Continuous advancement in nonvolatile and morphotropic beyond-Moore electronic devices requires integration of ferroelectric and semiconductor materials. The emergence of hafnium oxide (HfO ₂ )–based ferroelectrics that are compatible with atomic-layer deposition has opened interesting and promising avenues of research. However, the origins of ferroelectricity and pathways to controlling it in HfO ₂ are still mysterious. We demonstrate that local helium (He) implantation can activate ferroelectricity in these materials. The possible competing mechanisms, including He ion–induced molar volume changes, vacancy redistribution, vacancy generation, and activation of vacancy mobility, are analyzed. These findings both reveal the origins of ferroelectricity in this system and open pathways for nanoengineered binary ferroelectrics.

The AI and IoT era requires software and hardware capable of efficiently processing massive amounts data quickly and at a low cost. However, there are bottlenecks in existing Von Neumann structures, including the difference in the operating speed of current-generation DRAM and Flash memory systems, the large voltage required to erase the charge of nonvolatile memory cells, and the limitations of scaled-down systems. Ferroelectric materials are one exciting means of breaking away from this structure, as Hf-based ferroelectric materials have a low operating voltage, excellent data retention qualities, and show fast switching speed, and can be used as non-volatile memory (NVM) if polarization characteristics are utilized. Moreover, adjusting their conductance enables diverse computing architectures, such as neuromorphic computing with analog characteristics or ‘logic-in-memory’ computing with digital characteristics, through high integration. Several types of ferroelectric memories, including two-terminal-based FTJs, three-terminal-based FeFETs using electric field effect, and FeRAMs using ferroelectric materials as capacitors, are currently being studied. In this review paper, we include these devices, as well as a Fe-diode with high on/off ratio properties, which has a similar structure to the FTJs but operate with the Schottky barrier modulation. After reviewing the operating principles and features of each structure, we conclude with a summary of recent applications that have incorporated them.

Herein, we present a solar-blind ultraviolet photodetector realized using atomic layer-deposited p-type cuprous oxide (Cu₂O) underneath a mechanically exfoliated n-type β-gallium oxide (β-Ga₂O₃) nanomembrane. The atomic layer deposition process of the Cu₂O film applies bis(N,N′-di-secbutylacetamidinato)dicopper(I) [Cu(⁵Bu-Me-amd)]₂ as a novel Cu precursor and water vapor as an oxidant. The exfoliated β-Ga₂O₃ nanomembrane was transferred to the top of the Cu₂O layer surface to realize a unique oxide pn heterojunction, which is not easy to realize by conventional oxide epitaxy techniques. The current–voltage (I–V) characteristics of the fabricated pn heterojunction diode show the typical rectifying behavior. The fabricated Cu₂O/β-Ga₂O₃ photodetector achieves sensitive detection of current at the picoampere scale in the reverse mode. This work provides a new approach to integrate all oxide heterojunctions using membrane transfer and bonding techniques, which goes beyond the limitation of conventional heteroepitaxy.

We have experimentally demonstrated robust beta-gallium oxide ( $\beta $ -Ga ₂ O ₃ ) ferroelectric (FE) field-effect transistors (FeFETs) on a sapphire substrate operated up to 400 °C. Atomic layer deposited (ALD) Hf _0.5 Zr _0.5 O ₂ [hafnium zirconium oxide (HZO)] is used as the FE dielectric. The HZO/ $\beta $ -Ga ₂ O ₃ FeFETs are studied for their synaptic behavior applications at elevated temperatures. The devices show distinguishable polarization switching operation with the output conductance quasi-linearly controlled by the number of input pulses on the FE gate. In a simulation, on-chip learning accuracy reaches 94% at elevated temperatures using the Modified National Institute of Standards and Technology (MNIST) data set with a simple two-layer multilayer perceptron (MLP) network. These ultra wide bandgap semiconductor devices have the potential to fill the need for harsh environment neuromorphic applications.