Boron-doped activated carbon from the stems of Prosopis juliflora as an effective electrode material in symmetric supercapacitors

For a supercapacitor electrode, carbon-based materials have received great attention for their high surface area and stability. In this work, sustainable and cost-effective synthesis of boron-doped activated biomass-derived carbon from the stems of Prosopis juliflora has been reported for supercapacitor applications. The activation by KOH creates pores and boron induces p-type doping in the carbon matrix. The material gave a higher specific capacitance of 307.14 F/g at a current density of 0.5 A/g. The symmetric supercapacitor device delivered 156.29 F/g of specific capacitance with 98.1% of energy efficiency. The observed energy and power densities were 7.81 Wh/Kg and 150 W/Kg, respectively. The device was further studied with stability test for 1000 charge/discharge cycles and showed 98.6% of capacitance retention and 97.9% of coulombic efficiency.

     

A New Route for the Synthesis of Tungsten Carbide–Cobalt Nanocomposites

Synthesis of WC–Co nanocomposites generally involves gas-phase carburization. A novel approach in which a polymer precursor such as polyacrylonitrile serves as an in situ carbon source has been developed. The WC–Co nanocomposites formed are characterized by X-ray powder diffraction and electron microscopy. Nearly phase pure WC–Co nanocomposites with a particle size of 50–80 nm have been obtained. The phase purity of the products is strongly influenced by the synthesis and processing conditions such as the firing temperature, time, and atmosphere.     

Ellipsoidal neighbourhood outlier factor for distributed anomaly detection in resource constrained networks

Anomaly detection in resource constrained wireless networks is an important challenge for tasks such as intrusion detection, quality assurance and event monitoring applications. The challenge is to detect these interesting events or anomalies in a timely manner, while minimising energy consumption in the network. We propose a distributed anomaly detection architecture, which uses multiple hyperellipsoidal clusters to model the data at each sensor node, and identify global and local anomalies in the network. In particular, a novel anomaly scoring method is proposed to provide a score for each hyperellipsoidal model, based on how remote the ellipsoid is relative to their neighbours. We demonstrate using several synthetic and real datasets that our proposed scheme achieves a higher detection performance with a significant reduction in communication overhead in the network compared to centralised and existing schemes.     

Synthesis and characterization of liquid crystalline polymers containing aromatic ester mesogen and a nonmesogenic ferrocene unit in the spacer

A new series of liquid crystalline polymers containing aromatic triad ester mesogen and 1,1′‐disubstituted ferrocene as a nonmesogenic unit along with polymethylene spacer was synthesized. The polymer was synthesized by a room temperature polycondensation reaction between bis(4‐chloroformyl phenyloxy alkyl ferrocene dicarboxylate) and quinol. The alkyl groups have been varied by an even number of methylene groups with a range from two to ten groups. All the polymers were found to possess liquid crystalline properties. The identification of the mesophase is more transparent with an increase in the spacer. The thermal characteristics were studied using thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC). The results reveal that the thermal stability of the polymers was decreased with increasing spacer length. The T_g, T_m, and T_i of the polymers decreased with increasing methylene groups. The incorporation of the ferrocene moiety also has a considerable effect on the glass transition temperature. The char yield of the polymer decreases with an increasing methylene chain length. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 86: 3494–3501, 2002     

Ultra-Thin Single-Particle-Layer Sodium Beta-Alumina-Based Composite Polymer Electrolyte Membrane for Sodium-Metal Batteries

