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All sources NASA NTRS DOE OSTI

DOE OSTI2022

Deep Learning and Natural Language Processing for Accelerated Inverse Design of Optical Metamaterials

Optical metamaterial device design has enjoyed a long track of success over the past 50 years leading to the manipulation of light over a wide range of wavelengths spanning the ultraviolet to the far infrared. The manipulation of light over such wavelengths has already led to many technological advancements such as the design of selective radiative absorbers for solar energy, daytime passive cooling using deep space, and optical invisibility cloaks for defense applications. Further disruptive advancements in energy, defense, computing, and biomedical fields could be enabled or enhanced by future optical metamaterial devices. These technologies could lead to increased energy efficiency and hence reduced national primary energy consumption, cheap long duration energy storage, and next generation solid-state heat engines. But historically the methods to invent and develop all of these devices have been time- consuming and based mostly on intuition and iteration. Finding an optimal design can take years. In this project we developed a machine learning-based algorithm capable of automatically generating device designs to produce desired optical properties, reducing the design cycle life in certain situations to be almost instantaneous.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Deep Learning and Natural Language Processing for Accelerated Inverse Design of Optical Metamaterials

36 MATERIALS SCIENCE↗

DOE OSTI2023

Physics‐Informed Machine Learning for Inverse Design of Optical Metamaterials

Optical metamaterials manipulate light through various confinement and scattering processes, offering unique advantages like high performance, small form factor and easy integration with semiconductor devices. However, designing metasurfaces with suitable optical responses for complex metamaterial systems remains challenging due to the exponentially growing computation cost and the ill‐posed nature of inverse problems. To expedite the computation for the inverse design of metasurfaces, a physics‐informed deep learning (DL) framework is used. A tandem DL architecture with physics‐based learning is used to select designs that are scientifically consistent, have low error in design prediction, and accurate reconstruction of optical responses. The authors focus on the inverse design of a representative plasmonic device and consider the prediction of design for the optical response of a single wavelength incident or a spectrum of wavelength in the visible light range. The physics‐based constraint is derived from solving the electromagnetic wave equations for a simplified homogenized model. The model converges with an accuracy up to 97% for inverse design prediction with the optical response for the visible light spectrum as input, and up to 96% for optical response of single wavelength of light as input, with optical response reconstruction accuracy of 99%.

Sarkar, Sulagna↗

DOE OSTI2024

Quantum annealing-aided design of an ultrathin-metamaterial optical diode

Abstract Thin-film optical diodes are important elements for miniaturizing photonic systems. However, the design of optical diodes relies on empirical and heuristic approaches. This poses a significant challenge for identifying optimal structural models of optical diodes at given wavelengths. Here, we leverage a quantum annealing-enhanced active learning scheme to automatically identify optimal designs of 130 nm-thick optical diodes. An optical diode is a stratified volume diffractive film discretized into rectangular pixels, where each pixel is assigned to either a metal or dielectric. The proposed scheme identifies the optimal material states of each pixel, maximizing the quality of optical isolation at given wavelengths. Consequently, we successfully identify optimal structures at three specific wavelengths (600, 800, and 1000 nm). In the best-case scenario, when the forward transmissivity is 85%, the backward transmissivity is 0.1%. Electromagnetic field profiles reveal that the designed diode strongly supports surface plasmons coupled across counterintuitive metal–dielectric pixel arrays. Thereby, it yields the transmission of first-order diffracted light with a high amplitude. In contrast, backward transmission has decoupled surface plasmons that redirect Poynting vectors back to the incident medium, resulting in near attenuation of its transmission. In addition, we experimentally verify the optical isolation function of the optical diode.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Plasmonic gold-cellulose nanofiber aerogels

Assembly of plasmonic nanomaterials into a low refractive index medium, such as an aerogel, holds a great promise for optical metamaterials, optical sensors, and photothermal energy converters. However, conventional plasmonic aerogels are opaque and optically isotropic composites, impeding them from being used as low-loss or polarization-dependent optical materials. Here we demonstrate a plasmonic-cellulose nanofiber composite aerogel that comprises of well-dispersed gold nanorods within a cellulose nanofiber network. The cellulose aerogel host is highly transparent owing to the small scattering cross-section of the nanofibers and forms a nematic liquid crystalline medium with strong optical birefringence. We find that the longitudinal surface plasmon resonance peak of gold nanorods shows a dramatic shift when probed for the cellulose aerogel compared with the wet gels. Simulations reveal the shift of surface plasmon resonance peak with gel drying can be attributed to the change of the effective refractive index of the gels. This composite material may provide a platform for three- dimensional plasmonic devices ranging from optical sensors to metamaterials.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Deep Optical Switching on Subpicosecond Timescales in an Amorphous Ge Metamaterial

