Layered two-dimensional (2D) materials have entered the spotlight as promising channel materials for future optoelectronic devices owing to their excellent electrical and optoelectronic properties. However, their limited photodetection range caused by their wide bandgap remains a principal challenge in 2D layered materials-based phototransistors. Here, we developed a germanium (Ge)-gated MoS2 phototransistor that can detect light in the region from visible to infrared (λ = 520–1550 nm) using a detection mechanism based on band bending modulation. In addition, the Ge-gated MoS2 phototransistor is proposed as a multilevel optic-neural synaptic device, which performs both optical-sensing and synaptic functions on one device and is operated in different current ranges according to the light conditions: dark, visible, and infrared. This study is expected to contribute to the development of 2D material-based phototransistors and synaptic devices in next-generation optoelectronics.

Electrochemical metallization (ECM) threshold switches are in great demand for various applications such as next-generation logic technology, future memory, and neuromorphic computing. However, the instability of operation due to inherent filamentary randomness is a severe problem that is yet to be solved. Here, we propose a specially treated hafnium oxide (HfO x :N)-based ECM threshold switch with high reliability, low-voltage operation (0.2 V), high ON/ OFF ratio (5 × 10 8 ), great endurance (10 6 ), and fast switching speed (1.5 μs at 2 V). The nitrogen ions in the HfO x :N layer assist confining the path of the metallic filament, which significantly suppresses filament randomness as well as reduces power consumption and alternating current response time. The feasibility of ECM threshold switches to logic applications, AND and OR, is first introduced. The ECM threshold switch has great potential to be utilized in complementary logic circuits because of its ultralow operation power consumption, high integrability using an array structure (4F 2 ), and fast switching characteristics. Furthermore, we have successfully verified its applicability to flexible electronics on polyethylene naphthalate films that can retain stable operation under considerable mechanical stress. We believe that this research paves the way to fabricate highly reliable ECM threshold switches for flexible complementary logic circuits with ultralow power consumption.

Neural networks composed of artificial neurons and synapses mimicking the human nervous system have received much attention because of their promising potential in future computing systems. In particular, spiking neural networks (SNNs), which are faster and more energy‐efficient than conventional artificial neural networks, have recently been the focus of attention. However, because typical neural devices for SNNs are based on complementary metal‐oxide‐semiconductors that exhibit high consumption of power and require a large area, it is difficult to use them to implement a large‐scale network. Thus, a new structure should be developed to overcome the typical problems that have been encountered and to emulate bio‐realistic functions. This study proposes a versatile artificial neuron based on the bipolar electrochemical metallization threshold switch, which exhibits four requisite characteristics for a spiking neuron: all‐or‐nothing spiking, threshold‐driven spiking, refractory period, and strength‐modulated frequency. Furthermore, unique features such as an inhibitory postsynaptic potential and the bipolar switching characteristic for changing synaptic weight are realized. Additionally, by using a filament confinement technique, a high on/off ratio (≈6 × 107), a low threshold voltage (0.19 V), low variability (0.014), and endurance over 106 cycles are achieved. This research will serve as a stepping‐stone for advanced large‐scale neuromorphic systems.