Synaptic plasticity, metaplasticity and memory effects in hybrid organic-inorganic bismuth-based materials

Flexible and Energy-Efficient Synaptic Transistor with Quasi-Linear Weight Update Protocol by Inkjet Printing of Orientated Polar-Electret/High-k Oxide Composite Dielectric

Inkjet printing artificial synapse is cost-effective but challenging in emulating synaptic dynamics with a sufficient number of effective weight states under ultralow voltage spiking operation. A synaptic transistor gated by inkjet-printed composite dielectric of polar-electret polyvinylpyrrolidone (PVP) and high-k zirconia oxide (ZrOx) is proposed and thus synthesized to solve this issue. Quasi-linear weight update with a large variation margin is obtained through the coupling effect and the facilitation of dipole orientation, which can be attributed to the orderly arranged molecule chains induced by the carefully designed microfluidic flows. Crucial features of biological synapses including long-term plasticity, spike-timing-dependence-plasticity (STDP), "Learning-Experience" behavior, and ultralow energy consumption (<10 fJ/pulse) are successfully implemented on the device. Simulation results exhibit an excellent image recognition accuracy (97.1%) after 15 training epochs, which is the highest for printed synaptic transistors. Moreover, the device sustained excellent endurance against bending tests with radius down to 8 mm. This work presents a very viable solution for constructing the futuristic flexible and low-cost neural systems.

Recent advancements in implantable neural links based on organic synaptic transistors

The progress of brain synaptic devices has witnessed an era of rapid and explosive growth. Because of their integrated storage, excellent plasticity and parallel computing, and system information processing abilities, various field effect transistors have been used to replicate the synapses of a human brain. Organic semiconductors are characterized by simplicity of processing, mechanical flexibility, low cost, biocompatibility, and flexibility, making them the most promising materials for implanted brain synaptic bioelectronics. Despite being used in numerous intelligent integrated circuits and implantable neural linkages with multiple terminals, organic synaptic transistors still face many obstacles that must be overcome to advance their development. A comprehensive review would be an excellent tool in this respect. Therefore, the latest advancements in implantable neural links based on organic synaptic transistors are outlined. First, the distinction between conventional and synaptic transistors are highlighted. Next, the existing implanted organic synaptic transistors and their applicability to the brain as a neural link are summarized. Finally, the potential research directions are discussed.

Preliminary investigation on the implementation of an artificial synapse using TaOx-based memristor with thermally oxidized active layer

This study presents a preliminary exploration of thermally oxidized TaOx-based memristors and their potential as artificial synapses. Unlike the 10-min annealed devices, which display instability due to current overshoots, the 5-min annealed device exhibits stable resistive switching, retention, and endurance characteristics. Moreover, our memristor showcases synaptic behaviors encompassing potentiation, depression, spike-timing-dependent plasticity, and excitatory postsynaptic currents. This synaptic emulation holds tremendous promise for applications in neuromorphic computing, offering the opportunity to replicate the adaptive learning principles observed in biological synapses. In addition, we evaluate the device's suitability for pattern recognition within a neural network using the modified National Institute of Standards and Technology dataset. Our assessment reveals that the Pt/TaOx/Ta memristor with an oxidized insulator achieves outstanding potential manifested by an accuracy of 93.25% for the identical pulse scheme and an impressive accuracy of 95.42% for the incremental pulse scheme.

Influence of crystal structure and composition on optical and electronic properties of pyridinium-based bismuth iodide complexes

This study investigates the impacts of structure and composition on the optical and electronic properties of a series of pyridinium-based bismuth iodide complexes. Organic substrates with various functional groups, such as 4-aminopyridine (4-Ampy), 4-methylpyridine (4-Mepy), 4-dimethylaminopyridine (4-Dmapy), and 4-pyridinecarbonitrile (4-CNpy) with different electron-donating and electron-withdrawing groups at the para position of the pyridine ring were employed. Crystallographic analysis reveals various bismuth iodide structures, including 1D chains and discrete 0D motifs. The optical band gap of these materials, identified via diffuse reflectance spectroscopy (DRS) and verified with density functional theory (DFT) calculations, is influenced by the crystal packing and stabilising interactions. Through a comprehensive analysis, including Hirshfeld surface (HS) and void assessment, the study underscores the influence of noncovalent intermolecular interactions on crystal packing. Spectroscopic evaluations provide insights into electronic interactions, elucidating the role of electron donor and acceptor substituents within the lattice. Thermogravimetric differential thermal analysis (TG-DTA) indicates structural stability up to 250 °C. Linear sweep voltammetry (LSV) reveals significant conductivity in the range of 10-20 mS per pixel at 298.15 K. X-ray absorption spectroscopy (XAS) at the Bi L3 edge indicates a similar oxidation state and electronic environment across all samples, underscoring the role of bismuth centres surrounded by iodides.

