DH-GAN: a physics-driven untrained generative adversarial network for holographic imaging.

Digital holography is a 3D imaging technique by emitting a laser beam with a plane wavefront to an object and measuring the intensity of the diffracted waveform, called holograms. The object's 3D shape can be obtained by numerical analysis of the captured holograms and recovering the incurred phase. Recently, deep learning (DL) methods have been used for more accurate holographic processing. However, most supervised methods require large datasets to train the model, which is rarely available in most DH applications due to the scarcity of samples or privacy concerns. A few one-shot DL-based recovery methods exist with no reliance on large datasets of paired images. Still, most of these methods often neglect the underlying physics law that governs wave propagation. These methods offer a black-box operation, which is not explainable, generalizable, and transferrable to other samples and applications. In this work, we propose a new DL architecture based on generative adversarial networks that uses a discriminative network for realizing a semantic measure for reconstruction quality while using a generative network as a function approximator to model the inverse of hologram formation. We impose smoothness on the background part of the recovered image using a progressive masking module powered by simulated annealing to enhance the reconstruction quality. The proposed method exhibits high transferability to similar samples, which facilitates its fast deployment in time-sensitive applications without the need for retraining the network from scratch. The results show a considerable improvement to competitor methods in reconstruction quality (about 5 dB PSNR gain) and robustness to noise (about 50% reduction in PSNR vs noise increase rate).

Quantum Conductance in Memristive Devices: Fundamentals, Developments, and Applications.

Quantum effects in novel functional materials and new device concepts represent a potential breakthrough for the development of new information processing technologies based on quantum phenomena. Among the emerging technologies, memristive elements that exhibit resistive switching, which relies on the electrochemical formation/rupture of conductive nanofilaments, exhibit quantum conductance effects at room temperature. Despite the underlying resistive switching mechanism having been exploited for the realization of next-generation memories and neuromorphic computing architectures, the potentialities of quantum effects in memristive devices are still rather unexplored. Here, a comprehensive review on memristive quantum devices, where quantum conductance effects can be observed by coupling ionics with electronics, is presented. Fundamental electrochemical and physicochemical phenomena underlying device functionalities are introduced, together with fundamentals of electronic ballistic conduction transport in nanofilaments. Quantum conductance effects including quantum mode splitting, stability, and random telegraph noise are analyzed, reporting experimental techniques and challenges of nanoscale metrology for the characterization of memristive phenomena. Finally, potential applications and future perspectives are envisioned, discussing how memristive devices with controllable atomic-sized conductive filaments can represent not only suitable platforms for the investigation of quantum phenomena but also promising building blocks for the realization of integrated quantum systems working in air at room temperature.

Steep-slope field-effect transistors with AlGaN/GaN HEMT and oxide-based threshold switching device.

We report the demonstration of a steep-slope field-effect transistor with AlGaN/GaN MIS-HEMTs employing SiO2-based threshold switching devices in series with the source. The SiO2-based threshold switching devices exhibited steep slope when changing resistance states. The integrated steep-slope transistor showed a low subthreshold swing of sub-5 mV/dec with a transition range of over 105 in the transfer characteristics in both sweep directions at room temperature, as well as the low leakage current (10-5 µA µm-1) and a high I ON/I OFF ratio (>107). Moreover, with the SiO2-based threshold switching devices we also observed a positive shift of threshold voltages of the integrated device. Results from more than 50 transfer characteristics measurements also indicate the good repeatability and practicability of such a steep-switching device, where the average steep slopes are below 10 mV/decade. This steep-slope transistor with oxide-based threshold switching devices can be further extended to various transistor platforms like Si and III-V and are of potential interest for the development of power switching and high frequency devices.

Impact of radiation induced crystallization on programmable metallization cell electrical characteristics and reliability.

Chalcogenide-based, programmable metallization cells (PMC) cells have been characterized after exposure to increasing levels of absorbed dose (i.e., ionizing radiation exposure). We found, and show here for the first time, that total absorbed dose effects induce a slight modification of the switching phenomena with a moderate increase of the programmable low resistance state (LRS) of the PMCs after repeated switching depending on the processing conditions, while it does not impact the state programmed before exposure. We also show that an increase of the programmable high resistance state (HRS) occurs with irradiation. Such observations are discussed through correlation with crystallization observed in the concurrent X-ray diffraction (XRD) characterization of representative thin-film stacks of the PMCs. These new results are compared to previous results obtained on chalcogenide-based PMCs that did not identify/observe such effects.

A CMOS-compatible electronic synapse device based on Cu/SiO2/W programmable metallization cells.

In this work, the resistance plasticity of Cu/SiO2/W programmable metallization cell devices is experimentally explored for the emulation of biological synapses. PMC devices were fabricated with foundry friendly materials using standard processes. The resistance can be continuously increased or decreased with both dc and voltage pulse programming. Impedance spectroscopy results indicate that the gradual change of resistance is attributable to the expansion or contraction of a Cu-rich layer within the device. Pulse programming experiments further show that the pulse amplitude plays a more important role in resistance change than pulse width, which is consistent with the proposed 'dual-layer' device model. The dense resistance-state distribution, 1 V operating voltage and inherent CMOS-compatibility suggests its potential application as electronic synapse in neuromorphic computing.

Electrochemical metallization memories--fundamentals, applications, prospects.

This review focuses on electrochemical metallization memory cells (ECM), highlighting their advantages as the next generation memories. In a brief introduction, the basic switching mechanism of ECM cells is described and the historical development is sketched. In a second part, the full spectra of materials and material combinations used for memory device prototypes and for dedicated studies are presented. In a third part, the specific thermodynamics and kinetics of nanosized electrochemical cells are described. The overlapping of the space charge layers is found to be most relevant for the cell properties at rest. The major factors determining the functionality of the ECM cells are the electrode reaction and the transport kinetics. Depending on electrode and/or electrolyte material electron transfer, electro-crystallization or slow diffusion under strong electric fields can be rate determining. In the fourth part, the major device characteristics of ECM cells are explained. Emphasis is placed on switching speed, forming and SET/RESET voltage, R(ON) to R(OFF) ratio, endurance and retention, and scaling potentials. In the last part, circuit design aspects of ECM arrays are discussed, including the pros and cons of active and passive arrays. In the case of passive arrays, the fundamental sneak path problem is described and as well as a possible solution by two anti-serial (complementary) interconnected resistive switches per cell. Furthermore, the prospects of ECM with regard to further scalability and the ability for multi-bit data storage are addressed.