Toward Ubiquitous Electronics with 2D Materials and 3D Printing: Atomically Thin Optoelectronic Machine Vision Processor and Gigahertz RF Electronics via Direct Ink Writing

Abstract

The development of silicon semiconductor technology has produced breakthroughs in electronics by downscaling the physical size of devices and wires to the nanometer regime. However, silicon-based complementary metal–oxide–semiconductor (CMOS) technology is approaching its downscaling limit. Meanwhile, there is compelling demand for stretchable and flexible electronics— which are challenging to achieve with CMOS—, for numerous futuristic applications such as wearable systems, smart cities, and Internet-of-Things (IoT). Therefore, radically different types of materials and devices are needed to realize the potential of the next generation of electronics. Leveraging two-dimensional (2D) materials and three-dimensional (3D) printing, I have worked on two projects at Harvard, to realize innovations in design, fabrication and functionality of electronics for ubiquitous applications. These two pieces of work comprise the present thesis. In the first work, we explore the potential of 3D printing for creating radio-frequency (RF) passive devices as well as their integration into active RF electronic circuits. Specifically, we produce a broad array of RF passives that operate at GHz frequencies via direct ink writing, including lumped devices and wave-based devices, whose maximum quality factors (Q) and operational frequencies exceed 40 and 45 GHz, respectively. Moreover, to demonstrate the utility of these printed RF passive structures in active RF electronic circuits, we combine them with discrete transistors to fabricate self-sustained oscillators, synchronized oscillator arrays, and wireless transmitters clocked by the oscillators. In the other work, we investigate two-dimensional (2D) semiconductors, in particular transition metal dichalcogenide (TMD) monolayers. We expand the functional complexity of 2D integrated circuits (ICs) through a tenfold increase in the device integration scale. Specifically, we have developed an analog optoelectronic processor comprised of 1,024 photo field-effect transistors (photo-FETs) arranged in a crossbar array structure. Through capturing of optical images into electrical data (like the eye and optic nerve), and subsequent recognition of this data (like the brain) via analog in-memory computing, our optoelectronic processor emulates the two core functions of human vision.