Optoelectronic synapses integrating synaptic and optical-sensing functions exhibit large advantages in neuromorphic computing for visual information processing and complex learning, recognition, and memory in an energy-efficient way. However, electric stimulation is still essential for existing optoelectronic synapses to realize bidirectional weight-updating, restricting the processing speed, bandwidth, and integration density of the devices. Herein, a two-terminal optical synapse based on a wafer-scale pyrenyl graphdiyne/graphene/PbS quantum dot heterostructure is proposed that can emulate both the excitatory and inhibitory synaptic behaviors in an optical pathway. The simple device architecture and low-dimensional features of the heterostructure endow the optical synapse with robust flexibility for wearable electronics. This optical synapse features a linear and symmetric conductance-update trajectory with numerous conductance states and low noise, which facilitates the demonstration of accurate and effective pattern recognition with a strong fault-tolerant capability even at bending states. A series of logic functions and associative learning capabilities have been demonstrated by the optical synapses in optical pathways, significantly enhancing the information processing capability for neuromorphic computing. Moreover, an integrated visible information sensing memory processing system based on the optical synapse array is constructed to perform real-time detection, in situ image memorization, and distinction tasks. This work is an important step toward the development of optogenetics-inspired neuromorphic computing and adaptive parallel processing networks for wearable electronics.

Large-Scale and Flexible Optical Synapses for Neuromorphic Computing and Integrated Visible Information Sensing Memory Processing.

Synaptic devices based neuromorphic computing applications in artificial intelligence

Monolayers of group-IV monochalcogenides, such as GeS, GeSe, SnS, SnSe, and SnTe, display interesting properties such as ferroelectricity, ferroelasticity, and unusual spin textures. This makes these materials interesting from both fundamental and applied perspectives. This Colloquium explains recent progress in the experimental characterization and theoretical understanding as well as their potential for device applications.

Colloquium: Physical properties of group-IV monochalcogenide monolayers

Intrinsic polarization coupling in 2D α-In2Se3 toward artificial synapse with multimode operations

Ferroelectric field effect transistors (FeFETs) have attracted attention as next-generation devices as they can serve as a synaptic device for neuromorphic implementation and a one-transistor (1T) for achieving high integration Since the discovery of hafnium–zirconium oxide (HZO) with high ferroelectricity (even at a thickness of several nanometers) that can be fabricated by a complementary metal–oxide–semiconductor-compatible process, FeFETs have emerged as devices with great potential In this article, the basic principles of the FeFET and the design strategies for state-of-the-art FeFETs will be discussed FeFETs using Pb(ZrxTi1−x)O3, polyvinylidene fluoride, HZO, and two-dimensional materials are emphasized FeFETs, ferroelectric semiconductor field effect transistors, and metal–ferroelectric–insulator–semiconductor structures to which those materials can be applied are introduced, and their exotic performances are investigated Finally, the limitations of these devices’ current performance and the potential of these materials are presented

Ferroelectric field effect transistors: Progress and perspective

Exploring Ferroelectric Switching in α-In2Se3 for Neuromorphic Computing

Two-dimensional ferroelectrics is attractive for synaptic device applications because of its low power consumption and amenability to high-density device integration. Here, we demonstrate that tin monosulfide (SnS) films less than 6 nm thick show optimum performance as a semiconductor channel in an in-plane ferroelectric analogue synaptic device, whereas thicker films have a much poorer ferroelectric response due to screening effects by a higher concentration of charge carriers. The SnS ferroelectric device exhibits synaptic behaviors with highly stable room-temperature operation, high linearity in potentiation/depression, long retention, and low cycle-to-cycle/device-to-device variations. The simulated device based on ferroelectric SnS achieves ∼92.1% pattern recognition accuracy in an artificial neural network simulation. By switching the ferroelectric domains partially, multilevel conductance states and the conductance ratio can be obtained, achieving high pattern recognition accuracy.

In-Plane Ferroelectric Tin Monosulfide and Its Application in a Ferroelectric Analog Synaptic Device.

Memristor devices that exhibit high integration density, fast speed, and low power consumption are candidates for neuromorphic devices. Here, we demonstrate a filament-based memristor using p-type SnS as the resistive switching material, exhibiting superlative metrics such as a switching voltage ∼0.2 V, a switching speed faster than 1.5 ns, high endurance switching cycles, and an ultralarge on/off ratio of 108. The device exhibits a power consumption as low as ∼100 fJ per switch. Chip-level simulations of the memristor based on 32 × 32 high-density crossbar arrays with 50 nm feature size reveal on-chip learning accuracy of 87.76% (close to the ideal software accuracy 90%) for CIFAR-10 image classifications. The ultrafast and low energy switching of p-type SnS compared to n-type transition metal dichalcogenides is attributed to the presence of cation vacancies and van der Waals gap that lower the activation barrier for Ag ion migration.

Yishu Zhang

Papers

Exploring Ferroelectric Switching in α-In2Se3 for Neuromorphic Computing

In-Plane Ferroelectric Tin Monosulfide and Its Application in a Ferroelectric Analog Synaptic Device.

Exploring Low Power and Ultrafast Memristor on p-Type van der Waals SnS.

Analog and Digital Mode α-In2Se3 Memristive Devices for Neuromorphic and Memory Applications