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Register a new userUltra-thin yttria-stabilized zirconia as a flexible and stable substrate for infrared nano-optics
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Added by
Kavitha Kalavoor Gopalan
Publication date
2019
fields
Physics
and research's language is
English
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Infrared (IR) technologies have become increasingly relevant as they offer a wide range of applications, from thermal imaging to chemical and biological vibrational spectroscopy. Substrate materials, such as calcium fluoride and zinc selenide, are commonly used for IR optics. Unfortunately, they are typically fragile, hygroscopic and expensive, thus producing potential problems during device fabrication and in the long-term functional operation. Here, we introduce yttria-stabilized zirconia (YSZ) ceramic as a flexible and stable platform to implement next generation IR nano-optic devices. In particular, we have combined YSZ with metallic nano-structures and graphene to demonstrate new plasmonics, polarizers and transparent heating substrates. The proposed YSZ-based platforms enable high temperature processing that also withstand harsh environments because of its excellent mechanical, thermal and chemical stability. In addition to the functional capability of making foldable and bendable devices, the demonstrated mechanical flexibility offers the possibility of roll-to-roll processing for low cost and large scale fabrication processes. Our work offers compelling evidence that ultrathin YSZ is a unique substrate for IR applications, given all the combined features, including mechanical flexibility, durability, transparency and easy processing, which are not available from other available material alternatives.
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We have succeeded in growing epitaxial and highly stoichiometric films of EuO on yttria-stabilized cubic zirconia (YSZ) (001). The use of the Eu-distillation process during the molecular beam epitaxy assisted growth enables the consistent achievement of stoichiometry. We have also succeeded in growing the films in a layer-by-layer fashion by fine tuning the Eu vs. oxygen deposition rates. The initial stages of growth involve the limited supply of oxygen from the YSZ substrate, but the EuO stoichiometry can still be well maintained. The films grown were sufficiently smooth so that the capping with a thin layer of aluminum was leak tight and enabled ex situ experiments free from trivalent Eu species. The findings were used to obtain recipes for better epitaxial growth of EuO on MgO (001).
Multilayered heterostructures of Ce0.85Sm0.15O2-delta and Y0.16Zr0.92O2-delta of a high crystallographic quality were fabricated on (001) - oriented MgO single crystal substrates. Keeping the total thickness of the heterostructures constant, the number of ceria-zirconia bilayers was increased while reducing the thickness of each layer. At each interface Ce was found primarily in the reduced, 3+ oxidation state in a layer extending about 2 nm from the interface. Concurrently, the conductivity decreased as the thickness of the layers was reduced suggesting a progressive confinement of the charge transport along the YSZ layers. The comparative analysis of the in-plane electrical characterization suggests that the contribution to the total electrical conductivity of these interfacial regions is negligible. For the smallest layer thickness of 2 nm the doped ceria layers are electrically insulating and the ionic transport only occurs through the zirconia layers. This is explained in terms of a reduced mobility of the oxygen vacancies in the highly reduced ceria.
Voltage control of interfacial magnetism has been greatly highlighted in spintronics research for many years, as it might enable ultra-low power technologies. Among few suggested approaches, magneto-ionic control of magnetism has demonstrated large modulation of magnetic anisotropy. Moreover, the recent demonstration of magneto-ionic devices using hydrogen ions presented relatively fast magnetization toggle switching, tsw ~ 100 ms, at room temperature. However, the operation speed may need to be significantly improved to be used for modern electronic devices. Here, we demonstrate that the speed of proton-induced magnetization toggle switching largely depends on proton-conducting oxides. We achieve ~1 ms reliable (> 103 cycles) switching using yttria-stabilized zirconia (YSZ), which is ~ 100 times faster than the state-of-the-art magneto-ionic devices reported to date at room temperature. Our results suggest further engineering of the proton-conducting materials could bring substantial improvement that may enable new low-power computing scheme based on magneto-ionics.
Additive manufacturing represents a revolution due to its unique capabilities for freeform fabrication of near net shapes with strong reduction of waste material and capital cost. These unfair advantages are especially relevant for expensive and energy-demanding manufacturing processes of advanced ceramics such as Yttria-stabilized Zirconia, the state-of-the-art electrolyte in Solid Oxide Fuel Cell applications. In this study, self-supported electrolytes of yttria-stabilized zirconia have been printed by using a stereolithography three-dimensional printer. Printed electrolytes and complete cells fabricated with cathode and anode layers of lanthanum strontium manganite- and nickel oxide-yttria-stabilized zirconia composites, respectively, were electrochemical characterized showing full functionality. In addition, more complex configurations of the electrolyte have been printed yielding an increase of the performance entirely based on geometrical aspects. Complementary, a numerical model has been developed and validated as predictive tool for designing more advanced configurations that will enable highly performing and fully customized devices in the next future
Nano-optic imagers that modulate light at sub-wavelength scales could unlock unprecedented applications in diverse domains ranging from robotics to medicine. Although metasurface optics offer a path to such ultra-small imagers, existing methods have achieved image quality far worse than bulky refractive alternatives, fundamentally limited by aberrations at large apertures and low f-numbers. In this work, we close this performance gap by presenting the first neural nano-optics. We devise a fully differentiable learning method that learns a metasurface physical structure in conjunction with a novel, neural feature-based image reconstruction algorithm. Experimentally validating the proposed method, we achieve an order of magnitude lower reconstruction error. As such, we present the first high-quality, nano-optic imager that combines the widest field of view for full-color metasurface operation while simultaneously achieving the largest demonstrated 0.5 mm, f/2 aperture.
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