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Abstract Materials with field-tunable polarization are of broad interest to condensed matter sciences and solid-state device technologies. Here, using hydrogen (H) donor doping, we modify the room temperature metallic phase of a perovskite nickelate NdNiO3 into an insulating phase with both metastable dipolar polarization and space-charge polarization. We then demonstrate transient negative differential capacitance in thin film capacitors. The space-charge polarization caused by long-range movement and trapping of protons dominates when the electric field exceeds the threshold value. First-principles calculations suggest the polarization originates from the polar structure created by H doping. We find that polarization decays within ~1 second which is an interesting temporal regime for neuromorphic computing hardware design, and we implement the transient characteristics in a neural network to demonstrate unsupervised learning. These discoveries open new avenues for designing ferroelectric materials and electrets using light-ion doping.

Design of hardware based on biological principles of neuronal computation and plasticity in the brain is a leading approach to realizing energy-and sample-efficient AI and learning machines. An important factor in selection of the hardware building blocks is the identification of candidate materials with physical properties suitable to emulate the large dynamic ranges and varied timescales of neuronal signaling. Previous work has shown that the all-or-none spiking behavior of neurons can be mimicked by threshold switches utilizing material phase transitions. Here, we demonstrate that devices based on a prototypical metal-insulator-transition material, vanadium dioxide (VO2), can be dynamically controlled to access a continuum of intermediate resistance states. Furthermore, the timescale of their intrinsic relaxation can be configured to match a range of biologically relevant timescales from milliseconds to seconds. We exploit these device properties to emulate three aspects of neuronal analog computation: fast (~1 ms) spiking in a neuronal soma compartment, slow (~100 ms) spiking in a dendritic compartment, and ultraslow (~1 s) biochemical signaling involved in temporal credit assignment for a recently discovered biological mechanism of one-shot learning. Simulations show that an artificial neural network using properties of VO2 devices to control an agent navigating a spatial environment can learn an efficient path to a reward in up to fourfold fewer trials than standard methods. The phase relaxations described in our study may be engineered in a variety of materials and can be controlled by thermal, electrical, or optical stimuli, suggesting further opportunities to emulate biological learning in neuromorphic hardware. [ABSTRACT FROM AUTHOR]

Materials with field-tunable polarization are of broad interest to condensed matter sciences and solid-state device technologies. Here, using hydrogen (H) donor doping, we modify the room temperature metallic phase of a perovskite nickelate NdNiO3 into an insulating phase with both metastable dipolar polarization and space-charge polarization. We then demonstrate transient negative differential capacitance in thin film capacitors. The space-charge polarization caused by long-range movement and trapping of protons dominates when the electric field exceeds the threshold value. First-principles calculations suggest the polarization originates from the polar structure created by H doping. We find that polarization decays within ~1 second which is an interesting temporal regime for neuromorphic computing hardware design, and we implement the transient characteristics in a neural network to demonstrate unsupervised learning. These discoveries open new avenues for designing ferroelectric materials and electrets using light-ion doping. Hydrogen-doping driven metal to ferroelectric phase transition in a complex oxide NdNiO3 is demonstrated. Transient negative differential capacitance and implementation of polarization decay into neural network for learning are then presented. [ABSTRACT FROM AUTHOR]

A new type of reconfigurable negative group delay (NGD) circuits based on active transversal filter topology is introduced in this work. By incorporating varactors with the NGD circuit at the input and output ports of active transversal filter based on distributed amplifiers (DAs), one can notably enhance the tunability for both amplitude and phase responses, thereby enabling NGD characteristic synthesis with a wider reconfigurable range. In this article, the proposed reconfigurable NGD circuits are applied to create both tunable non-Foster elements and tunable squint-free beamforming networks, which are verified by experiment. Furthermore, a general $N$ -stage transfer function for the proposed reconfigurable NGD circuit is derived, in which a two-stage particular case is given as an illustrative proof-of-concept example. Based on the reconfigurable NGD circuits, a prototype of a tunable negative capacitor is fabricated and measured, of which the capacitance can be tuned from −1.0 to −4.0 pF over a bandwidth of 100 MHz at 1 GHz or around 10% relative bandwidth. In addition, such an NGD circuit is utilized to create a low-dispersion superluminal transmission line, which enables a reconfigurable series antenna feedline for squint-free beam steering. Experimental results show that the main beam of the NGD antenna array has a tuning range from −15° to 15° within a squint-free bandwidth of 100 MHz at 2 GHz or within a relative bandwidth of around 5%. [ABSTRACT FROM AUTHOR]