Natural Organic Materials Based Memristors and Transistors for Artificial Synaptic Devices in Sustainable Neuromorphic Computing Systems

Natural organic materials such as protein and carbohydrates are abundant in nature, renewable, and biodegradable, desirable for the construction of artificial synaptic devices for emerging neuromorphic computing systems with energy efficient operation and environmentally friendly disposal. These artificial synaptic devices are based on memristors or transistors with the memristive layer or gate dielectric formed by natural organic materials. The fundamental requirement for these synaptic devices is the ability to mimic the memory and learning behaviors of biological synapses. This paper reviews the synaptic functions emulated by a variety of artificial synaptic devices based on natural organic materials and provides a useful guidance for testing and investigating more of such devices.

Near-Infrared Artificial Synapses for Artificial Sensory Neuron System

The computing based on artificial neuron network is expected to break through the von Neumann bottleneck of traditional computer, and to greatly improve the computing efficiency, displaying a broad prospect in the application of artificial visual system. In the specific structural layout, it is a common method to connect the discrete photodetector with the artificial neuron in series, which enhances the complexity of signal recognition, conversion and storage. In this work, organic small molecule IR-780 iodide is inserted into the memory device as both the charge trapping layer and near-infrared (NIR) photoresponsive film. Through electrical and optical regulation, artificial synaptic functions including short-term plasticity, long-term plasticity, and spike rate dependence are realized. In the established artificial sensory neuron system, NIR optical pulses can significantly improve the spiking rate. Moreover, the spiking neural networks are further constructed by simulation for handwritten digit classification. This research may contribute to the development of light driven neural robots, optical signal encryption, and neural computing.

Incorporating a redox active entity to attain electrical bistability in a polymer semiconductor

Owing to the advantages of 3-D printable stack, scalability and low cost solution state production, polymer-based resistive memory devices have been identified as the promising alternative for conventional oxide technology. Resistive memory devices based on the redox switch mechanism is particularly found to yield high precision with respect to the operational voltages. Reversible non-volatile resistive state switching was realized with high device yield (>80%), with a redox-active chemical entity conjugated to the polymeric semiconductor, and the control experiments with the model compound confirmed the imperative role of the redox-active anthraquinone center in the polymeric backbone. Highly uniform nanodomains and the trap free layers excluded the possibilities of other known switching mechanisms. Optical studies and the molecular modelling data assert the presence of strong charge transfer characteristics upon optical excitation due to the insertion of the anthraquinone unit, which was detrimental in exhibiting bistable conductive states in electrical bias as well.

Suppressed Stochastic Switching Behavior and Improved Synaptic Functions in an Atomic Switch Embedded with a 2D NbSe2 Material

We investigated chemical vapor-deposited (CVD) two-dimensional (2D) niobium diselenide (NbSe₂) material for the resistive switching and synaptic characteristics. Three different atomic switch devices with Ag/HfO₂/Pt, Ag/Ti/HfO₂/Pt, and Ag/NbSe₂/HfO₂/Pt were studied as both memory and neuromorphic devices. Both the inserted Ti and NbSe₂ buffer layers effectively control the stochastic Ag-ion diffusion, leading to suppressed variation of switching characteristics, which is a critical issue in an atomic switch device. Especially, the device with the 2D NbSe₂ buffer layer strikingly enhanced the device reliability in both endurance and retention. In conjunction with scanning transmission electron microscopy (STEM) and energy-dispersive spectrometry (EDS) analysis of the control of the Ag-ion migration, it was understood that filament connection is interrelated with the SET and RESET processes. Besides resistive behaviors in the memory device, various synapse functions such as spike-rate-dependent plasticity (SRDP), forgetting curve, potentiation, and depression were demonstrated with an atomic switch with the 2D NbSe₂ buffer layer. Furthermore, the emulated long-term synaptic property was simulated using the MNIST 28 × 28 pixel database. Using adopting a CVD 2D NbSe₂ blocking layer, the stochastic Ag-ion diffusion behavior is well-controlled and therefore stable switching and synapse functions are attained.

Anisotropic Photoconductivity and Long-Lived Charge Carriers in Bismuth-Based One-Dimensional Perovskite with Type-IIa Band Alignment

Bismuth-based perovskites are attracting intense scientific interest due to low toxicity and excellent moisture stability compared to lead-based analogues. However, high exciton binding energy, poor charge carrier separation, and transport efficiencies lower their optoelectronic performances. To address these issues, we have integrated an electronically active organic cation, naphthalimide ethylammonium, between the [BiI₅^2-]_n chains via crystal engineering to form a novel perovskite-like material (naphthalimide ethylammonium)₂BiI₅ (NBI). Single crystal analysis revealed a one-dimensional quantum-well structure for NBI in which inter-inorganic well electronic coupling is screened by organic layers. It exhibited anisotropic photoconductivity and long-lived charge carriers with milliseconds lifetime, which is higher than that of CH₃NH₃PbI₃. Density functional theory calculations confirmed type-IIa band alignment between organic cations and inorganic chains, allowing the former to electronically contribute to the overall charge transport properties of the material.