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In the era of big data, the necessity for in-memory computing has become increasingly pressing, rendering memristors a crucial component in next-generation computing architectures. The self-rectifying memristor (SRM), in particular, has emerged as a promising solution to mitigate the sneak path current issue in crossbar architectures. In this work, a Pt/HfO2/WO3−x/TiN SRM structure is reported with an impressive rectification ratio above 106. To elucidate the underlying mechanisms, we systematically investigate the impact of the WO3−x resistive layer thickness modulation on the device's conductive behavior. Our findings reveal that the abundant traps in the WO3−x resistive layer and the excellent insulating property of HfO2 synergistically suppress negative current while promoting positive current. According to the simulation, the crossbar array based on the proposed SRMs can realize an array scale of over 21 Gbit. Furthermore, artificial synapses fabricated using these SRMs demonstrate a remarkable linearity of 0.9973. In conclusion, our results underscore the great potential of these SRMs for the ultra-large-scale integration of neuromorphic hardware, providing a guide for future ultra-high-energy efficiency hardware with minimal circuit overhead. [ABSTRACT FROM AUTHOR]

In this Letter, we present a dual-layer oxide volatile memristor characterized by an Ag/TaOx/ZnO/Pt structure. This innovative design deviates from traditional Ag/ZnO/Pt devices, chiefly through the introduction of a thin TaOx layer between the electrolyte and the active electrode. Our devices exhibit remarkable features, including an unprecedentedly low switching voltage slope, measuring a mere 0.221 mV/dec, and a threshold voltage that can be reduced to as low as 0.177 V. To further elucidate the performance enhancement of the device, we utilize first-principles calculations. The results reveal that the relatively high formation energy of oxygen vacancies in the supplementary TaOx layer facilitates meticulous control over the rupture and formation of silver conductive nanofilaments. [ABSTRACT FROM AUTHOR]

The neuromorphic system simulates the storage, computing, and information expression architecture of the biological brain, which processes massive amounts of data with extremely low power consumption and high speed. Therefore, it is urgent to innovate a computing paradigm to solve the power-consumption and computing-power problems induced by the rapid development of data-centric applications. With the advent of the Internet of Things and the era of big data, the ability of machine data processing to reach the level of human brain cognition and learning is an important goal in the field of Internet information technology, including cloud computing, data mining, machine learning, and artificial intelligence (AI). [Extracted from the article]

Shape-stable solid–solid phase-change material (PCM) has attracted much attention due to its excellent thermal properties and shape stability. In this study, cellulose nanocrystal (CNC) was introduced as a high thermal-conductivity nanoskeleton material, and polyethylene glycol (PEG) was used as a solid–liquid phase-change functional material. A green, simple aqueous phase radical polymerization method was used to synthesize shape-stable CNC-based solid–solid phase-change material. The effect of different reaction times on the chemical structure, crystallization ability, thermal stability, and phase transformation properties of the PCM was investigated. All PCM samples showed excellent thermal stability when the temperature was lower than 300 °C. In particular, the synthesized PCM at 12 h had a melt phase transition temperature of 47.1 °C and a phase transition enthalpy up to 82.3 J/g. In addition, the phase-change enthalpy and temperature of PCM-12h did not change significantly after 120 heating and cooling scans. The PCM-12h showed thermal reliability, shape stability, controlled phase-change behaviors, and good heat storage/release properties after thermal treatment. The PCM has potential applications in smart heat storage and temperature control textiles/clothes, building insulation materials, and other energy storage fields. [ABSTRACT FROM AUTHOR]

The increasing sophistication of cybersecurity threats, driven by the proliferation of big data and the Internet of Things (IoT), necessitates the development of advanced real-time intrusion detection systems (IDSs). In this study, we present a novel approach that integrates NiO-doped WO 3- x /ZnO bilayer self-rectifying memristors (SRMs) within a reservoir computing (RC) framework for IDS applications. The proposed crossbar array architecture exploits the exceptional dynamic properties of SRMs, achieving a classification accuracy of 93.07% on the CSE-CIC-IDS2018 data set, while demonstrating ultrahigh information-processing efficiency. Our approach not only leverages the tunable characteristics of memristors but also addresses the challenge of sneak path currents in large-scale integration, offering a robust and scalable solution for next-generation IDS. This work exemplifies the power of emerging electronics in enhancing cybersecurity through innovative hardware implementations.

The previous studies have demonstrated the excellent neuroprotective effects of xenon. In this study, we verified the anti-seizure and neuroprotective roles of xenon in epileptogenesis and evaluated the involvement of oxidative stress and iron accumulation in the protective roles of xenon. Epileptogenesis was induced by pentylenetetrazole (PTZ) treatment in Sprague-Dawley rats. During epileptogenesis, we found increased levels of iron and oxidative stress accompanied by elevated levels of divalent metal transporter protein 1 and iron regulatory protein 1, which are closely associated with iron accumulation. Meanwhile, the levels of autophagy and mitophagy increased, alongside significant neuronal damage and cognitive deficits. Xenon treatment reversed these effects: oxidative stress and iron stress were reduced, neuronal injury and seizure severity were attenuated, and learning and memory deficits were improved. Thus, our results confirmed the neuroprotective and anti-seizure effects of xenon treatment in PTZ-induced epileptogenesis. The reduction in oxidative and iron stress may be the main mechanisms underlying xenon treatment. Thus, this study provides a potential intervention strategy for epileptogenesis., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Zhang, Cheng, Zhai, Yuan, Hu, Meng, Fan, Sun and Li.)

As pointed out by many researchers in the last few decades, differential equations with fractional (non-integer) order differential operators, in comparison with classical integer order ones, have apparent advantages in modeling. A Caputo fractional order system of ordinary differential equations is introduced to model the virus infection at the population level in this chapter. As well known, there are two main methods to study the dynamics of a model: qualitative analysis and numerical modeling. Here the qualitative analysis, including uniqueness, invariant set, and stability, is first presented with intuitive derivation. Then the famous genetic algorithm is introduced to numerically model the dynamics of virus infection, i.e. to adjust the parameters of the Caputo fractional model such that its solution can properly fit real data and predict future., (© 2022. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.)

Charged nanocellulose (NC) with a high aspect ratio (larger than 100) extracted from animal or bacterial cellulose and chemical cross-linked NC aerogels have great promising applicability in material science, but facile fabrication of such NC aerogels from plant cellulose by physical cross-linking still remains a major challenge. In this work, carboxylated cellulose nanofiber (CNF) with the highest aspect ratio of 144 was extracted from wasted ginger fibers by a simple one-step acid hydrolysis. Our approach could easily make the carboxylated CNF assemble into robust bulk aerogels with tunable densities and desirable shapes on a large scale (3D macropores to mesopores) by hydrogen bonds. Excitingly, these CNF aerogels had better compression mechanical properties (99.5 kPa at 80% strain) and high shape recovery. Moreover, the CNF aerogels had strong coagulation-flocculation ability (87.1%), removal efficiency of MB dye uptake (127.73 mg/g), and moderate Cu 2+ absorption capacity (45.053 mg/g), which were due to assistance mechanisms of charge neutralization, network capture effect, and chain bridging of high aspect ratio carboxylated CNF. This provided a novel physical cross-linking method to design robust aerogels with modulated networked structures to be a general substrate material for industrial applications such as superabsorbent, flocculation, oil-water separation, and potential electrical energy storage materials.