The rapid development of information technology has led to urgent requirements for high efficiency and ultralow power consumption. In the past few decades, neuromorphic computing has drawn extensive attention due to its promising capability in processing massive data with extremely low power consumption. Here, we offer a comprehensive review on emerging artificial neuromorphic devices and their applications. In light of the inner physical processes, we classify the devices into nine major categories and discuss their respective strengths and weaknesses. We will show that anion/cation migration-based memristive devices, phase change, and spintronic synapses have been quite mature and possess excellent stability as a memory device, yet they still suffer from challenges in weight updating linearity and symmetry. Meanwhile, the recently developed electrolyte-gated synaptic transistors have demonstrated outstanding energy efficiency, linearity, and symmetry, but their stability and scalability still need to be optimized. Other emerging synaptic structures, such as ferroelectric, metal–insulator transition based, photonic, and purely electronic devices also have limitations in some aspects, therefore leading to the need for further developing high-performance synaptic devices. Additional efforts are also demanded to enhance the functionality of artificial neurons while maintaining a relatively low cost in area and power, and it will be of significance to explore the intrinsic neuronal stochasticity in computing and optimize their driving capability, etc. Finally, by looking into the correlations between the operation mechanisms, material systems, device structures, and performance, we provide clues to future material selections, device designs, and integrations for artificial synapses and neurons.

Van der Waals heterostructures composed of two-dimensional (2D) transition metal dichalcogenides (TMD) materials have stimulated tremendous research interest in various device applications, especially in energy-efficient future-generation electronics. Such ultra-thin stacks as tunnel junction theoretically present unprecedented possibilities of tunable relative band alignment and pristine interfaces, which enable significant performance enhancement for steep-slope tunneling transistors. In this work, the optimal 2D-2D heterostructure for tunneling transistors is presented and elaborately engineered, taking into consideration both electric properties and material stability. The key challenges, including band alignment and metal-to-2D semiconductor contact resistances, are optimized separately for integration. By using a new dry transfer technique for the vertical stack, the selected WS₂/SnS₂ heterostructure-based tunneling transistor is fabricated for the first time, and exhibits superior performance with comparable on-state current and steeper subthreshold slope than conventional FET, as well as on-off current ratio over 10⁶ which is among the highest value of 2D-2D tunneling transistors. A visible negative differential resistance feature is also observed. This work shows the great potential of 2D layered semiconductors for new heterostructure devices and can guide possible development of energy-efficient future-generation electronics.