Two-dimensional Materials for Energy-Efficient Computing

In this talk, I will focus on describing a new paradigm of devices based on two-dimensional (2D) materials for sensing, computing, storage, and hardware security inspired by various insect, avian, and mammalian brains. We exploit unique electronic and optoelectronic properties of layered 2D materials to design high-performance, ultra-low-power, artificially intelligent, and inherently secure solid-state devices inspired by natural intelligence. For example, we have mimicked auditory information processing in barn owls (<i>Nature Communications</i>, <i>10, 3450, 2019</i>), collision avoidance by locusts (<i>Nature Electronics, 3, 646–655, 2020</i>), and subthreshold signal detection by paddlefish and cricket using stochastic resonance (<i>Nature Communications, 2020</i>). We have also mimicked probabilistic computing in animal brains using low-power Gaussian synapses (<i>Nature Communications</i>,<i> 10, 4199, 2019</i>), and memristive graphene synapses (<i>Nature Communications, 11, 5474, 2020</i>) and realized biomimetic devices that can emulate neurotransmitter release in chemical synapses (<i>ACS Nano</i>, <i>11, 3, 2017</i><i>)</i> and neural encoding in afferent neurons<i> (</i><i>Nature Communications, 12, 2143, 2021</i><i>)</i>. We have also made thes devices secure through SAT-attack-resistant hardware obfuscation using camouflaged 2D heterostructures (<i>ACS Nano, 15, 2, 2021</i>) and by realizing machine learning resilient and reconfigurable physically unclonable functions (<i>Nature Electronics 4, 364-374, 2021</i>).