Jang‐Sik Lee

Neuromorphic computing is a promising alternative to conventional computing systems as it could enable parallel computation and adaptive learning process. However, the development of energy efficient neuromorphic hardware systems has been hindered by the limited performance of analog synaptic devices. Here, we demonstrate the analog conductance modulation behavior in the ferroelectric thin-film transistors (FeTFT) that have the nanoscale ferroelectric material and oxide semiconductors. Accurate

A flexible and transparent resistive switching memory based on a natural organic polymer for future flexible electronics is reported. The device has a coplanar structure of Mg/Ag‐doped chitosan/Mg on plastic substrate, which shows promising nonvolatile memory characteristics for flexible memory applications. It can be easily fabricated using solution processes on flexible substrates at room temperature and indicates reliable memory operations. The elucidated origin of the bipolar resistive switc

A number of synapse devices have been intensively studied for the neuromorphic system which is the next-generation energy-efficient computing method. Among these various types of synapse devices, photonic synapse devices recently attracted significant attention. In particular, the photonic synapse devices using persistent photoconductivity (PPC) phenomena in oxide semiconductors are receiving much attention due to the similarity between relaxation characteristics of PPC phenomena and Ca<sup>2+</

Abstract Neuromorphic and cognitive computing with a capability of analyzing complicated information is explored as a new paradigm of intelligent systems. An implementation of a renewable material as an essential building block of an artificial synaptic device is suggested and a flexible and transparent synaptic device based on collagen extracted from fish skin is demonstrated. This device exhibits essential synaptic behaviors including analog memory characteristics, excitatory postsynaptic curr

Organolead halide perovskites exhibit excellent optoelectronic and photovoltaic properties such as a wide range of light absorption and tunable band gaps. However, the presence of toxic elements and chemical instability under an ambient atmosphere hindered lead halide perovskites from real device applications because of environmental issues and stability. Here, we demonstrate a resistive switching memory device based on a lead-free bismuth halide perovskite (CH3NH3)3Bi2I9 (MABI). The active laye

The demand for high memory density has increased due to increasing needs of information storage, such as big data processing and the Internet of Things. Organic-inorganic perovskite materials that show nonvolatile resistive switching memory properties have potential applications as the resistive switching layer for next-generation memory devices, but, for practical applications, these materials should be utilized in high-density data-storage devices. Here, nanoscale memory devices are fabricated

A novel device structure is presented for amorphous oxide semiconductor thin-film transistors with high performance as well as improved electrical/optical stress stability. The highly stable transistor devices are developed using composition-modulated dual active layers. This approach could potentially be used to fabricate product-level display devices using amorphous oxide semiconductors in the near future. Detailed facts of importance to specialist readers are published as ”Supporting Informat

Neuromorphic devices and systems have attracted attention as next-generation computing due to their high efficiency in processing complex data. So far, they have been demonstrated using both machine-learning software and complementary metal-oxide-semiconductor-based hardware. However, these approaches have drawbacks in power consumption and learning speed. An energy-efficient neuromorphic computing system requires hardware that can mimic the functions of a brain. Therefore, various materials hav

Semiconductor device technology has continuously advanced through active research and the development of innovative technologies during the past decades. Semiconductor devices are expected to descend below the 10 nm scale within the next 10 years. Meanwhile, nanofabrication technology and the synthesis of nanostructured materials for novel device applications have made considerable progress too. This review will discuss new technologies that make this continuous device scaling possible. Then, re

Abstract Increasing demands for information‐storage capacity and for miniaturization of memory cells have driven exploration of new‐generation data storage devices, because the conventional Si‐based memory technology is approaching its fundamental physical limits. Hybrid materials and novel device structure may lead to a paradigm shift toward memory devices that have high density, multifunctionality, and low power consumption. Here, the structure and operation mechanism of resistive switching me

Tunable memory characteristics are investigated according to the metal-nanoparticle species being used in memory devices. The memory devices are fabricated using diblock copolymer micelles as templates to synthesize nanoparticles of cobalt, gold, and a binary mixture thereof. Programmable memory characteristics show different charging/discharging behaviors according to the storage element configurations as confirmed by nanoscale device characterization.

Recently, much progress has been made toward the fabrication of non-volatile memory devices based on metallic nanoparticles. Among the many kinds of nanoparticles, gold nanoparticles are some of the most widely used materials for charge trapping elements in non-volatile memory devices because they are chemically stable, easily synthesized, and have a high work function. Various synthesis methods have been applied to fabricate gold nanoparticle-based nonvolatile memory devices and recent progress

There is an increased demand for next-generation memory devices with high density and fast operation speed to replace conventional memory devices. Memristors are promising candidates for next-generation memory devices because of their scalability, stable data retention, low power consumption, and fast operation. Among the various types of memristors, halide perovskites exhibit potential as emerging materials for memristors by using hysteresis based on the movement of defects or ions in halide pe

Multiple data storage memory devices based on the controlled capacitive coupling of trapped electrons are fabricated using highly ordered arrays of metal nanoparticles. Results are presented from metal nanoparticle-based memory devices with controlled nanoparticle charge trapping elements, which undergo gate-voltage-adjustable multilevel memory states. Experimental and theoretical analysis for multilevel data manipulations and visualization of memory states are done on the nanometer scale. Detai