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Doped‐metal oxide‐based memristors, with the potential for improved switching performance and capability for multi‐bit information storage, are attractive candidates in the implementation of artificial neural network (ANN) hardware systems. However, performance and process considerations such as switching behavior and complementary‐metal‐oxide‐semiconductor (CMOS) process compatibility remain a challenge. This study shows that amorphous Zr‐doped HfO2 (HZO) memristors fabricated via a co‐sputtering approach improve the switching performance by providing a controllable knob to modulate defects in the switching layer. At the same time, it satisfies the CMOS process compatibility requirements for industry adoption. HZO memristors with optimized stoichiometry exhibit 30% reduced switching voltages and 50% faster switching as compared to control HfO2 memristors. Concurrently, this study shows that high linearity analog states tuning is achievable via a programming scheme that utilizes voltage pulses with increasing amplitudes. This study further shows via simulation evaluation that HZO memristors implemented in a self‐organizing‐map (SOM) network for Fashion MNIST database classification, achieve an accuracy of 92% with short training cycles. The results thus pave a potential pathway for further development of CMOS process compatible HZO memristors for use in future storage and computing applications. [ABSTRACT FROM AUTHOR]

The development and application of artificial intelligence have led to the exploitation of low‐power and compact intelligent information‐processing systems integrated with sensing, memory, and neuromorphic computing functions. The 2D van der Waals (vdW) materials with abundant reservoirs for arbitrary stacking based on functions and enabling continued device downscaling offer an attractive alternative for continuously promoting artificial intelligence. In this study, full 2D SnS2/h‐BN/CuInP2S6 (CIPS)‐based ferroelectric field‐effect transistors (Fe‐FETs) and utilized light‐induced ferroelectric polarization reversal to achieve excellent memory properties and multi‐functional sensing‐memory‐computing vision simulations are designed. The device exhibits a high on/off current ratio of over 105, long retention time (>104 s), stable cyclic endurance (>350 cycles), and 128 multilevel current states (7‐bit). In addition, fundamental synaptic plasticity characteristics are emulated including paired‐pulse facilitation (PPF), short‐term plasticity (STP), long‐term plasticity (LTP), long‐term potentiation, and long‐term depression. A ferroelectric optoelectronic reservoir computing system for the Modified National Institute of Standards and Technology (MNIST) handwritten digital recognition achieved a high accuracy of 93.62%. Furthermore, retina‐like light adaptation and Pavlovian conditioning are successfully mimicked. These results provide a strategy for developing a multilevel memory and novel neuromorphic vision systems with integrated sensing‐memory‐processing. [ABSTRACT FROM AUTHOR]

The search for high‐performance resistive random‐access memory (RRAM) devices is essential to pave the way for highly efficient non‐Von Neumann computing architecture. Here, it is reported on an alloying approach using atomic layer deposition for a Zn‐doped HfOx‐based resistive random‐access memory (HfZnO RRAM), with improved performance. As compared with HfOx RRAM, the HfZnO RRAM exhibits reduced switching voltages (>20%) and switching energy (>3×), as well as better uniformity both in voltages and resistance states. Furthermore, the HfZnO RRAM exhibits stable retention exceeding 10 years, as well as write/erase endurance exceeding 105 cycles. In addition, excellent linearity and repeatability of conductance tuning can be achieved using the constant voltage pulse scheme, achieving ≈90% accuracy in a simulated multi‐layer perceptron network for the recognition of modified national institute of standards and technology database handwriting. The HfZnO RRAM is also characterized down to the temperature of 4 K, showing functionality and the elucidation of its carrier conduction mechanism. Hence, a potential pathway for doped‐RRAM to be used in a wide range of temperatures including quantum computing and deep‐space exploration is shown. [ABSTRACT FROM AUTHOR]

Abstract: Nonvolatile optoelectronic memories integrated with the functions of sensing, data storage, and data processing are promising for the potential Internet of things (IoT) applications. To meet the requirements of IoT devices, multifunctional memory devices with low power consumption and secure data storage are highly desirable. This study demonstrates an optoelectronic resistive switching memory integrated with sensing and logic operations by adopting organic–inorganic hybrid CH3NH3PbI3−xClx perovskites, which possess unusual defect physics and excellent light absorption. The CH3NH3PbI3−xClx cell exhibits low operation voltage of 0.1 V with the assistance of light illumination, long‐term retention property, and multiple resistance states. Its unique optoelectronic characteristics enable to perform logic operation for inputting one electrical pulse and one optical signal, and detect the coincidence of electrical and optical signal as well. This design provides possibilities for smart sensor in IoT application. [ABSTRACT FROM AUTHOR]

Owing to an ultrathin body, atomic scale smoothness, dangling bond-free surface, and sizable bandgap, transistors based on two-dimensional (2D) layered semiconductors show the potential of scalability down to the nanoscale, high-density three-dimensional integration, and superior performance in terms of better electrostatic control and smaller power consumption compared with conventional three-dimensional semiconductors (Si, Ge, and III-V compound materials). To apply 2D layered materials into complementary metal-oxide-semiconductor logic circuits, it is important to modulate the carrier type and density in a controllable manner, and engineer the contact (between metal electrode and 2D semiconductor) and the interface (between dielectrics and semiconducting channel) to get close to their intrinsic carrier mobility. In this review, the most widely studied 2D transition metal dichalcogenides (TMD) are focused on, and an overview of recent progress on doping, contact, and interface engineering of the TMD-based field-effect transistors is provided. [ABSTRACT FROM AUTHOR]

A two-dimensional (2D) ferroelectric semiconductor, which is coupled with photosensitivity and room-temperature ferroelectricity, provides the possibility of coordinated conductance modulation by both electric field and light illumination and is promising for triggering the revolution of optoelectronics for monolithic multifunctional integration. Here, we report that semiconducting Sn 2 P 2 S 6 crystals can be achieved in a 2D morphology using a chemical vapor transport approach with the assistant of space confinement and experimentally demonstrate the robust ferroelectricity in atomic-thin Sn 2 P 2 S 6 nanosheet at room temperature. The intercorrelated programming of ferroelectric order along out-of-plane (OOP) and in-plane (IP) directions enables a tunable bulk photovoltaic (BPV) effect through multidirectional electrical control. By combining the capability of anisotropic in-plane optical absorption, a highly integrated Sn 2 P 2 S 6 optoelectronic device vertically sandwiched with graphene electrodes yields the polarization-dependent open-circuit photovoltage with a dichroic ratio of 2.0 under 405 nm light illumination. The reintroduction of ferroelectric Sn 2 P 2 S 6 to the 2D asymmetric semiconductor family provides possibilities to hardware implement of the self-powered polarization-sensitive photodetection and spotlights the promising applications for next-generation photovoltaic devices.

Conducting bridge random access memory (CBRAM) is one of the most promising candidates for future nonvolatile memories. It is important to understand the scalability and retention of CBRAM cells to realize better memory performance. Here, we directly observe the switching dynamics of Cu tip/SiO 2 /W cells with various active electrode sizes using in situ transmission electron microscopy. Conducting filaments (CFs) grow from the active electrode (Cu tip) to inert electrode (W) during the SET operations. The size of the Cu tip affects the electric-field distribution, the amount of the cation injection into electrolyte, and the dimension of the CF. This study provides helpful understanding on the relationship between power consumption and retention of CBRAM cells. We also construct a theoretical model to explain the electrode-size-dependent CF growth in SET operations, showing good agreement with our experimental results.