Optically Stimulated Artificial Synapse Based on Layered Black Phosphorus

Hebbian models of development and learning require both activity-dependent synaptic plasticity and a mechanism that induces competition between different synapses. One form of experimentally observed long-term synaptic plasticity, which we call spike-timing-dependent plasticity (STDP), depends on the relative timing of pre- and postsynaptic action potentials. In modeling studies, we find that this form of synaptic modification can automatically balance synaptic strengths to make postsynaptic firing irregular but more sensitive to presynaptic spike timing. It has been argued that neurons in vivo operate in such a balanced regime. Synapses modifiable by STDP compete for control of the timing of postsynaptic action potentials. Inputs that fire the postsynaptic neuron with short latency or that act in correlated groups are able to compete most successfully and develop strong synapses, while synapses of longer-latency or less-effective inputs are weakened. Show more

Graphene and transition metal dichalcogenides (TMDCs) are the two major types of layered materials under intensive investigation. However, the zero-bandgap nature of graphene and the relatively low mobility in TMDCs limit their applications. Here we reintroduce black phosphorus (BP), the most stable allotrope of phosphorus with strong intrinsic in-plane anisotropy, to the layered-material family. For 15-nm-thick BP, we measure a Hall mobility of 1,000 and 600 cm(2)V(-1)s(-1) for holes along the light (x) and heavy (y) effective mass directions at 120 K. BP thin films also exhibit large and anisotropic in-plane optical conductivity from 2 to 5 μm. Field-effect transistors using 5 nm BP along x direction exhibit an on-off current ratio exceeding 10(5), a field-effect mobility of 205 cm(2)V(-1)s(-1), and good current saturation characteristics all at room temperature. BP shows great potential for thin-film electronics, infrared optoelectronics and novel devices in which anisotropic properties are desirable. Show more

Memory is believed to occur in the human brain as a result of two types of synaptic plasticity: short-term plasticity (STP) and long-term potentiation (LTP; refs 1-4). In neuromorphic engineering, emulation of known neural behaviour has proven to be difficult to implement in software because of the highly complex interconnected nature of thought processes. Here we report the discovery of a Ag(2)S inorganic synapse, which emulates the synaptic functions of both STP and LTP characteristics through the use of input pulse repetition time. The structure known as an atomic switch, operating at critical voltages, stores information as STP with a spontaneous decay of conductance level in response to intermittent input stimuli, whereas frequent stimulation results in a transition to LTP. The Ag(2)S inorganic synapse has interesting characteristics with analogies to an individual biological synapse, and achieves dynamic memorization in a single device without the need of external preprogramming. A psychological model related to the process of memorizing and forgetting is also demonstrated using the inorganic synapses. Our Ag(2)S element indicates a breakthrough in mimicking synaptic behaviour essential for the further creation of artificial neural systems that emulate characteristics of human memory. Show more