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In recent years, wide‐bandgap semiconductor β‐Ga2O3 material has been widely studied because of its excellent properties. Simultaneously, 2D metal oxides (2DMOs) have also become a focus of research owing to their superior stability and unique physical properties arising from quantum confinement effects. Therefore, the exploration of 2D β‐Ga2O3 is expected to reveal its novel electrical properties in electronic applications. However, the synthesis of high‐quality 2D β‐Ga2O3 remains a formidable challenge. Herein, a confined space is constructed to synthesize high‐quality 2D β‐Ga2O3 nanoflakes by enhancing the control of the kinetics of chemical vapor deposition process. In the device results, it is shown that the grown nanoflakes have excellent switching properties and potential artificial synaptic response characteristics. Based on this premise, an artificial recognition system for handwritten numerals is developed, achieving a peak recognition accuracy of approximately 96%. This system holds significant potential for application within an emerging neuromorphic recognition framework tailored for advanced driver‐assistance systems. In this work, a new feasible pathway is provided for the synthesis of 2D non‐layered oxides and the potential of 2D oxides in the field of neuroanalog electronics and recognition is shown, thereby advancing the fields of 2D β‐Ga2O3 electronics and 2DMOs electronics. [ABSTRACT FROM AUTHOR]

The emergence of 2D van der Waals (vdW) materials, owing to highly tunable electrical conductivity, remarkably free stackability, and excellent compatibility for heterojunction integration, has provided abundant research diversity of artificial synapses. Here, an innovative 2D vdW heterosynaptic memtransistor (vdW‐HT) synapse is proposed with a ferroelectric CuInP2S6 inserted layer. Neuromorphic synaptic weight change of the vdW‐HT synapse in this work are modulated by the synergistic effects of interlayer coupling and ferroelectric polarization reversal. It is the first time to evaluate the required initial energy consumption of ferroelectric vdW‐HT synapses with matrixed biomimetic characteristics of “Learning–Forgetting–Re‐learning–Memorizing.” The required initial energy consumption is only ≈3.06 pJ, which provided supporting evidence to indicate the promising potential of vdW‐HT synapses in exploring neuromorphic applications. A vdW‐HT computing system with artificial recognition capability for intelligent automobiles is established and demonstrated outstanding recognition abilities for multiple targets in various environments. The highest recognition accuracy for pedestrians is 98%. In addition, the excellent recognition property is integrated with a robotic arm, successfully achieving high‐precision grasping behavior and designated position transmission for identified targets. These results provide promising strategies for the integrated development of emerging neuromorphic electronics and industrial applications. [ABSTRACT FROM AUTHOR]

Miniaturizing van der Waals (vdW) ferroelectric materials to atomic scales is essential for modern devices like nonvolatile memory and sensors. To unlock their full potential, their growth mechanisms, interface effects, and stabilization are preferably investigated, particularly for ultrathin 2D nanosheets with single‐unit cell thickness. This study focuses on Bi2TeO5 (BTO) and utilizes precise control over growth kinetics at the nucleation temperature to create specific interfacial reconfiguration layers. Ultrathin BTO nanosheets with planar ferroelectricity at a single‐unit cell thickness are successfully grown. Atomic‐scale characterization reveals a disordered distribution of elements in the interfacial layer, which buffers strain from lattice mismatch. The theoretical calculations support these observations. Furthermore, this strategy also can be extended to the growth of a variety of 2D ternary oxide nanosheets. This work contributes to a better understanding of growth and stability mechanisms in 2D ultrathin nanosheets. [ABSTRACT FROM AUTHOR]

Resistive random access memory (RRAM) devices with Ni/AlO x /Pt-structure were manufactured by deposition of a solution-based aluminum oxide (AlO x ) dielectric layer which was subsequently annealed at temperatures from 200 °C to 300 °C, in increments of 25 °C. The devices displayed typical bipolar resistive switching characteristics. Investigations were carried out on the effect of different annealing temperatures for associated RRAM devices to show that performance was correlated with changes of hydroxyl group concentration in the AlO x thin films. The annealing temperature of 250 °C was found to be optimal for the dielectric layer, exhibiting superior performance of the RRAM devices with the lowest operation voltage (<1.5 V), the highest ON/OFF ratio (>10 4 ), the narrowest resistance distribution, the longest retention time (>10 4 s) and the most endurance cycles (>150).