Heba Abunahla

Effect of device, size, activation energy, temperature, and frequency on memristor switching time

Memristor has a potential to play a big role in the electronics industry as it provides small size, low cost and low power. However, the asymmetry between the ON and OFF switching times of the device hinders the adaption of the device in modern electronics systems. The contribution of this paper is to explore the relationship between the length of the memristor and the switching times. To achieve this the nonlinear model of oxygen vacancies is used. The model also includes coupling with electron transfer. The study shows that tuning the device length can affect the switching time significantly. This paper shows that having a device length of 10-nm gives switching ON and OFF times in the range of 4s - 13ns for applied voltage of 1V - 2.3V. In additon, the obtained OFF/ON switching time ratio is 3x compared to several order of magnitudes reported inliterature for device length of 50-nm. The proposed model is also used to study the effect of changing temperature, activation energy and frequency on memristor switching time.

Modeling Valance Change Memristor Device: Oxide Thickness, Material Type, and Temperature Effects

This paper 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 parameters of the proposed model are tuned and validated using experimental data of a fabricated wire based NbO1-x junction. This device is attractive for neuromorphic and computing applications, where multilevel state is desirable. 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.

Novel secret key generation techniques using memristor devices

This paper proposes novel secret key generation techniques using memristor devices. The approach depends on using the initial profile of a memristor as a master key. In addition, session keys are generated using the master key and other specified parameters. In contrast to existing memristor-based security approaches, the proposed development is cost effective and power efficient since the operation can be achieved with a single device rather than a crossbar structure. An algorithm is suggested and demonstrated using physics based Matlab model. It is shown that the generated keys can have dynamic size which provides perfect security. Moreover, the proposed encryption and decryption technique using the memristor based generated keys outperforms Triple Data Encryption Standard (3DES) and Advanced Encryption Standard (AES) in terms of processing time. This paper is enriched by providing characterization results of a fabricated microscale Al/TiO2/Al memristor prototype in order to prove the concept of the proposed approach and study the impacts of process variations. The work proposed in this paper is a milestone towards System On Chip (SOC) memristor based security.

Resistive switching in sol-gel derived microscale memristors

This paper describes the synthesis of micro-thick hafnium-oxide (∼ 60 μm) memristors using a low-cost sol-gel drop-coating technique, and emphasizes on key parameters to be considered in the development of the microscale technology. The impact of electrode material on the device I-V electrical behavior is screened with the use of different metals, with different work-functions and oxygen affinities such as aluminum (Al), copper (Cu), titanium (Ti) and palladium (Pd) under a symmetric metal-insulator-metal arrangement. The type of metal contact was found to play a vital role in the switching behavior of the devices, highlighting a potential chemical interplay between the drop-coating solution and the electrode surface during the fabrication process. The effect of the sol-gel drying temperature on the I-V curve characteristics is also investigated with similar devices made at 60 °C and 80 °C. For example, the Roff/Ron ratio of Al/Al-type memristors was found to increase by approximately nine folds when the drying temperature was increased from 60 °C to 80 °C. As depicted from the changes observed in the maximum flowing current within an I-V curve, the drying temperature was generally found to mainly affect the internal resistance of the devices, allowing external control over the Roff/Ron ratio.

Novel microscale memristor with uniqueness property for securing communications

A rewritable micro-thick low power memristor device is presented. The memristor is fabricated based on a novel structure that is composed of Al/TiO2/Cu. The device switches at 3X lower voltage compared to the existing bipolar memristor state of the art at the microscale. The fabricated device exhibits unique I-V characteristic among similar devices when operated without prior electroforming. Thus, a new secure communication technique is proposed based on the existence of third trust party (TTP). As each host has unique memristor device, messages can be encrypted and decrypted securely using memristor based keys. In addition, Scyther analysis are provided to prove the security of the proposed technique. This work takes advantage of the inherited variation of memristor device electric characteristics to strengthen security algorithm in cryptographic application.

An Efficient Heterogeneous Memristive xnor for In-Memory Computing

Resistive RAM (RRAM) technologies are gaining importance due to their appealing characteristics, which include non-volatility, small form factor, low power consumption, and ability to perform logic operations in memory. These characteristics make RRAM highly suited for Internet of Things devices and similarly resource-constrained systems. This paper proposes a novel memristor-based xnor gate that enables the execution of xnor/xor function in the memristive crossbar memory. The proposed two-input xnor gate requires two steps to perform the xnor function. The design of the circuit utilizes bipolar and unipolar memristors and permits cascading by only adding an extra step and one computing memristor. To the best of our knowledge, this is the first native stateful xnor logic implementation. Spice simulations have been used to verify the functionality of the proposed circuit. This includes benchmarking the proposed design against the state-of-the-art stateful memristor-based logic circuits. The results for implementing three-input xor using the proposed circuit demonstrate efficient performance in terms of energy, latency, and area. The gate shows 56% saving in energy, 54% less number of steps (latency), and 50% less number of computing MR (area) compared with the state-of-the-art stateful xor/xnor implementations.

Physics model of memristor devices with varying active materials

This paper presents a physics-based model for memristors with different active layer materials. The model predicts the effect of changing the active material on the electrical characteristics of the devices. It captures the essential characteristics of the memristor such as coupling between ion mobility and electron current in addition to the nonlinear effects of electric fields. The parameters in the model depend on material (metal-oxide) properties that have impact on the device behavior. These properties are activation energy, escape attempt frequency, hopping parameter and relative permittivity. In this work, the effect of each parameter is highlighted and explained. In addition, the physics-based Matlab model is used to analyze the electrical characteristics of simulated memristor device using the following oxide materials; ZnO, TiO2 and Ta2O5. The simulation results of the model are validated with experimental data reported in the literature. The value of this contribution is to enable the selection of suitable oxide materials for the target memristor using correlated mathematical models.

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.

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.

Synthesis and Characterization of Micro-Thick TiO 2 and HfO 2 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.