Active nanostructured optical components show promise as potential building blocks for novel light-based computing and data processing architectures. However, nanoscale all-optical switches that have low activation powers and high-contrast ultrafast switching have been elusive so far. Here, pump–probe measurements performed on amorphous-Ge-based micro-resonator metasurfaces that exhibit strong resonant modes in the mid-infrared are reported. Relative change is observed in transmittance of ΔT/T ≈ 1 with picosecond (down to τ ≈ 0.5 ps) free carrier relaxation rates, obtained with very low pump fluences of 50 μJ cm –2 . In this work, these observations are attributed to efficient free carrier promotion, affecting light transmittance via high quality-factor optical resonances, followed by an increased electron–phonon scattering of free carriers due to the amorphous crystal structure of Ge. Full-wave simulations based on a permittivity model that describes free-carrier damping through crystal structure disorder find excellent agreement with the experimental data. These findings offer an efficient and robust platform for all-optical switching at the nanoscale.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Anisotropic optical and magnetic response in self-assembled TiN–CoFe 2 nanocomposites

Transition metal nitrides (e.g., TiN) have shown tremendous promise in optical metamaterials for nanophotonic devices due to their plasmonic properties comparable to noble metals and superior high temperature stability. Vertically aligned nanocomposites (VANs) offer a great platform for combining two dissimilar functional materials with a one-step deposition technique toward multifunctionality integration and strong structural/property anisotropy. Here, we report a two-phase nanocomposite design combining ferromagnetic CoFe 2 nanosheets in the plasmonic TiN matrix as a new hybrid plasmonic metamaterial. The hybrid metamaterials exhibit anisotropic optical and magnetic responses, as well as a pronounced magneto-optical coupling response evidenced by Magneto-optic Kerr Effect measurement, owing to the novel vertically aligned structure. This work demonstrates a new TiN-based metamaterial with anisotropic properties and multifunctionality toward light polarization modulation, optical switching, and integrated optics.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Helical Photonic Metamaterials for Encrypted Chiral Holograms

Helical structures are among the most quintessential three-dimensional (3D) forms that exhibit mirror asymmetry, a hallmark of chirality. Various structural parameters of helices directly linked to chiroptical properties highlight their importance as essential optical metamaterials for polarization-resolved sensors, imaging, and spectroscopies. However, such function-defining properties remain incompletely understood due to fabrication challenges and the lack of a relationship between structure and optical properties. Here, helical structures are analyzed parametrically, and correlations are established that are applicable to the design of chiral helical optical metamaterials. By systematically varying independent parameters—such as from single-turn to five-turn helices and from small major radii to larger ones optimized to fit the unit cell—the underlying relationships with ellipticty are revealed. In addition to theoretical modeling, the findings are experimentally validated using 3D printing and terahertz spectroscopy. The results demonstrate that optimized helical structures are mechanically tunable and exhibit unprecedented optical properties, including broadband and high-magnitude ellipticity spectra. Being embedded in soft elastomers, helical arrays can serve as soft, stretchable optical-mechanical sensors and holograms containing encoded information, such as barcodes and quick response (QR) codes. Chiral QR codes are realized using pixelated single helices with different handedness, demonstrating their potential as advanced encryption/decryption systems for security applications and chiral metaholograms.

Encrypted QR codes↗

DOE OSTI2021

Co-Design of Free-Space Metasurface Optical Neuromorphic Classifiers for High Performance

Classification of features in a scene typically requires conversion of the incoming photonic field into the electronic domain. Recently, an alternative approach has emerged whereby passive structured materials can perform classification tasks by directly using free-space propagation and diffraction of light. In this manuscript, we present a theoretical and computational study of such systems and establish the basic features that govern their performance. We show that system architecture, material structure, and input light field are intertwined and need to be co-designed to maximize classification accuracy. Our simulations show that a single layer metasurface can achieve classification accuracy better than conventional linear classifiers, with an order of magnitude fewer diffractive features than previously reported. For a wavelength λ, single layer metasurfaces of size 100λ × 100λ with an aperture density λ –2 achieve ~96% testing accuracy on the MNIST data set, for an optimized distance ~100λ to the output plane. This is enabled by an intrinsic nonlinearity in photodetection, despite the use of linear optical metamaterials. Furthermore, we find that once the system is optimized, the number of diffractive features is the main determinant of classification performance. The slow asymptotic scaling with the number of apertures suggests a reason why such systems may benefit from multiple layer designs. Finally, we show a trade-off between the number of apertures and fabrication noise.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Light–matter coupling in large-area van der Waals superlattices

