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Über dieses Buch

This book provides readers with a single-source guide to fabricate, characterize and model memristor devices for sensing applications. The authors describe a correlated, physics-based model to simulate and predict the behavior of devices fabricated with different oxide materials, active layer thickness, and operating temperature. They discuss memristors from various perspectives, including working mechanisms, different synthesis methods, characterization procedures, and device employment in radiation sensing and security applications.



Chapter 1. Memristor Device Overview

Memristors are one of the emerging technologies that can potentially replace state-of-the-art integrated electronic devices for advanced computing and digital and analog circuit applications including neuromorphic networks. Over the past few years, research and development mostly focused on revolutionizing the metal-oxide materials, which are used as core components of the popular metal-insulator-metal (MIM) memristors owing to their highly recognized resistive switching behavior. This chapter outlines the recent advancements and characteristics of such memristive devices, with a special focus on (i) their established resistive switching mechanisms and (ii) the key challenges associated with their fabrication processes including the impeding criteria of material adaptation for the electrode, capping, and insulator component layers. Potential applications and an outlook into the future development of metal-oxide memristive devices are also outlined.

Heba Abunahla, Baker Mohammad

Chapter 2. Synthesis and Characterization of Micro-Thick TiO2 and HfO2 Memristors

Solgel/drop-coated micro-thick TiO2 memristors are investigated and developed for sensing applications. Devices constructed with coated aluminum (Al) electrodes exhibit unipolar I–V characteristics with dynamic turn-on voltage and progressive ROFF/RON ratio loss under applied bias. Endurance failure of micro-thick Al/Al stacks is ascribed to gradual passivation of Al surface resulting from an electrically enhanced oxygen-ion diffusion. By exchanging a single Al contact with higher work-function copper (Cu) metal, two distinct superimposed TiO2 phases are formed. After initial forming, the hybrid stack could achieve a bipolar memristance, with high ROFF/RON (up to 106), and over 10 switching cycles at low operating voltages (±1 V). This chapter also presents micro-thick memristors which are fabricated using alternatively the hafnium-oxide (HfO2) chemistry for the active material. The main focus of the micro-thick HfO2 devices provided here is to investigate the switchability of the novel system and to study the effect of changing key parameters such as (i) the electrode material and (ii) the drying temperature during solgel processing on the resistive switching behavior. The results presented in this chapter highlight important structure to performance findings that provide guidance and insights on optimizing the solgel drop-coating of micro-thick memristor devices.

Heba Abunahla, Baker Mohammad

Chapter 3. Synthesis and Characterization of Nano-Thick HfO2 Memristive Crossbar

In this chapter, the geometric scaling effect is investigated on the unipolar switching behavior of nano-thick Pd(TE)/Hf (capping)/HfO2/Pd(BE) metal-insulator-metal memristive devices. The electrical I–V characteristics of such device are studied as a function of the active area and thickness of each of the metal-oxide film and the capping layer. The device active area is shown to play a critical role in dictating the magnitude of the threshold turn-on voltage (VON). For (Hf-7 nm/HfO2-10 nm) stack particularly, it is found that the average VON decreases from 4.7 to 2.8 V when the active area increases from 50 × 50 to 200 × 200 µm2. Beyond this size, the threshold VON saturates and the device active area have a minimal effect on VON. Also, the switching ON voltage increases when the capping layer thickness increases as it adds to the total active film of the device. For the fabricated devices, decreasing the oxide thickness from 10-nm to 5-nm reduces the average turn-on voltage by 21-to-27% for 50 × 50-to-400 × 400 µm2 active area range, demonstrating an improvement in the threshold power consumption of the memristor. These findings can be used to guide the design and fabrication of memristors for an improved RRAM and memristive-based applications.

Heba Abunahla, Baker Mohammad

Chapter 4. Synthesis and Characterization of Wire-Based NbO Memristive Junctions

Bio-inspired semiconductor-based devices with adaptive and dynamic properties will have many advantages over conventional static digital silicon-based technologies. The ability to compute, process, and retain information in parallel, without referencing other circuit elements, offers enhanced speed, storage density, energy efficiency, and functionality benefits. A novel crossbar microwire-based device consisting of Nb/NbO/Pt structure that exhibits neural synapse-like adaptive conductivity (i.e., synaptic plasticity) is presented. The neuromorphic memristive junction, formed at the interface between the Pt metal wire and the thermally annealed core-shell Nb–NbO wire, demonstrates 1000 times conductivity change with an effective continuum of resistance levels. The device can also be fully activated to display standard resistance switching between two states. In the subthreshold regime, the voltage flux applied through the ~400 nm thick NbO junction is shown to have a linear relationship to the charge produced within the device. The conductance value G is a function of the total flux history applied. This has implications in emerging neuromorphic semiconductor hardware.

Heba Abunahla, Baker Mohammad

Chapter 5. Memristor Device for Security and Radiation Applications

The first physical demonstration of a non-volatile resistive-switching memory based on the nanostructured Pt/TiO2/Pt metal/insulator/metal stack from HP, has spurred the scientific community to develop memristive devices for a wide variety of applications. Owing to low-power and ultra-fast switching capabilities, memristors with nanoscale thickness geometry have been extensively investigated as potential replacements for flash memory technology in simple analog- and digital- computing applications. In Addition, both scalability and interconnectivity of memristors, through brain-inspired computing, have sparked a considerable move toward advancing of next-generation intelligent computing systems. On the horizon, other potential uses of the memristor have also emerged, particularly in sensing where attractive measurable changes in the I–V fingerprint of some device configurations have been demonstrated under certain types of extrinsic disturbances. Additionally, the unique and chaotic I–V response of some memristors opens the door for potential applications in hardware security. This chapter reports on novel approaches to utilize the electrical characteristics of the fabricated memristive devices for radiation sensing and security applications.

Heba Abunahla, Baker Mohammad

Chapter 6. Memristor Device Modeling

This chapter presents a physics-based mathematical model for anionic memristor devices. The model utilizes Poisson Boltzmann equation to account for temperature effect on device potential at equilibrium and comprehends material effect on device behaviors. A detailed MATLAB-based algorithm is developed to clarify and simplify the simulation environment. Moreover, the provided model is used to simulate and predict the effect of oxide thickness, material type, and operating temperatures on the electrical characteristics of the device. The value of this contribution is to provide a framework intended to simulate anionic memristor devices using correlated mathematical models. In addition, the model can be used to explore device materials and predict its performance.

Heba Abunahla, Baker Mohammad


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