Donghun Lee

The memristor, a composite word of memory and resistor, has become one of the most important electronic components for brain-inspired neuromorphic computing in recent years. This device has the ability to control resistance with multiple states by memorizing the history of previous electrical inputs, enabling it to mimic a biological synapse in the neural network of the human brain. Among many candidates for memristive materials, including metal oxides, organic materials, and low-dimensional nan

Abstract Two-dimensional (2D) semiconductors hold promises for electronic and optoelectronic applications due to their outstanding electrical and optical properties. Despite a short research history, a wide range of ‘proof-of-concept’ devices based on 2D materials have been demonstrated, highlighting their impact in advanced technology. Here we review the unique properties 2D semiconducting materials and their applications in terms of electronic and optoelectronic devices. We summarize all the e

The development of energy-efficient artificial synapses capable of manifoldly tuning synaptic activities can provide a significant breakthrough toward novel neuromorphic computing technology. Here, a new class of artificial synaptic architecture, a three-terminal device consisting of a vertically integrated monolithic tungsten oxide memristor, and a variable-barrier tungsten selenide/graphene Schottky diode, termed as a 'synaptic barrister,' are reported. The device can implement essential synap

Two-dimensional stacks of dissimilar hexagonal monolayers exhibit unusual electronic, photonic and photovoltaic responses that arise from substantial interlayer excitations. Interband excitation phenomena in individual hexagonal monolayer occur in states at band edges (valleys) in the hexagonal momentum space; therefore, low-energy interlayer excitation in the hexagonal monolayer stacks can be directed by the two-dimensional rotational degree of each monolayer crystal. However, this rotation-dep

Heterosynaptic neuromodulation is a key enabler for energy-efficient and high-level biological neural processing. However, such manifold synaptic modulation cannot be emulated using conventional memristors and synaptic transistors. Thus, reported herein is a three-terminal heterosynaptic memtransistor using an intentional-defect-generated molybdenum disulfide channel. Particularly, the defect-mediated space-charge-limited conduction in the ultrathin channel results in memristive switching charac

In optoelectronic devices based on two-dimensional (2D) semiconductor heterojunctions, the efficient charge transport of photogenerated carriers across the interface is a critical factor to determine the device performances. Here, we report an unexplored approach to boost the optoelectronic device performances of the WSe₂-MoS₂ <i>p</i>-<i>n</i> heterojunctions via the monolithic-oxidation-induced doping and resultant modulation of the interface band alignment. In the propos

Assembling solution-processed van der Waals ( vdW ) materials into thin films holds great promise for constructing large-scale, high-performance thin-film electronics, especially at low temperatures. While transition metal dichalcogenide thin films assembled in solution have shown potential as channel materials, fully solution-processed vdW electronics have not been achieved due to the absence of suitable dielectric materials and high-temperature processing. In this work, we report on all-soluti

Abstract Ultralow power chemical sensing is essential toward realizing the Internet of Things. However, electrically driven sensors must consume power to generate an electrical readout. Here, a different class of self‐powered chemical sensing platform based on unconventional photovoltaic heterojunctions consisting of a top graphene (Gr) layer in contact with underlying photoactive semiconductors including bulk silicon and layered transition metal dichalcogenides is proposed. Owing to the chemica

The combined characteristics of non-wettabililty and strong plasmonic resonances make superhydrophobic plasmonic nanostructures an appealing tool for ultrasensitive detection in surface-enhanced Raman scattering (SERS). However, inducing superhydrophobic surfaces on originally hydrophilic metals (e.g., gold, silver) while achieving high plasmonic enhancement requires sophisticated surface engineering and often involves complex fabrication processes. In this article, we design and fabricate cost

In this study, we present a classification method for ternary small data using the modified ternary Allen–Cahn (tAC) system. The governing system is the tAC equation with the fidelity term, which keeps the solution as close as possible to the given data. To solve the tAC system with the fidelity term, we apply an operator splitting method. We use an implicit-explicit finite difference method for solving the split equations. To validate the robust and superior performance of the proposed numerica

Large-area and uniform plasmonic nanostructures have often been fabricated by simply evaporating noble metals such as gold and silver on a variety of nanotemplates such as nanopores, nanotubes, and nanorods. However, some highly uniform nanotemplates are limited to be utilized by long, complex, and expensive fabrication. Here, we introduce a cost-effective and high-throughput fabrication method for plasmonic interference coupled nanostructures based on quasi-uniform anodic aluminum oxide (QU-AAO