Self-Assembled Lanthanum Oxide Nanoflakes by Electrodeposition Technique for Resistive Switching Memory and Artificial Synaptic Devices

Wafer scale WS2based ultrafast photosensing and memory computing devices for neuromorphic computing

Integration of optical sensors with memristors can establish the bridge between photosensing and memory devices for Internet of Things (IoT) based applications. This paper presents the realization of integrated sensing and computing memory (ISCM) devices using tungsten disulfide (WS2) and their application for neuromorphic computing. The ISCM device fabrication process is scalable as microfabrication steps followed on 2″ wafer, ISCM device testing and image classification for neuromorphic computing. The photosensing/memory tests were conducted using electrical and optical stimulations (broadband spectrum). The fabricated photosensing device offers a higher responsivity (8 A W-1), higher detectivity (2.85 × 1011Jones) and fast response speed (80.2/78.3μs) at 950 nm. The memory device has shown a set/reset time of 51.6/73.5μs respectively. Further, the repeatability, stability and reproducibility tests were conducted by stimulating the device with different modulating frequencies. The frequency modulation tests confirm that the ISCM devices are stable and perfect candidate for real-time IoT applications. Moreover, the device's potentiation and depression results were used for image classification with the accuracy of 98.27%. These demonstrated device's test results provide possibilities to fabricate the smart sensors with integrated functionalities.

Multilevel Conductance States of Vapor-Transport-Deposited Sb2S3 Memristors Achieved via Electrical and Optical Modulation

The pursuit of advanced brain-inspired electronic devices and memory technologies has led to explore novel materials by processing multimodal and multilevel tailored conductive properties as the next generation of semiconductor platforms, due to von Neumann architecture limits. Among such materials, antimony sulfide (Sb2S3) thin films exhibit outstanding optical and electronic properties, and therefore, they are ideal for applications such as thin-film solar cells and nonvolatile memory systems. This study investigates the conduction modulation and memory functionalities of Sb2S3 thin films deposited via the vapor transport deposition technique. Experimental results indicate that the Ag/Sb2S3/Pt device possesses properties suitable for memory applications, including low operational voltages, robust endurance, and reliable switching behavior. Further, the reproducibility and stability of these properties across different device batches validate the reliability of these devices for practical implementation. Moreover, Sb2S3-based memristors exhibit artificial neuroplasticity with prolonged stability, promising considerable advancements in neuromorphic computing. Leveraging the photosensitivity of Sb2S3 enables the Ag/Sb2S3/Pt device to exhibit significant low operating potential and conductivity modulation under optical stimulation for memory applications. This research highlights the potential applications of Sb2S3 in future memory devices and optoelectronics and in shaping electronics with versatility.

CogniFiber: Harnessing Biocompatible and Biodegradable 1D Collagen Nanofibers for Sustainable Nonvolatile Memory and Synaptic Learning Applications

Here, resistive switching (RS) devices are fabricated using naturally abundant, nontoxic, biocompatible, and biodegradable biomaterials. For this purpose, 1D chitosan nanofibers (NFs), collagen NFs, and chitosan-collagen NFs are synthesized by using an electrospinning technique. Among different NFs, the collagen-NFs-based device shows promising RS characteristics. In particular, the optimized Ag/collagen NFs/fluorine-doped tin oxide RS device shows a voltage-tunable analog memory behavior and good nonvolatile memory properties. Moreover, it can also mimic various biological synaptic learning properties and can be used for pattern classification applications with the help of the spiking neural network. The time series analysis technique is employed to model and predict the switching variations of the RS device. Moreover, the collagen NFs have shown good cytotoxicity and anticancer properties, suggesting excellent biocompatibility as a switching layer. The biocompatibility of collagen NFs is explored with the help of NRK-52E (Normal Rat Kidney cell line) and MCF-7 (Michigan Cancer Foundation-7 cancer cell line). Additionally, the biodegradability of the device is evaluated through a physical transient test. This work provides a vital step toward developing a biocompatible and biodegradable switching material for sustainable nonvolatile memory and neuromorphic computing applications.

Piezo-Acoustic Resistive Switching Behaviors in High-Performance Organic-Inorganic Hybrid Perovskite Memristors

Memristors are regarded as promising candidates for breaking the problems including high off-chip memory access delays and the hash rate cost of frequent data moving induced by algorithms for data-intensive applications of existing computational systems. Recently, organic-inorganic halide perovskites (OIHPs) have been recognized as exceptionally favorable materials for memristors due to ease of preparation, excellent electrical conductivity, and structural flexibility. However, research on OIHP-based memristors focuses on modulating resistive switching (RS) performance through electric fields, resulting in difficulties in moving away from complex external circuits and wire connections. Here, a multilayer memristor has been constructed with eutectic gallium and indium (EGaIn)/ MAPbI3 /poly(3,4-ethylenedioxythiophene): poly(4-styrenesulphonate) (PEDOT: PSS)/indium tin oxide (ITO) structure, which exhibits reproducible and reliable bipolar RS with low SET/RESET voltages, stable endurance, ultrahigh average ON/OFF ratio, and excellent retention. Importantly, based on ion migration activated by sound-driven piezoelectric effects, the device exhibits a stable acoustic response with an average ON/OFF ratio greater than 103 , thus realizing non-contact, multi-signal, and far-field control in RS modulation. This study provides a single-structure multifunctional memristor as an integrated architecture for sensing, data storage, and computing.

Stretchable and neuromorphic transistors for pain perception and sensitization emulation

Pain perception nociceptors (PPN), an important type of sensory neuron, are capable of sending out alarm signals when the human body is exposed to destructive stimuli. Simulating the human ability to perceive the external environment and spontaneously avoid injury is a critical function of neural sensing of artificial intelligence devices. The demand for developing artificial PPN has subsequently increased. However, due to the application scenarios of bionic electronic devices such as human skin, electronic prostheses, and robot bodies, where a certain degree of surface deformation constantly occurs, the ideal artificial PPN should have the stretchability to adapt to real scenarios. Here, an organic semiconductor nanofiber artificial pain perception nociceptor (NAPPN) based on a pre-stretching strategy is demonstrated to achieve key pain aspects such as threshold, sensitization, and desensitization. Remarkably, while stretching up to 50%, the synaptic behaviors and injury warning ability of NAPPN can be retained. To verify the wearability of the device, NAPPN was attached to a curved human finger joint, on which PPN behaviors were successfully mimicked. This provides a promising strategy for realizing neural sensing function on either deformed or mobile electronic devices.