Inspired by the biological neuromorphic system, which exhibits a high degree of connectivity to process huge amounts of information, photonic memory is expected to pave a way to overcome the von Neumann bottleneck for nonconventional computing. Here, a photonic flash memory based on all-inorganic CsPbBr perovskite quantum dots (QDs) is demonstrated. The heterostructure formed between the CsPbBr QDs and semiconductor layer serves as a basis for optically programmable and electrically erasable characteristics of the memory device. Furthermore, synapse functions including short-term plasticity, long-term plasticity, and spike-rate-dependent plasticity are emulated at the device level. The photonic potentiation and electrical habituation are implemented and the synaptic weight exhibits multiple wavelength response from 365, 450, 520 to 660 nm. These results may locate the stage for further thrilling novel advances in perovskite-based memories.

Flexible sensors that efficiently detect various stimuli relevant to specific environmental or biological species have been extensively studied due to their great potential for the Internet of Things and wearable electronics applications. The application of flexible and stretchable electronics to device-engineering technologies has enabled the fabrication of slender, lightweight, stretchable, and foldable sensors. Here, recent studies on flexible sensors for biological analytes, ions, light, and pH are outlined. In addition, contemporary studies on device structure, materials, and fabrication methods for flexible sensors are discussed, and a market overview is provided. The conclusion presents challenges and perspectives in this field.

The in-depth understanding of ions' generation and movement inside all-inorganic perovskite quantum dots (CsPbBr QDs), which may lead to a paradigm to break through the conventional von Neumann bottleneck, is strictly limited. Here, it is shown that formation and annihilation of metal conductive filaments and Br ion vacancy filaments driven by an external electric field and light irradiation can lead to pronounced resistive-switching effects. Verified by field-emission scanning electron microscopy as well as energy-dispersive X-ray spectroscopy analysis, the resistive switching behavior of CsPbBr QD-based photonic resistive random-access memory (RRAM) is initiated by the electrochemical metallization and valance change. By coupling CsPbBr QD-based RRAM with a p-channel transistor, the novel application of an RRAM-gate field-effect transistor presenting analogous functions of flash memory is further demonstrated. These results may accelerate the technological deployment of all-inorganic perovskite QD-based photonic resistive memory for successful logic application.

Bioinspired artificial haptic neuron system has received much attention in the booming artificial intelligence industry for its broad range of high-impact applications such as personal healthcare monitoring, electronic skins, and human-machine interfaces. An artificial haptic neuron system is designed by integrating a piezoresistive sensor and a Nafion-based memristor for the first time in this paper. The piezoresistive sensor serves as a sensory receptor to transform mechanical stimuli into electric signals, and the Nafion-based memristor serves as the synapse to further process the information. The pyramid-structured sensor exhibits excellent sensitivity (6.7 × 10 7 kPa −1 in 1-5 kPa and 3.8 × 10 5 kPa −1 in 5-50 kPa) and durability (>7000 cycles), while the memristor realizes fundamental synaptic functions under low power consumption (10-200 pJ) and remains stable for over 10 4 consecutive tests. The integrated system can detect tactile stimuli encoded with temporal information, such as the count, frequency, duration and speed of the external force. As a proof-of-concept, English characters recognition with high accuracy can be achieved on the system under a supervised learning method. This work shows promising potential in bioinspired sensing systems owing to the high performance, excellent durability, and simple fabrication procedure.

The continued growth in the demand of data storage and processing has spurred the development of high-performance storage technologies and brain-inspired neuromorphic hardware. Semiconductor quantum dots (QDs) offer an appealing option for these applications since they combine excellent electronic/optical properties and structural stability and can address the requirements of low-cost, large-area, and solution-based manufactured technologies. Here, we focus on the development of nonvolatile memories and neuromorphic computing systems based on QD thin-film solids. We introduce recent advances of QDs and highlight their unique electrical and optical features for designing future electronic devices. We also discuss the advantageous traits of QDs for novel and optimized memory techniques in both conventional flash memories and emerging memristors. Then, we review recent advances in QD-based neuromorphic devices from artificial synapses to light-sensory synaptic platforms. Finally, we highlight major challenges for commercial translation and consider future directions for the postsilicon era.