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A one-selector one resistor (1S1R) array formed of a selector and resistive random access memory (RRAM) is an important way to achieve high-density storage and neuromorphic computing. However, the low durability and poor consistency of the selector limit its practical application. The fabrication of a selector based on egg albumen (EA) is reported in this paper. The device exhibits excellent bidirectional threshold switching characteristics, including a low leakage current (10 -7  A), a high ON/OFF current ratio (10 6 ), and good endurance (>700 days). It is used as a selector to form a 1S1R unit in combination with an EA-based RRAM to effectively solve the leakage current in a crossbar array. A feasible solution is provided for the realization of a protein-based 1S1R array to achieve high-density storage. The 1S1R unit shows characteristics similar to those of synapses in the human brain under impulse excitation and has great potential in simulating the human brain for neuromorphic calculations.)., (© 2023 Wiley-VCH GmbH.)

Gold nanoparticles (Au NPs) have good biocompatibility and special quantum effects. In this Letter, we embedded Au NPs into silkworm hemolymph (SH) to improve the performance of the device and fabricated Al/SH:Au NPs/indium tin oxide (ITO)/glass resistive random access memory. The device exhibits a bipolar switching behavior with a retention time of 10 4 s. Compared with the Al/SH/ITO device without Au NPs, the device has a higher ON/OFF current ratio (>10 5 ) and a smaller V reset . The improvement in device performance is attributed to the fact that Au NPs act as the electron-trapping center in the device; a Coulomb blockade occurs after electrons are trapped, thereby increasing the resistance of the device in the high-resistance state. Using optimized devices can realize multilevel data storage and can also simulate synaptic characteristics such as potentiation and depression. The device is expected to be applied to high-density, low-cost, degradable, and biocompatible storage devices and neuromorphic computing in the future.

The realization of artificial synapses based on biomaterials is of great significance for the development of environmentally friendly neuromorphic hardware systems and artificial intelligence. In this sense, a bioartificial synapse composited with egg albumen (EA) and multiwalled carbon nanotubes (MWCNTs) is fabricated. Based on the adjustable weight of the artificial synapse, the plasticity of electrical synapses is explored. Due to the photogenerated carriers and thermoelectric effects of carbon nanotubes, the device has optoelectronic properties, so the optoelectronic synaptic plasticity of the device is explored under light pulses. The device is well suited for biological synapses and shows great potential for applications in future high‐density storage and neuromorphic computing systems. In addition, to further study the physical mechanism of the conductive process of the device, the electrical characteristics of the contact interface between carbon nanotubes doped with Fe substitution and the upper electrode Al are mainly analyzed by first principles, and the adsorption, charge distribution, and band structure between them are theoretically studied. [ABSTRACT FROM AUTHOR]

As artificial synapse devices, memristors have attracted widespread attention in the field of neuromorphic computing. In this paper, Al/polymethyl methacrylate (PMMA)/egg albumen (EA)–graphene quantum dots (GQDs)/PMMA/indium tin oxide (ITO) electrically/optically tunable biomemristors were fabricated using the egg protein as a dielectric layer. The electrons in the GQDs were injected from the quantum dots into the dielectric layer or into the adjacent quantum dots under the excitation of light, and the EA–GQDs dielectric layer formed a pathway composed of GQDs for electronic transmission. The device successfully performed nine brain synaptic functions: excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF), short-term potentiation (STP), short-term depression (STD), the transition from short-term plasticity to long-term plasticity, spike-timing-dependent plasticity (STDP), spike-rate-dependent plasticity (SRDP), the process of learning, forgetting, and relearning, and Pavlov associative memory under UV light stimulation. The successful simulation of the synaptic behavior of this device provides the possibility for biomaterials to realize neuromorphic computing. [ABSTRACT FROM AUTHOR]

