Room-Temperature-Processable Highly Reliable Resistive Switching Memory with Reconfigurability for Neuromorphic Computing and Ultrasonic Tissue Classification

Reversible metal-filamentary mechanism has been widely investigated to design an analog resistive switching memory (RSM) for neuromorphic hardware-implementation. However, uncontrollable filament-formation, inducing its reliability issues, has been a fundamental challenge. Here, an analog RSM with 3D ion transport channels that can provide unprecedentedly high reliability and robustness is demonstrated. This architecture is realized by a laser-assisted photo-thermochemical process, compatible with the back-end-of-line process and even applicable to a flexible format. These superior characteristics also lead to the proposal of a practical adaptive learning rule for hardware neural networks that can significantly simplify the voltage pulse application methodology even with high computing accuracy. A neural network, which can perform the biological tissue classification task using the ultrasound signals, is designed, and the simulation results confirm that this practical adaptive learning rule is efficient enough to classify these weak and complicated signals with high accuracy (97%). Furthermore, the proposed RSM can work as a diffusive-memristor at the opposite voltage polarity, exhibiting extremely stable threshold switching characteristics. In this mode, several crucial operations in biological nervous systems, such as Ca²⁺ dynamics and nonlinear integrate-and-fire functions of neurons, are successfully emulated. This reconfigurability is also exceedingly beneficial for decreasing the complexity of systems—requiring both drift- and diffusive-memristors.     

Metal Single-Site Molecular Complex–MXene Heteroelectrocatalysts Interspersed Graphene Nanonetwork for Efficient Dual-Task of Water Splitting and Metal–Air Batteries

Development of multifunctional electrocatalysts with high efficiency and stability is of great interest in recent energy conversion technologies. Herein, a novel heteroelectrocatalyst of molecular iron complex (Fe_MC)-carbide MXene (Mo₂TiC₂T_x) uniformly embedded in a 3D graphene-based hierarchical network (GrH) is rationally designed. The coexistence of Fe_MC and MXene with their unique interactions triggers optimum electronic properties, rich multiple active sites, and favorite free adsorption energy for excellent trifunctional catalytic activities. Meanwhile, the highly porous GrH effectively promotes a multichannel architecture for charge transfer and gas/ion diffusion to improve stability. Therefore, the Fe_MC–MXene/GrH results in superb performances towards oxygen reduction reaction (ORR), oxygen evolution reaction (OER), and hydrogen evolution reaction (HER) in alkaline medium. The practical tests indicate that Zn/Al–air batteries derived from Fe_MC–MXene/GrH cathodic electrodes produce high power densities of 165.6 and 172.7 mW cm⁻², respectively. Impressively, the liquid-state Zn–air battery delivers excellent cycling stability of over 1100 h. In addition, the alkaline water electrolyzer induces a low cell voltage of 1.55 V at 10 mA cm⁻² and 1.86 V at 0.4 A cm⁻² in 30 wt.% KOH at 80 °C, surpassing recent reports. The achievements suggest an exciting multifunctional electrocatalyst for electrochemical energy applications.     

Discrete GWO Optimized Data Aggregation for Reducing Transmission Rate in IoT

The conventional hospital environment is transformed into digital transformation that focuses on patient centric remote approach through advanced technologies. Early diagnosis of many diseases will improve the patient life. The cost of health care systems is reduced due to the use of advanced technologies such as Internet of Things (IoT), Wireless Sensor Networks (WSN), Embedded systems, Deep learning approaches and Optimization and aggregation methods. The data generated through these technologies will demand the bandwidth, data rate, latency of the network. In this proposed work, efficient discrete grey wolf optimization (DGWO) based data aggregation scheme using Elliptic curve Elgamal with Message Authentication code (ECEMAC) has been used to aggregate the parameters generated from the wearable sensor devices of the patient. The nodes that are far away from edge node will forward the data to its neighbor cluster head using DGWO. Aggregation scheme will reduce the number of transmissions over the network. The aggregated data are preprocessed at edge node to remove the noise for better diagnosis. Edge node will reduce the overhead of cloud server. The aggregated data are forward to cloud server for central storage and diagnosis. This proposed smart diagnosis will reduce the transmission cost through aggregation scheme which will reduce the energy of the system. Energy cost for proposed system for 300 nodes is 0.34μJ. Various energy cost of existing approaches such as secure privacy preserving data aggregation scheme (SPPDA), concealed data aggregation scheme for multiple application (CDAMA) and secure aggregation scheme (ASAS) are 1.3 μJ, 0.81 μJ and 0.51 μJ respectively. The optimization approaches and encryption method will ensure the data privacy.     

Chain Vacancies in 2D Crystals

Defects in bulk crystals can be classified into vacancies, interstitials, grain boundaries, stacking faults, dislocations, and so forth. In particular, the vacancy in semiconductors is a primary defect that governs electrical transport. Concentration of vacancies depends mainly on the growth conditions. Individual vacancies instead of aggregated vacancies are usually energetically more favorable at room temperature because of the entropy contribution. This phenomenon is not guaranteed in van der Waals 2D materials due to the reduced dimensionality (reduced entropy). Here, it is reported that the 1D connected/aggregated vacancies are energetically stable at room temperature. Transmission electron microscopy observations demonstrate the preferential alignment direction of the vacancy chains varies in different 2D crystals: MoS₂ and WS₂ prefer direction, while MoTe₂ prefers direction. This difference is mainly caused by the different strain effect near the chalcogen vacancies. Black phosphorous also exhibits directional double‐chain vacancies along 〈01〉 direction. Density functional theory calculations predict that the chain vacancies act as extended gap (conductive) states. The observation of the chain vacancies in 2D crystals directly explains the origin of n‐type behavior in MoTe₂ devices in recent experiments and offers new opportunities for electronic structure engineering with various 2D materials.     

