Energy efficiency, parallel information processing, and unsupervised learning make the human brain a model computing system for unstructured data handling. Different types of oxide memristors can emulate synaptic functions in artificial neuromorphic circuits. However, their cycle‐to‐cycle variability or strict epitaxy requirements remain a challenge for applications in large‐scale neural networks. Here, solution‐processable ferroelectric tunnel junctions (FTJs) with P(VDF‐TrFE) copolymer barriers are reported showing analog memristive behavior with a broad range of accessible conductance states and low energy dissipation of 100 fJ for the onset of depression and 1 pJ for the onset of potentiation by resetting small tunneling currents on nanosecond timescales. Key synaptic functions like programmable synaptic weight, long‐ and short‐term potentiation and depression, paired‐pulse facilitation and depression, and Hebbian and anti‐Hebbian learning through spike shape and timing‐dependent plasticity are demonstrated. In combination with good switching endurance and reproducibility, these results offer a promising outlook on the use of organic FTJ memristors as building blocks in artificial neural networks.

A multifunctional optoelectronic resistive switching memory, composed of a simple ITO/CeO2- x/AlOy/Al structure, is demonstrated. Arising from the photo-induced detrapping, electrode-injection and retrapping of electrons in the CeO2-x/AlOy/Al interfacial region, the device shows broadband, linear, and persistent photoresponses that can be used for the integration of demodulating, arithmetic, and memory functions in a single device for future optoelectronic interconnect systems.

Memristive devices are able to store and process information, which offers several key advantages over the transistor-based architectures. However, most of the two-terminal memristive devices have fixed functions once made and cannot be reconfigured for other situations. Here, we propose and demonstrate a memristive device "memlogic" (memory logic) as a nonvolatile switch of logic operations integrated with memory function in a single light-gated memristor. Based on nonvolatile light-modulated memristive switching behavior, a single memlogic cell is able to achieve optical and electrical mixed basic Boolean logic of reconfigurable "AND", "OR", and "NOT" operations. Furthermore, the single memlogic cell is also capable of functioning as an optical adder and digital-to-analog converter. All the memlogic outputs are memristive for in situ data storage due to the nonvolatile resistive switching and persistent photoconductivity effects. Thus, as a memdevice, the memlogic has potential for not only simplifying the programmable logic circuits but also building memristive multifunctional optoelectronics.

The integration and cooperation of mechanoreceptors, neurons and synapses in somatosensory systems enable humans to efficiently sense and process tactile information. Inspired by biological somatosensory systems, we report an optoelectronic spiking afferent nerve with neural coding, perceptual learning and memorizing capabilities to mimic tactile sensing and processing. Our system senses pressure by MXene-based sensors, converts pressure information to light pulses by coupling light-emitting diodes to analog-to-digital circuits, then integrates light pulses using a synaptic photomemristor. With neural coding, our spiking nerve is capable of not only detecting simultaneous pressure inputs, but also recognizing Morse code, braille, and object movement. Furthermore, with dimensionality-reduced feature extraction and learning, our system can recognize and memorize handwritten alphabets and words, providing a promising approach towards e-skin, neurorobotics and human-machine interaction technologies.