Two-dimensional (2D) crystals have renewed opportunities in design and assembly of artificial lattices without the constraints of epitaxy. However, the lack of thickness control in exfoliated van der Waals (vdW) layers prevents realization of repeat units with high fidelity. Recent availability of uniform, wafer-scale samples permits engineering of both electronic and optical dispersions in stacks of disparate 2D layers with multiple repeating units. In this study, we present optical dispersion engineering in a superlattice structure comprising alternating layers of 2D excitonic chalcogenides and dielectric insulators. By carefully designing the unit cell parameters, we demonstrate greater than 90% narrow band absorption in less than 4 nm of active layer excitonic absorber medium at room temperature, concurrently with enhanced photoluminescence in square-centimetre samples. These superlattices show evidence of strong light–matter coupling and exciton–polariton formation with geometry-tuneable coupling constants. Our results demonstrate proof of concept structures with engineered optical properties and pave the way for a broad class of scalable, designer optical metamaterials from atomically thin layers.

2D Crystals↗

DOE OSTI2020

Morphology Control of Self-Assembled Three-Phase Au-BaTiO 3 –ZnO Hybrid Metamaterial for Tunable Optical Properties

Microstructural control in metal-dielectric hybrid metamaterials presents enormous opportunities in tailoring the physical properties including the magnetic and optical properties. In this paper, we demonstrate a strong tunability achieved in the microstructure of self-assembled ordered three-phase Au-BaTiO 3 –ZnO hybrid metamaterial along with its optical properties, grown by a pulsed laser deposition method. Varying the growth temperature, deposition frequency, and template thickness evolves the microstructure by tuning the Au and ZnO pillar geometry as well as the shape and size of the Au nanoparticles capping the ZnO nanowires. The three-phase hybrid metamaterials exhibit unique optical properties, including enhanced nonlinear optical properties, hyperbolic dispersion in the visible and near-infrared wavelength region, and tuned epsilon-near-zero (ENZ) wavelength upon varying the deposition parameters. This study suggests that the three-phase hybrid metamaterials present great potential in the microstructure and optical property tuning that can also be applied to other two-phase and three-phase nanocomposite systems.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Mie-Resonant Three-Dimensional Metacrystals

Optical metamaterials, engineered to exhibit electromagnetic properties not found in natural materials, may enable new light-based applications including cloaking and optical computing. While there have been significant advances in the fabrication of two-dimensional metasurfaces, planar structures create nontrivial angular and polarization sensitivities, making omnidirectional operation impossible. Although three-dimensional (3D) metamaterials have been proposed, their fabrication remains challenging. In this work, we use colloidal crystal engineering with DNA to prepare isotropic 3D metacrystals from Au nanocubes. We show that such structures can exhibit refractive indices as large as ~8 in the mid-infrared, far greater than that of common high-index dielectrics. Additionally, we report the first observation of multipolar Mie resonances in metacrystals with well-formed habits, occurring in the mid-infrared for sub-micron metacrystals, which we measured using synchrotron infrared microspectroscopy. Finally, we predict that arrays of metacrystals could exhibit negative refraction. The results present a promising platform for engineering devices with unnatural optical properties.

3D metamaterials↗

DOE OSTI2022

Altering apparent optical properties with an array of semitransparent mesoscale structures

The ability to control and optimize interactions between light and matter has much utility in engineering design. A well-researched way to achieve optical property modulation is via the use of optical metamaterials, which feature sub-wavelength scale surface structures. In this work, an alternative approach for modulating optical properties is presented using a composite surface modified with a periodic array of semitransparent hemispherical shell mesoscale structures which are larger than the incident light wavelength. A ray-tracing simulation approach is used to predict the optical behavior for an arrayed surface. At oblique angles of incidence, significant increases and decreases in apparent absorptance are achieved via the use of optically thick and thin shells, respectively. Additionally, a potential application to solar cells is described with optimal spectral behavior achieved via the use of semitransparent external structures.

Kucuktas, Onur A.↗

DOE OSTI2023

Decoding the Atomic Structure of Ga 2 Te 5 Pulsed Laser Deposition Films for Memory Applications Using Diffraction and First-Principles Simulations