The synaptic behavior of the Ni–Co layered double hydroxide-based memristor was demonstrated. The modulation effect of pulse amplitude, duration, and excitation interval on the conductance of memristor is analyzed. On account of analog resistive switching features, and the nonlinear transmission characteristics of synapses, pulse-time-dependent plasticity, long-term/short-term memory, and "learning" and "forgetting" behaviors of synapses are simulated and carried out. The analog bipolar resistance switch was ascribed to the formation and breakdown of oxygen filaments formed in Ni–Co layered double hydroxides films. This kind of memristor with an analog resistance switch is very promising to provide an implementation method for the development of electronic synapse function. [ABSTRACT FROM AUTHOR]

Multilevel data memory and artificial synaptic plasticity in poly(vinylidene fluoride-co-trifluoroethylene) [P(VDF-TrFE)] ferroelectric field effect transistors were demonstrated. The dynamics of ferroelectric polarization transformation modulate potential of transistor channel, and adjust the electric field of the P(VDF-TrFE) ferroelectric film by potential along channel direction, thus realizing the multilevel nonvolatile memory state. The artificial synaptic plasticity of transistor is simulated, and the long-term plasticity of excited/inhibited postsynaptic current, paired impulse facilitation/inhibition, and spike-rate-dependent plasticity is realized. In long-term potentiation/depression simulation of devices, the conductivity symmetry and linearity are improved by setting the amplitude of the pulse increments. In addition, the vector-matrix multiplication operation was performed in a crossbar array. This work demonstrates the scheme to develop the P(VDF-TrFE) transistors-based multilevel memory and neural morphological computing. [Display omitted] • A programming scheme is proposed to modulate channel electric field. • The application of 3-bit/cell operation multilevel memory is illustrated. • The potential is modulated from polarization transformation dynamics. • Artificial synaptic plasticity of P(VDF-TrFE) FeFETs is simulated. • The conductivity symmetry and linearity are improved. [ABSTRACT FROM AUTHOR]

Resistive memory is one of the important components for building neuromorphic systems, which can be used as artificial synapses to transmit information. Natural biomaterials are naturally degradable materials, and artificial synaptic devices fabricated from them are particularly important for sustainable green electronics development. Here, on the basis of soybean material as a dielectric layer, we embed gold nanoparticles into it to obtain better memory properties. The switching current ratio of the resistive memory after embedding gold nanoparticles is increased, up to 105, which avoids the possibility of misreading errors during data storage and provides a powerful condition for realizing multilevel behavior. In addition, the device was also demonstrated to simulate the synaptic potentiation/depression function, and the results indicated that the high-performance soybean resistive memory has high-density data storage and exhibits great potential in applications as artificial synapses. • Au nanoparticles are doped in the soybean dielectric layer, which increases the switching current ratio of the device. • By changing the method of limiting the current, 4-bit storage can be achieved to improve the storage density of the device. • Applying excitations to the device can successfully simulate synapses. [ABSTRACT FROM AUTHOR]

[Display omitted] • Memristor based on Co-Ni LDHs hybrid nanosheets is reported. • Devices exhibit nonvolatile resistance switching behavior. • Multiple progressive resistance switches could be achieved. • Memristors were used to simulate synaptic function in biology. • O vacancy is the physical mechanism of the resistance switch behavior. Because of its excellent electrical properties and promising application prospects, two-dimensional materials have attracted extensive research interests of researchers. Among them, Co-Ni layered double hydroxide (LDH) has semiconductor properties and has been widely studied in super capacitor. However, there are few reports about 2D Co-Ni LDHs materials as memristors. In this work, a memristor based on Co-Ni LDHs hybrid nanosheets is reported. After electroforming, Al/Co-Ni LDHs/Al devices exhibit nonvolatile resistance switching behavior. More importantly, multiple progressive resistance switches could be achieved by adjusting the duration or amplitude of the applied pulse (less than the set threshold voltage to prevent a sudden setting process). Given its gradual resistive switching, Co-Ni LDHs-based memristors were used to simulate synaptic function in biology, including: "learning" and "forgetting" process, STP and LTP, PPF characteristics, and STDP. By studying the microstructure, it is proposed that the O vacancy is the physical mechanism of the resistance switch behavior. This work reveals that Co-Ni LDH nanosheets have excellent application potential in memristors, which may open the door to more functions and applications. [ABSTRACT FROM AUTHOR]