Emerging 2D Metal Oxides: From Synthesis to Device Integration

Abstract

2D metal oxides have aroused increasing attention in the field of electronics and optoelectronics due to their intriguing physical properties. In this review, an overview of recent advances on synthesis of 2D metal oxides and their electronic applications is presented. First, the tunable physical properties of 2D metal oxides that relate to the structure (various oxidation‐state forms, polymorphism, etc.), crystallinity and defects (anisotropy, point defects, and grain boundary), and thickness (quantum confinement effect, interfacial effect, etc.) are discussed. Then, advanced synthesis methods for 2D metal oxides besides mechanical exfoliation are introduced and classified into solution process, vapor‐phase deposition, and native oxidation on a metal source. Later, the various roles of 2D metal oxides in widespread applications, i.e., transistors, inverters, photodetectors, piezotronics, memristors, and potential applications (solar cell, spintronics, and superconducting devices) are discussed. Finally, an outlook of existing challenges and future opportunities in 2D metal oxides is proposed.

Recent Progress on Phase Engineering of Nanomaterials

“…Apart from TMDs, transition metal oxides also show great promise in optoelectronic applications due to their relatively wide bandgap, high breakdown electric field, and high stability . Among them, TiO 2 has attracted a lot of attention because of its phase-dependent optoelectronic properties.…”

“…Apart from TMDs, transition metal oxides also show great promise in optoelectronic applications due to their relatively wide bandgap, high breakdown electric field, and high stability. 1304 Among them, TiO 2 has attracted a lot of attention because of its phase-dependent optoelectronic properties. The bandgaps of the anatase, rutile, and brookite phases of TiO 2 are 3.2, 3.0, and 3.1 eV, respectively, which are suitable for UV photodetectors.…”

Definition of a Localized Conducting Path via Suppressed Charge Injection in Oxide Memristors for Stable Practical Hardware Neural Networks

“…6 Such a device has been demonstrated as an ideal memory component for hardware neural networks from the perspectives of integration density and electrical characteristics. 7−9 Various types of memristors, such as a photonic memristor based on the phosphorene nanoparticles, 10 an organic memristor, 11−13 a 2D material-based memristor, 14 and an oxide-based memristor, 15,16 have been utilized as memory components in the neuromorphic systems. In particular, the oxide memristor has been evaluated as a promising option for artificial synapses in hardware neural networks due to its large scalability and high compatibility with the complementary metal oxide semiconductor.…”

“…Therefore, it is essential to develop a promising memory device with high integration density to achieve practical neural networks. , The mechanisms and applications of a resistive switching device known as a memristor have been studied using physical models and simulations . Such a device has been demonstrated as an ideal memory component for hardware neural networks from the perspectives of integration density and electrical characteristics. − Various types of memristors, such as a photonic memristor based on the phosphorene nanoparticles, an organic memristor, − a 2D material-based memristor, and an oxide-based memristor, , have been utilized as memory components in the neuromorphic systems. In particular, the oxide memristor has been evaluated as a promising option for artificial synapses in hardware neural networks due to its large scalability and high compatibility with the complementary metal oxide semiconductor. − For the oxide-based memristor, through the application of electric stimuli, a conducting filament (CF) composed of oxygen vacancies forms within an oxide-insulating film, leading to its resistive switching characteristics.…”

Covalent Organic Frameworks for Neuromorphic Devices

“…Nevertheless, the ideal neuromorphic devices, as the building block of the neuromorphic systems, generally require low operation energy consumption, high linearity and symmetry of programmable conductance states, and tailorable state-retention time. To this end, various materials, including oxides, − perovskites, − organic materials, , quantum dots, chalcogenides, , MXene, , and other 2D materials, ,, have been explored for high-performance neuromorphic devices (e.g., memristors, synaptic transistors, and optoelectronic synaptic devices). − …”