Mesoporous Germanium Anode Materials for Lithium‐Ion Battery with Exceptional Cycling Stability in Wide Temperature Range

Porous structured materials have unique architectures and are promising for lithium‐ion batteries to enhance performances. In particular, mesoporous materials have many advantages including a high surface area and large void spaces which can increase reactivity and accessibility of lithium ions. This study reports a synthesis of newly developed mesoporous germanium (Ge) particles prepared by a zincothermic reduction at a mild temperature for high performance lithium‐ion batteries which can operate in a wide temperature range. The optimized Ge battery anodes with the mesoporous structure exhibit outstanding electrochemical properties in a wide temperature ranging from ?20 to 60 °C. Ge anodes exhibit a stable cycling retention at various temperatures (capacity retention of 99% after 100 cycles at 25 °C, 84% after 300 cycles at 60 °C, and 50% after 50 cycles at ?20 °C). Furthermore, full cells consisting of the mesoporous Ge anode and an LiFePO₄ cathode show an excellent cyclability at ?20 and 25 °C. Mesoporous Ge materials synthesized by the zincothermic reduction can be potentially applied as high performance anode materials for practical lithium‐ion batteries.     

Mechanical property enhancement of aligned multi-walled carbon nanotube sheets and composites through press-drawing process

A solid-state drawing and winding process was done to create thin aligned carbon nanotube (CNT) sheets from CNT arrays. However, waviness and poor packing of CNTs in the sheets are two main weaknesses restricting their reinforcing efficiency in composites. This report proposes a simple press-drawing technique to reduce wavy CNTs and to enhance dense packing of CNTs in the sheets. Non-pressed and pressed CNT/epoxy composites were developed using prepreg processing with a vacuum-assisted system. Effects of pressing on the mechanical properties of the aligned CNT sheets and CNT/epoxy composites were examined. Pressing with distributed loads of 147, 221, and 294 N/m showed a substantial increase in the tensile strength and the elastic modulus of the aligned CNT sheets and their composites. The CNT sheets under a press load of 221 N/m exhibited the best mechanical properties found in this study. With a press load of 221 N/m, the pressed CNT sheet and its composite, respectively, enhanced the tensile strength by 139.1 and 141.9%, and the elastic modulus by 489 and 77.6% when compared with non-pressed ones. The pressed CNT/epoxy composites achieved high tensile strength (526.2 MPa) and elastic modulus (100.2 GPa). Results show that press-drawing is an important step to produce superior CNT sheets for development of high-performance CNT composites.     

Recent Advances on 3D Printing Technique for Thermal‐Related Applications

Advances in ink formulation and printing techniques make producing material systems with new and versatile characteristics and functionalities possible. Additive manufacturing or 3D printing enables fabricating complex structures at a faster production rate using different types of materials for various applications. Recently, 3D printing methods are being studied for thermal‐related applications. In this paper, the authors review recent progress of materials and printing techniques for thermal application devices using composite materials.

     

Facile synthesis of CsPbBr3/PbSe composite clusters

In this work, CsPbBr₃ and PbSe nanocomposites were synthesized to protect perovskite material from self-enlargement during reaction. UV absorption and photoluminescence (PL) spectra indicate that the addition of Se into CsPbBr₃ quantum dots modified the electronic structure of CsPbBr₃, increasing the band gap from 2.38 to 2.48 eV as the Cs:Se ratio increased to 1:3. Thus, the emission color of CsPbBr₃ perovskite quantum dots was modified from green to blue by increasing the Se ratio in composites. According to X-ray diffraction patterns, the structure of CsPbBr₃ quantum dots changed from cubic to orthorhombic due to the introduction of PbSe at the surface. Transmission electron microscopy and X-ray photoemission spectroscopy confirmed that the atomic distribution in CsPbBr₃/PbSe composite clusters is uniform and the composite materials were well formed. The PL intensity of a CsPbBr₃/PbSe sample with a 1:1 Cs:Se ratio maintained 50% of its initial intensity after keeping the sample for 81 h in air, while the PL intensity of CsPbBr₃ reduced to 20% of its initial intensity. Therefore, it is considered that low amounts of Se could improve the stability of CsPbBr₃ quantum dots.     

Study on the solidification cracking behaviour of high strength aluminum alloy welds: Effects of alloying elements and solidification behaviours

The solidification cracking susceptibility of the 7000 series Al-Zn-Mg high strength aluminum alloy has been studied. The cracking behaviour of the specimens were evaluated by a Tig-a-Ma-Jig Varestraint test process under various augmented strain conditions. It has been experimentally observed that the addition of copper decreased the solidification cracking resistivity of the high strength aluminum alloy weld metal by increasing the total crack length (TCL). The effect of the addition of manganese on the solidification cracking behaviour is found to be beneficial by markedly decreasing the solidification cracking susceptibility as the manganese content increases from 0.3 to 0.7%. This enhancement by manganese is understood to be attributed to the reduction of the mushy zone size during the solidification process. The effects of chromium and zirconium additions are also investigated. The weld metal containing zirconium is less sensitive to the solidification cracking than the weld metal containing chromium. In addition, the solidification behaviours of the tested alloys are also investigated and it is found that as the solidification temperature range (T) becomes narrow, the solidified structure becomes more dendritic in its features which is believed to create higher solidification cracking resistance.