Emulating synaptic response in n- and p-channel MoS₂ transistors by utilizing charge trapping dynamics

Area of Science:

• Materials Science
• Neuroscience
• Computer Engineering

Background:

• Neuromorphic computing seeks to overcome the limitations of von Neumann architectures in terms of computational complexity and power consumption.
• Spiking neural networks (SNNs), crucial for neuromorphic computing, require hardware emulating neuronal and synaptic functions.
• Existing hardware struggles to efficiently mimic the complex behavior of biological synapses.

Purpose of the Study:

• To develop and characterize novel synaptic devices for neuromorphic computing applications.
• To leverage electron trapping phenomena in atomically thin transistors to emulate synaptic plasticity.
• To demonstrate the potential of these devices for implementing learning rules like STDP.

Main Methods:

• Fabrication and characterization of re-doped (n-type) and Nb-doped (p-type) molybdenum disulfide (MoS2) field-effect transistors.
• Utilized pulsed-gate measurements to investigate electron trapping/de-trapping dynamics and synaptic behavior.
• Quantified short-term plasticity using pulse-paired facilitation (PPF) and long-term plasticity through potentiation and depression measurements.

Main Results:

• MoS2 transistors demonstrated short-term plasticity (ms) and long-term plasticity (minutes) mimicking synaptic memory.
• Observed PPF time constants closely matched biological synapses (τ1 = 27.4 ms, τ2 = 725 ms).
• Devices exhibited analog behavior with over 50 accessible conductance states and successfully emulated spike-time-dependent plasticity (STDP).

Conclusions:

• Atomically thin MoS2 transistors effectively emulate synaptic functions, including short/long-term plasticity and STDP.
• These synaptic devices offer advantages over existing iontronic counterparts for neuromorphic hardware development.
• The findings pave the way for novel hardware implementations in brain-inspired computing.