Abstract: Advances in silicon-based digital electronics and improved understanding of the human brain have spurred tremendous interest in artificial intelligence and neuromorphic computing. The last few decades have seen a rapid rise in both computation power and theoretical framework that has resulted in more efficient solutions for specialized cognitive tasks. Since logic processing and memory are intimately connected, neural computation is not burdened by the von Neumann bottleneck. However, progress in artificial intelligence has fallen short of initial predictions and inspired the new approach of hardware implementation using a nano-ionic device that mimics biological neuron at a fundamental level.

I will discuss an artificial synapse realized in a device called a memtransistor that is based on single-layer semiconducting MoS₂. The internal resistance of the device is tuned not only by the biasing history but also by a third gate terminal. Furthermore, an open architecture channel allows multiple electrodes, resulting in elusive heterosynaptic plasticity — a necessary ingredient for hyperconnectivity. In addition, an artificial neuron is needed to integrate signals received via the synapses and fires a charge wave along the axon, causing subsequent synaptic switching.

I will discuss a practical route to designing artificial neurons based on films from solution-processed two-dimensional materials that embody two coupled state variables (temperature and charge) needed for action-potential based computation. An alternative artificial neuron based on heterojunctions will also be presented to circumvent the issues of stochasticity. Finally, a new fabrication method and a new memtransistor crossbar architecture will be discussed to achieve the desired scaling. I will conclude with future goals in fundamental research and applications.

Bio: Vinod K. Sangwan is a postdoctoral researcher at Northwestern University. He received a B. Tech. in engineering physics from the Indian Institute of Technology Mumbai and  a Ph.D. in physics from the University of Maryland. His research spans several disciplines including applied physics, electrical engineering, materials science, and chemistry. His current interests are defects dynamics in 2-D materials, nanoscale transport, ultrafast optical processes, emerging photovoltaic materials and devices, and quantum materials.