Weisong Wang

Vanadium Oxide Thin-Film Variable Resistor-Based RF Switches

Vanadium dioxide (VO2) is a unique phase change material (PCM) that possesses a metal-to-insulator transition property. Pristine VO2 has a negative temperature coefficient of resistance, and it undergoes an insulator-to-metal phase change at a transition temperature of 68 °C. Such a property makes the VO2 thin-film-based variable resistor (varistor) a good candidate in reconfigurable electronics to be integrated with different RF devices such as inductors, varactors, and antennas. Series single-pole single-throw (SPST) switches with integrated VO2 thin films were designed, fabricated, and tested. The overall size of the device is 380 μm × 600 μm. The SPST switches were fabricated on a sapphire substrate with integrated heating coil to control VO2 phase change. During the test, when VO2 thin film changed from insulator at room temperature to metallic state (low-resistive phase) at 80 °C, the insertion loss of the SPST switch was <;3 dB at 10 GHz. In addition, the isolation of the SPST improved to better than 30 dB when the temperature dropped to 20 °C. These tunable characteristics of the RF switch provide evidence for VO2 as a useful PCM for the broad range of applications in reconfigurable electronics.

Lithium based memristive device

The effort of investigating memristor material continues. This paper demonstrates the latest results of such effort by our group. These include memristor device design and measurement based on stacked lithium niobate and aluminum oxide. I-V sweeping results show good switch memristive characteristic. Other preliminary results in this paper include temperature dependency study, pulse voltage write/read and retention characterization. From these results, lithium niobate based device show the temperature stability and multiple stages of write/read and long retention period. All these demonstrate its potential for the application of neuromorphic computing in the future.

Fabrication, characterization, and modeling of memristor devices

This paper describes the fabrication of memristor devices based on titanium and hafnium oxides. The device cross sectional area is varied to observe the impact this has on the current-voltage characteristic. A modeling technique is then utilized that is capable of matching the current-voltage characteristics of memristor devices. The model was able to match the titanium oxide device described in this paper with 13.58% error. The device model was then used in a neuromorphic simulation showing that a circuit based on this device is capable of learning logic functions.

Filament formation in lithium niobate memristors supports neuromorphic programming capability

Memristor crossbars are capable of implementing learning algorithms in a much more energy and area efficient manner compared to traditional systems. However, the programmable nature of memristor crossbars must first be explored on a smaller scale to see which memristor device structures are most suitable for applications in reconfigurable computing. In this paper, we demonstrate the programmability of memristor devices with filamentary switching based on LiNbO3, a new resistive switching oxide. We show that a range of resistance values can be set within these memristor devices using a pulse train for programming. We also show that a neuromorphic crossbar containing eight memristors was capable of correctly implementing an OR function. This work demonstrates that lithium niobate memristors are strong candidates for use in neuromorphic computing.

Memristor devices for use in neuromorphic systems

This paper describes the fabrication and characterization process used to develop memristors that are strong candidates for use in neuromorphic systems. A common approach for the development of memristor-based neuromorphic circuits is to store synaptic weight values within memristors as resistance values. This requires use of the continuous resistance range available in the memristors to store the weight matrix produced by a learning algorithm. More specifically, these devices will be used in systems that implement supervised learning algorithms such as single and multilayer perceptrons. It is important to be able to iteratively program a target resistance through a number of feedback controlled voltage pulses as opposed to abruptly switching the device between two binary states. This paper shows how TiO2 memristor devices placed in a crossbar arrangement are capable of implementing Boolean logic functions using a perceptron algorithm. Resistances within a memristor crossbar can be tuned and reconfigured so that a neuron circuit based on this crossbar can represent multiple different functions.

Methods for high resolution programming in lithuim niobate memristors for neuromorphic hardware

Memristor crossbars are capable of implementing learning algorithms in a much more energy and area efficient manner compared to traditional systems. However, the programmable nature of memristor crossbars must first be explored on a smaller scale to see which memristor device structures are most suitable for applications in reconfigurable computing. In this paper, we demonstrate the programmability of memristor devices with filamentary switching based on LiNbOx, a new resistive switching oxide. We have performed several characterization experiments that demonstrate the high resolution programmability of these devices. Once the optimal programming voltages and conductivity ranges for these memristor devices are determined, a method is presented to determine how many unique states can be achieved in these devices. Parameters obtained from this analysis can greatly strengthen memristor device models that implement realistic stochastic switching behavior. We show that 11 unique states can be stored in this device with 95% confidence, but many more states are achievable using feedback write techniques or in-situ learning. Therefore, we have determined that Lithium Niobate memristors are strong candidates for use in neuromorphic computing.

A resonant circuit realization using a 3D inductor in combination with thin film varactor technology

A resonant circuit combining a 3D inductor with the barium strontium titanate thin film varactor, is presented in this work. The filter was fabricated using a 3D inductor fabrication process. The modeling of the filter was examined using the Advanced Design System (ADS). The measurement results showed that the resonant frequencies were around 10 GHz and correlated to different number of turns of 3D inductor. The inductances extracted from the equivalent circuit varied from 0.28 nH to 0.37 nH.

Vanadium dioxide thin film series single-pole single throw switch

Vanadium dioxide (VO2) thin films have unique insulator to metal transition above the critical temperature of 72 °C. In this research, VO2 thin films were deposited on a sapphire substrate for thermally controllable RF/microwave switching devices with integrated heating coil. The VO2 thin film based devices showed insulator performance at room temperature and metallic state (low resistive phase) at 80 °C. Switching devices designed using a VO2 series varistor showed good isolation (<; -30 dB) and low insertion loss (> -5 dB) up to 20 GHz.