Neuromorphic computing systems that are capable of parallel information storage and processing with high area and energy efficiencies, offer important opportunities for future storage systems and in‐memory computing. Here, it is shown that a carbon dots/silk protein (CDs/silk) blend can be used as a light‐tunable charge trapping medium to fabricate an electro‐photoactive transistor synapse. The synaptic device can be optically operated in volatile or nonvolatile modes, ensuring concomitant short‐term and long‐term neuroplasticity. The synaptic‐like behaviors are attributed to the photogating effect induced by trapped photogenerated electrons in the hybrid CDs/silk film which is confirmed with atomic force microscopy based electrical techniques. In addition, system‐level pattern recognition capability of the synaptic device is evaluated by a single‐layer perceptron model. The remote optical operation of neuromorphic architecture provides promising building blocks to complete bioinspired photonic computing paradigms.

The threshold switching (TS) phenomenon in memristors has drawn great attention for its versatile applications in selectors, artificial neurons, true random number generators, and electronic integrations. The transition between nonvolatile resistive switching and volatile TS modes can be realized by doping, varying annealing and voltage sweeping conditions, or imposing different compliance current. Here, a strategy is reported to achieve such transition by the noninvasive UV light stimulus based on InP/ZnS quantum dot (QD) memristor. The core-shell InP/ZnS QDs with quasi-type II band alignment ensures photoexcited electrons localized in InP core, photoexcited hole state distributed in the outer shell, and subsequent lifetime controlling of conductive filament under light irradiation. Systematic mechanism investigations indicate that UV photogenerated holes are accumulated on the surface of the QD film, which is consistent with rapid transfer of photogenerated holes in the coreshell InP/ZnS structure. Based on the light-modulated effect, a reconfigurable 9 × 9 visual data storage array with a key pattern and a simple leaky integrateand-fire circuit are constructed. These results suggest the potential of direct optical modulation of memory mode through energy band engineering, leading to future optoelectronic and electronic device for the implementation of neuromorphic visual system and artificial neural networks.

2D materials with intriguing properties have been widely used in optoelectronics. However, electronic devices suffered from structural damage due to the ultrathin materials and uncontrolled defects at interfaces upon metallization, which hindered the development of reliable devices. Here, a damage‐free Au/h‐BN/Au memristor is reported using a clean, water‐assisted metal transfer approach by physically assembling Au electrodes onto the layered h‐BN which minimized the structural damage and undesired interfacial defects. The memristors demonstrate significantly improved performance with the coexistence of nonpolar and threshold switching as well as tunable current levels by controlling the compliance current, compared with devices with evaporated contacts. The devices integrated into an array show suppressed sneak path current and can work as both logic gates and latches to implement logic operations allowing in‐memory computing. Cross‐sectional scanning transmission electron microscopy analysis validates the feasibility of this nondestructive metal integration approach, the crucial role of high‐quality atomically sharp interface in resistive switching, and a direct observation of percolation path. The underlying mechanism of boron vacancies‐assisted transport is further supported experimentally by conductive atomic force microscopy free from process‐induced damage, and theoretically by ab initio simulations.

By virtue of energy efficiency, high speed, and parallelism, brain‐inspired neuromorphic computing is a promising technology to overcome the von Neumann bottleneck and capable of processing massive sophisticated tasks in the background of big data. The abilities of perceiving and reacting to events in artificial neuromorphic systems allow us to build the communicative electronic–biological interfaces to get closer to electronic life. Protein materials offer great application potentials in such a system due to their sustainability, low cost, controllable hierarchical structure, intrinsic biocompatibility, and biodegradability. Herein, a timely review of the development of protein‐based memories for data storage and neuromorphic computing is provided. Proteins’ unique mechanical, electronic, optical properties, and their broad applications are discussed. Then, the progress of protein‐based two‐terminal memristor and three‐terminal transistor‐type memory is reviewed, and their applications for data storage, logic circuit, and neuromorphic computing are introduced. Finally, the major challenges and outlook toward the future developing directions of protein‐based computing systems are pointed out.

In article number 1909114, Ye Zhou, Su‐Ting Han, and co‐workers present a photonic memristor featuring UV‐sensitive quantum dot‐based switching media. The memristive device can be readily switched from the nonvolatile to volatile threshold regime via UV light, providing a noninvasive method for storing data in both a temporal and permanent manner in a single device.

Resistive random access memory (RRAM) based on hybrid organic-inorganic halide perovskite (HOIP) has recently gained significant interests due to its low activation energy of ion migration. HOIP RRAM has been...

In this paper, new upconversion (UC) phosphors for Yb3+-Er3+ and Yb3+-Ho3+ doped Gd9.33(SiO4)6O2 (GSO) were designed via solid-state reaction method. The phase purity of the samples was examined by XRD...

Brain-inspired neuromorphic computing has been extensively researched, taking advantage of increased computer power, the acquisition of massive data, and algorithm optimization. Neuromorphic computing requires mimicking synaptic plasticity and enables near-in-sensor computing. In synaptic transistors, how to elaborate and examine the link between microstructure and characteristics is a major difficulty. Due to the absence of interlayer shielding effects, defect-free interfaces, and wide spectrum responses, reducing the thickness of organic crystals to the 2D limit has a lot of application possibilities in this computing paradigm. This paper presents an update on the progress of 2D organic crystal-based transistors for data storage and neuromorphic computing. The promises and synthesis methodologies of 2D organic crystals are summarized. Following that, applications of 2D organic crystals for ferroelectric nonvolatile memory, circuit-type optoelectronic synapses, and neuromorphic computing are addressed. Finally, new insights and challenges for the field's future prospects are presented, pushing the boundaries of neuromorphic computing even farther.