Heejun Yang

Artificial van der Waals heterostructures with two-dimensional (2D) atomic crystals are promising as an active channel or as a buffer contact layer for next-generation devices. However, genuine 2D heterostructure devices remain limited because of impurity-involved transfer process and metastable and inhomogeneous heterostructure formation. We used laser-induced phase patterning, a polymorph engineering, to fabricate an ohmic heterophase homojunction between semiconducting hexagonal (2H) and meta

Despite several years of research into graphene electronics, sufficient on/off current ratio I(on)/I(off) in graphene transistors with conventional device structures has been impossible to obtain. We report on a three-terminal active device, a graphene variable-barrier "barristor" (GB), in which the key is an atomically sharp interface between graphene and hydrogenated silicon. Large modulation on the device current (on/off ratio of 10(5)) is achieved by adjusting the gate voltage to control the

The dynamic processing of optoelectronic signals carrying temporal and sequential information is critical to various machine learning applications including language processing and computer vision. Despite extensive efforts to emulate the visual cortex of human brain, large energy/time overhead and extra hardware costs are incurred by the physically separated sensing, memory, and processing units. The challenge is further intensified by the tedious training of conventional recurrent neural netwo

Abstract The large-scale crossbar array is a promising architecture for hardware-amenable energy efficient three-dimensional memory and neuromorphic computing systems. While accessing a memory cell with negligible sneak currents remains a fundamental issue in the crossbar array architecture, up-to-date memory cells for large-scale crossbar arrays suffer from process and device integration (one selector one resistor) or destructive read operation (complementary resistive switching). Here, we intr

Synaptic computation, which is vital for information processing and decision making in neural networks, has remained technically challenging to be demonstrated without using numerous transistors and capacitors, though significant efforts have been made to emulate the biological synaptic transmission such as short-term and long-term plasticity and memory. Here, we report synaptic computation based on Joule heating and versatile doping induced metal-insulator transition in a scalable monolayer-mol

Engineering surface atoms of transition metal dichalcogenides (TMDs) is a promising way to design catalysts for efficient electrochemical reactions including the hydrogen evolution reaction (HER). However, materials processing based on TMDs, such as vacancy creation or edge exposure, for active HER, has resulted in insufficient atomic-precision lattice homogeneity and a lack of clear understanding of HER over 2D materials. Here, we report a durable and effective HER at atomically defined reactio

Electron scattering at graphene edges is expected to make a crucial contribution to the electron transport in graphene nanodevices by producing quantum interferences. Atomic-scale scanning tunneling microscopy (STM) topographies of different edge structures of monolayer graphene show that the localization of the electronic density of states along the C-C bonds, a property unique to monolayer graphene, results in quantum interference patterns along the graphene carbon bond network, whose shapes d

Doping two-dimensional (2D) semiconductors beyond their degenerate levels provides the opportunity to investigate extreme carrier density-driven superconductivity and phase transition in 2D systems. Chemical functionalization and the ionic gating have achieved the high doping density, but their effective ranges have been limited to ∼1 nm, which restricts the use of highly doped 2D semiconductors. Here, we report on electron diffusion from the 2D electride [Ca 2 N] + ·e – to MoTe 2 over a distanc

Polymorphic 2D materials allow structural and electronic phase engineering, which can be used to realize energy-efficient, cost-effective, and scalable device applications. The phase engineering covers not only conventional structural and metal-insulator transitions but also magnetic states, strongly correlated band structures, and topological phases in rich 2D materials. The methods used for the local phase engineering of 2D materials include various optical, geometrical, and chemical processes

Diverse synaptic plasticity with a wide range of timescales in biological synapses plays an important role in memory, learning, and various signal processing with exceptionally low power consumption. Emulating biological synaptic functions by electric devices for neuromorphic computation has been considered as a way to overcome the traditional von Neumann architecture in which separated memory and information processing units require high power consumption for their functions. Synaptic devices a

Abstract Phase engineering is a breakthrough for various electronic and energy device applications with transition metal dichalcogenides (TMDs). Chemical methods, such as lithium intercalation, are mostly used for phase engineering, which achieves atomically thin flakes and high catalytic performances in several group 6 TMDs including MoS 2 . However, chemical methods cannot be applied to MoTe 2 , a widely investigated group 6 TMD with intriguing semiconducting, topological, and catalytic proper