Engineering Method for Tailoring Electrical Characteristics in TiN/TiOx/HfOx/Au Bi-Layer Oxide Memristive Devices

Abstract

Memristive devices have led to an increased interest in neuromorphic systems. However, different device requirements are needed for the multitude of computation schemes used there. While linear and time-independent conductance modulation is required for machine learning, non-linear and time-dependent properties are necessary for neurobiologically realistic learning schemes. In this context, an adaptation of the resistance switching characteristic is necessary with regard to the desired application. Recently, bi-layer oxide memristive systems have proven to be a suitable device structure for this purpose, as they combine the possibility of a tailored memristive characteristic with low power consumption and uniformity of the device performance. However, this requires technological solutions that allow for precise adjustment of layer thicknesses, defect densities in the oxide layers, and suitable area sizes of the active part of the devices. For this purpose, we have investigated the bi-layer oxide system TiN/TiOx/HfOx/Au with respect to tailored I-V non-linearity, the number of resistance states, electroforming, and operating voltages. Therefore, a 4-inch full device wafer process was used. This process allows a systematic investigation, i.e., the variation of physical device parameters across the wafer as well as a statistical evaluation of the electrical properties with regard to the variability from device to device and from cycle to cycle. For the investigation, the thickness of the HfOx layer was varied between 2 and 8 nm, and the size of the active area of devices was changed between 100 and 2,500 µm2. Furthermore, the influence of the HfOx deposition condition was investigated, which influences the conduction mechanisms from a volume-based, filamentary to an interface-based resistive switching mechanism. Our experimental results are supported by numerical simulations that show the contribution of the HfOx film in the bi-layer memristive system and guide the development of a targeting device.

Multilayer redox-based HfOx/Al2O3/TiO2 memristive structures for neuromorphic computing

“…5 c), as well as the nonlinearities and asymmetry of the maximum currents. With ≤ 0.1 eV, the values for the Schottky barrier lowering found in the area-type devices are of a typical order of magnitude reported previously 67 . Also, the obtained activation energies of diffusion (≈ 0.4–0.7 eV) roughly match the theoretical value of 0.69 eV 54 , 55 for ideal single crystalline HfO 2 but are overall smaller.…”

“…This is larger than the values of HfO x /TiO x interfaces 47 and can explain the stable area-type switching behavior we observe in the trilayer devices. The stabilization leads to various additional advantages in performance compared to previously presented HfO x /TiO 2 bilayer devices 67 , such as the possibility of operating without current compliance and initial electroforming cycles in devices of both hafnium oxide stoichiometries.…”

“…Details on the XPS measurements and the fabrication process are provided in Ref. 67 . The variation of electrical properties of reactively sputtered metal oxides has been investigated elsewhere 86 .…”

“…The contributions of the Al 2 O 3 and the TiO 2 layer to the current–voltage characteristics are considered by one effective resistance with a corresponding current . This current depends on the voltage amplitude over these layers and is scaled by the fitting parameter 67 …”

Stochastic behaviour of an interface-based memristive device

“…Therefore, the applications are predominantly in the field of RRAMs. In contrast, interface type devices are often driven by the movement of ions or charged defects within the active layer that modify the electrical characteristics of the metal/insulator interfaces (Schottky contacts or tunneling contacts), which act as boundaries for the active layer [20][21][22]. The switching dynamics is therefore analogue.…”