This article presents a nonlinear leaky wave antenna (LWA) with frequency dependent parametric radiation based on a fundamentally slow‐wave transmission line (TL) structure. Unlike a conventional LWA that radiates at the excitation frequency, the radiation for the proposed travelling wave structure relies on the parametric frequencies based on the injected pump signals. The proposed nonlinear fundamentally slow wave structure utilizes a periodic sharply bend TL loaded by varactor diodes as nonlinear elements. By utilizing the n = −1 spatial harmonic, the fundamentally slow wave structure can enter the leaky wave region at higher frequencies, where the parametric radiation results from the bifurcation of the injected pump signals. Such TL‐based nonlinear LWA reduces the design complexity and fabrication difficulty. The resulting parametric frequency radiation can be used for beam steering, which provides additional degree of design freedom. [ABSTRACT FROM AUTHOR]

Deep-subwavelength optical field localization and ultra-long-range transmission are crucial for nanoscale photonics integration. However, the transmission performances of plasmon modes are restricted by the trade-off between the modal confinement and loss. Here we design a graphene-coated nanowire-based plasmonic waveguide to achieve unprecedented optical waveguiding performances, which is fully compatible with the silicon-on-insulator platform. The graphene plasmon modes in the proposed structure are systematically evaluated in terms of geometric and physical parameters. Benefiting from the distinctive modal field distribution caused by the silicon nano-rib, the proposed graphene plasmonic waveguide could support a deep-subwavelength plasmon mode with ultra-low loss, which outperforms most graphene-coated nanowire-based waveguides in the mid-infrared band. Also, the modal properties are quite robust against fabrication imperfections and the proposed configuration exhibits very low mode crosstalk. The proposed waveguiding approach paves the way for potential applications in tunable integrated photonic devices at the nanoscale. [ABSTRACT FROM AUTHOR]

An approximate three-wave model is suggested for describing the modal field inside the high-index dielectric rod of a hybrid plasmonic waveguide. An evanescent wave, an uniform wave and a propagating wave are considered along the direction perpendicular to the metal surface. The superposition of these three waves forms the modal field inside the high-index rod. Through numerical tests, we find that this model is highly valid for a large range of waveguide sizes. [ABSTRACT FROM AUTHOR]

The waveguiding of terahertz surface plasmons by a GaAs strip-loaded graphene waveguide is investigated based on the effective-index method and the finite element method. Modal properties of the effective mode index, modal loss, and cut-off characteristics of higher order modes are investigated. By modulating the Fermi level, the modal properties of the fundamental mode could be adjusted. The accuracy of the effective-index method is verified by a comparison between the analytical results and numerical simulations. Besides the modal properties, the crosstalk between the adjacent waveguides, which determines the device integration density, is studied. The findings show that the effective-index method is highly valid for analyzing dielectric-loaded graphene plasmon waveguides in the terahertz region and may have potential applications in subwavelength tunable integrated photonic devices. [ABSTRACT FROM AUTHOR]

In recent years, graphene-coated nanowires (GCNWs) have attracted considerable research interest due to the unprecedented optical properties of graphene in terahertz (THz) and mid-infrared bands. Graphene plasmons in GCNWs have become an attractive platform for nanoscale applications in subwavelength waveguides, polarizers, modulators, nonlinear devices, etc. Here, we provide a comprehensive overview of the surface conductivity of graphene, GCNW-based plasmon waveguides, and applications of GCNWs in optical devices, nonlinear optics, and other intriguing fields. In terms of nonlinear optical properties, the focus is on saturable absorption. We also discuss some limitations of the GCNWs. It is believed that the research of GCNWs in the field of nanophotonics will continue to deepen, thus laying a solid foundation for its practical application. [ABSTRACT FROM AUTHOR]