problem for which the ResNet model was initially trained. We use a quasi-analytical discrete dipole approximation (DDA) method to simulate electrically large metasurface arrays to obtain ground truth data for training and testing of our deep neural network. Our approach can save significant time for examining novel metasurface designs by harnessing the power of transfer learning, as it effectively mitigates the pervasive data bottleneck issue commonly encountered in deep learning. We demonstrate that for the best case when the transfer task is sufficiently similar to the target task, a new task can be effectively trained using only a few data points yet still achieve a test mean absolute relative error of 3 % with a pre-trained neural network, realizing data reduction by a factor of 1000.
Structural health monitoring of an engineered component in a harsh environment is critical for multiple DOE missions including nuclear fuel cycle, subsurface energy production/storage, and energy conversion. Supported by a seeding Laboratory Directed Research & Development (LDRD) project, we have explored a new concept for structural health monitoring by introducing a self-sensing capability into structural components. The concept is based on two recent technological advances: metamaterials and additive manufacturing. A self-sensing capability can be engineered by embedding a metastructure, for example, a sheet of electromagnetic resonators, either metallic or dielectric, into a material component. This embedment can now be realized using 3-D printing. The precise geometry of the embedded metastructure determines how the material interacts with an incident electromagnetic wave. Any change in the structure of the material (e.g., straining, degradation, etc.) would inevitably perturbate the embedded metastructures or metasurface array and therefore alter the electromagnetic response of the material, thus resulting in a frequency shift of a reflection spectrum that can be detected passively and remotely. This new sensing approach eliminates complicated environmental shielding, in-situ power supply, and wire routing that are generally required by the existing active-circuit-based sensors. The work documented in this report has preliminarily demonstrated the feasibility of the proposed concept. The work has established the needed simulation tools and experimental capabilities for future studies.
We performed large scale molecular dynamics (MD) simulations and reactive & quantum molecular dynamics simulations to investigate: (1) faceting, grain growth, and crack healing in ceramics; (2) stress-release mechanism and healing in fibers; and (3) mechanical properties of two-dimensional metamaterials. We also designed highly accurate interatomic potentials and forces using artificial neural networks (ANN) and first-principles molecular dynamics simulation data for use in our MD and reactive MD simulations. We demonstrated the efficacy of modeling quantum materials atomistic simulation data using unsupervised deep learning approaches on a quantum computer. These achievements are elaborated in the following sections.
This project conducted a modeling study on seismic invisibility cloaks that render geologic targets invisible to seismic waves, using the concept of seismic metamaterials. We present a parametric numerical study on the behaviors of seismic waves through cloaks with different design parameters as well as degrees of geologic heterogeneity. In addition, a seismic cloaking strategy is proposed for a future field-scale experiment at a real-world test bed. This feasibility study will guide future field experiment designs and ultimately allow us to conduct systematic field-scale tests employing Sandia’s existing resources and field expertise. The ultimate goal is to develop methods and design parameters of seismic invisibility cloaks to protect against natural and man-made seismic waves. Seismic cloaking has potential applications in several areas of national security, energy, and natural hazard reduction.
The objective of the project was to develop and validate monolithic mesoporous metamaterials (MMMs), to which we also refer as Mesoporous Optically Clear Heat Insulators (MOCHIs) capable of serving as High-thermal-barrier Glazing (including Windows, Skylights, and Daylighting) with Transparency ≥99%, Color Rendering Index ≥99%, Haze ≤1%, Thermal Insulation per inch ≥R-15, Manufacturing Cost per Square Foot ≤$0.3; In addition, MMM-Based Frame Insulation and Glazing Products with Thermal Insulation per inch R-10 to R-15. All objectives of the project were successfully accomplished.
ZnO-Au nanocomposite thin films have been previously reported as hybrid metamaterials with unique optical properties such as plasmonic resonance properties and hyperbolic behaviors. In this study, Au composition in the ZnO-Au nanocomposites has been effectively tuned by target composition variation and thus resulted in microstructure and optical property tuning. Specifically, all the ZnO-Au nanocomposite thin films grown through the pulsed laser deposition (PLD) method show obvious vertically aligned nanocomposite (VAN) structure with the Au nanopillars embedded in the ZnO matrix. Moreover, the average diameter of Au nanopillars increases as Au concentration increases, which also leads to the redshifts in the surface plasmon resonance (SPR) wavelength and changes in the hyperbolic behaviors of the films. As a whole, this work discusses how strain-driven tuning of optical properties and microstructure resulted through a novel Au concentration variation approach which has not been previously attempted in the ZnO-Au thin film system. These highly ordered films present great promise in the areas of sensing, waveguides, and nanophotonics to name a few.
Metamaterials (MTMs) are structured materials with subwavelength features that can be engineered to have some unique properties not found in nature, such as negative refractive index, reversed Doppler effect, and reversed Cherenkov radiation. Based on these novel MTMs, several important research groups have made great attempts to develop novel MTM-inspired vacuum electron devices (VEDs) and accelerators. Just as solid-state power devices are innovated by incessant emerging of new semiconductor materials, VEDs can also be inspired by MTMs to have very remarkable advantages, such as smaller size, higher power, higher efficiency, and/or larger gain relative to conventional VEDs, such as traveling-wave tubes, backward-wave oscillators, and klystrons. Similarly, relative to conventional accelerators, MTM-inspired accelerators have obvious advantages, such as smaller size and higher accelerating gradient. Furthermore, MTM-inspired devices have promising applications in areas such as radar, communication, electronic warfare, microwave heating, and imaging.
Polarization control plays a vital role in terahertz (THz) photonics, enabling a wide range of applications from imaging and spectroscopy to sensing and wireless communication. However, conventional polarization control methods at THz frequencies are limited by narrow operational bandwidths and excessive absorption losses. In this work, we present a broadband THz polarization control based on the polarization guiding effect. We design and fabricate a THz polarization rotator capable of rotating incident linear polarization by 90°. The device consists of 24 twistingly stacked silicon–air metagrating layers that introduce a large degree of form birefringence, with each metagrating layer being 280 µm thick and sequentially twisted by 3.75°. Numerical simulations using the Berreman 4 × 4 method predict broadband operation of the device. Experimental validation using THz time-domain spectroscopy confirms efficient and broadband 90° polarization rotation from 0.2 to 1.25 THz. Based on this concept, we further propose THz Q-plates for the generation of broadband structured vector beams with radial and azimuthal polarization states. This work offers a scalable, material-agnostic platform for advanced THz polarization manipulation and vector beam engineering, opening new pathways for next-generation THz photonic devices.