Neuromorphic computing, reconfigurable optical metamaterials that are operational over a wide spectral range, holographic and nonvolatile displays of extremely high resolution, integrated smart photonics, and many other applications need next-generation phase-change materials (PCMs) with better energy efficiency and wider temperature and spectral ranges to increase reliability compared to current flagship PCMs, such as Ge 2 Sb 2 Te 5 or doped Sb 2 Te. Gallium tellurides are favorable compounds to achieve the necessary requirements because of their higher melting and crystallization temperatures, combined with low switching power and fast switching rate. Ga 2 Te 3 and non-stoichiometric alloys appear to be atypical PCMs; they are characterized by regular tetrahedral structures and the absence of metavalent bonding. The sp 3 gallium hybridization in cubic and amorphous Ga 2 Te 3 is also different from conventional p-bonding in flagship PCMs, raising questions about its phase-change mechanism. Furthermore, gallium tellurides exhibit a number of unexpected and highly unusual phenomena, such as nanotectonic compression and viscosity anomalies just above their melting points. Using high-energy X-ray diffraction, supported by first-principles simulations, we will elucidate the atomic structure of amorphous Ga 2 Te 5 PLD films, compare it with the crystal structure of tetragonal gallium pentatelluride, and investigate the electrical, optical, and thermal properties of these two materials to assess their potential for memory applications, among others.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Atomic Structure and Dynamics of Unusual and Wide-Gap Phase-Change Chalcogenides: A GeTe 2 Case

Brain-inspired computing, reconfigurable optical metamaterials, photonic tensor cores, and many other advanced applications require next-generation phase-change materials (PCMs) with better energy efficiency and a wider thermal and spectral range for reliable operations. Germanium ditelluride (GeTe 2 ), with higher thermal stability and a larger bandgap compared to current benchmark PCMs, appears promising for THz metasurfaces and the controlled crystallization of atomically thin 2D materials. Using high-energy X-Ray diffraction supported by first-principles simulation, the atomic structure in semiconducting pulsed laser deposition films and metallic high-temperature liquids is investigated. The results suggest that the structural and chemical metastability of GeTe 2 , leading to disproportionation into GeTe and Te, is related to high internal pressure during a semiconductor–metal transition, presumably occurring in the supercooled melt. Similar phenomena are expected for canonical GeS 2 and GeSe 2 under high temperatures and pressures.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2021

Babinet's principle and saturation of the resonance frequency of scaled-down complementary metasurfaces

It has been previously demonstrated that the resonant frequency of the Split Ring Resonator (SRR) reaches a saturation value when its size is continuously scaled down, and at the same time, the resonance is attenuated. Now, it is demonstrated that similar saturation and attenuation phenomena happens to its complementary screen, which is commonly called a Complementary SRR (CSRR). It was found that the saturation frequency of the CSRR is near the saturation frequency of the SRR with equal geometrical dimensions. It is possible to control their saturation levels by tuning the geometry of the resonators. This work is relevant for the design of quasi-optical metamaterials based on one or both kinds of structures (i.e., SRRs and CSRRs) at once, especially when they both are required to resonate at the same frequency.

Ortiz, Julián D. (ORCID:0000000248056148)↗

DOE OSTI2024

Inverse design of a pyrochlore lattice of DNA origami through model-driven experiments

Sophisticated statistical mechanics approaches and human intuition have demonstrated the possibility of self-assembling complex lattices or finite-size constructs. However, attempts so far have mostly only been successful in silico and often fail in experiment because of unpredicted traps associated with kinetic slowing down (gelation, glass transition) and competing ordered structures. Theoretical predictions also face the difficulty of encoding the desired interparticle interaction potential with the experimentally available nano- and micrometer-sized particles. To overcome these issues, we combine SAT assembly (a patchy-particle interaction design algorithm based on constrained optimization) with coarse-grained simulations of DNA nanotechnology to experimentally realize trap-free self-assembly pathways. In this paper, we use this approach to assemble a pyrochlore three-dimensional lattice, coveted for its promise in the construction of optical metamaterials, and characterize it with small-angle x-ray scattering and scanning electron microscopy visualization.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2022

Neuromorphic Information Processing by Optical Media

Classification of features in a scene typically requires conversion of the incoming photonic field int the electronic domain. Recently, an alternative approach has emerged whereby passive structured materials can perform classification tasks by directly using free-space propagation and diffraction of light. In this manuscript, we present a theoretical and computational study of such systems and establish the basic features that govern their performance. We show that system architecture, material structure, and input light field are intertwined and need to be co-designed to maximize classification accuracy. Our simulations show that a single layer metasurface can achieve classification accuracy better than conventional linear classifiers, with an order of magnitude fewer diffractive features than previously reported. For a wavelength λ, single layer metasurfaces of size 100λ x 100λ with aperture density λ -2 achieve ~96% testing accuracy on the MNIST dataset, for an optimized distance ~100λ to the output plane. This is enabled by an intrinsic nonlinearity in photodetection, despite the use of linear optical metamaterials. Furthermore, we find that once the system is optimized, the number of diffractive features is the main determinant of classification performance. The slow asymptotic scaling with the number of apertures suggests a reason why such systems may benefit from multiple layer designs. Finally, we show a trade-off between the number of apertures and fabrication noise.

47 OTHER INSTRUMENTATION↗