Inorganic/organic composite polymer electrolytes (CPEs) with good flexibility and electrode contact have been pursued for solid−state sodium-metal batteries. However, the application of CPEs for high energy density solid−state sodium-metal batteries is still limited by the low Na⁺ conductivity, large thickness, and low ion transference number. Herein, an ultra-thin single-particle-layer (UTSPL) composite polymer electrolyte membrane with a thickness of ≈20 µm straddled by a sodium beta−alumina ceramic electrolyte (SBACE) is presented. A ceramic Na⁺-ion electrolyte that bridges or percolates across an ultra-thin and flexible polymer membrane provides: 1) the strength and flexibility from the polymer membrane, 2) excellent electrolyte/electrode interfacial contact, and 3) a percolation path for Na⁺-ion transfer. Owing to this novel design, the obtained UTSPL-35SBACE membrane exhibits a high Na⁺-ion conductivity of 0.19 mS cm⁻¹ and a transference number of 0.91 at room temperature, contributing to long−term cycling stability of symmetric sodium cells with a small overpotential. The assembled quasi-solid-state cell with the as−prepared UTSPL-35SBACE membrane displays superior cycling performance with a discharge capacity of 105 mAh g⁻¹ at 0.5 °C rate after 100 cycles and excellent rate performance (82 mAh g⁻¹ at 5 °C rate) at room temperature with the potassium manganese hexacyanoferrate (KMHCF)@CNTs/CNFs cathode, where KMHCF refers to potassium manganese hexacyanoferrate.     

Inkjet‐Printed Lithium–Sulfur Microcathodes for All‐Printed,Integrated Nanomanufacturing

Improved thin‐film microbatteries are needed to provide appropriate energy‐storage options to power the multitude of devices that will bring the proposed “Internet of Things” network to fruition (e.g., active radio‐frequency identification tags and microcontrollers for wearable and implantable devices). Although impressive efforts have been made to improve the energy density of 3D microbatteries, they have all used low energy‐density lithium‐ion chemistries, which present a fundamental barrier to miniaturization. In addition, they require complicated microfabrication processes that hinder cost‐competitiveness. Here, inkjet‐printed lithium–sulfur (Li–S) cathodes for integrated nanomanufacturing are reported. Single‐wall carbon nanotubes infused with electronically conductive straight‐chain sulfur (S@SWNT) are adopted as an integrated current‐collector/active‐material composite, and inkjet printing as a top‐down approach to achieve thin‐film shape control over printed electrode dimensions is used. The novel Li–S cathodes may be directly printed on traditional microelectronic semicoductor substrates (e.g., SiO₂) or on flexible aluminum foil. Profilometry indicates that these microelectrodes are less than 10 µm thick, while cyclic voltammetry analyses show that the S@SWNT possesses pseudocapacitive characteristics and corroborates a previous study suggesting the S@SWNT discharge via a purely solid‐state mechanism. The printed electrodes produce ≈800 mAh g^?1 S initially and ≈700 mAh g^?1 after 100 charge/discharge cycles at C/2 rate.     

Rechargeable Aluminum‐Ion Batteries Based on an Open‐Tunnel Framework

Rechargeable batteries based on an abundant metal such as aluminum with a three‐electron transfer per atom are promising for large‐scale electrochemical energy storage. Aluminum can be handled in air, thus offering superior safety, easy fabrication, and low cost. However, the development of Al‐ion batteries has been challenging due to the difficulties in identifying suitable cathode materials. This study presents the use of a highly open framework Mo_{2.5 + y} VO_{9 + z} as a cathode for Al‐ion batteries. The open‐tunnel oxide allows a facile diffusion of the guest species and provides sufficient redox centers to help redistribute the charge within the local host lattice during the multivalent‐ion insertion, thus leading to good rate capability with a specific capacity among the highest reported in the literature for Al‐based batteries. This study also presents the use of Mo_{2.5 + y} VO_{9 + z} as a model host to develop a novel ultrafast technique for chemical insertion of Al ions into host structures. The microwave‐assisted method employing diethylene glycol and aluminum diacetate (Al(OH)(C₂H₃O₂)₂) can be performed in air in as little as 30 min, which is far superior to the traditional chemical insertion techniques involving moisture‐sensitive organometallic reagents. The Al‐inserted Al _x Mo_{2.5 + y} VO_{9 + z} obtained by the microwave‐assisted chemical insertion can be used in Al‐based rechargeable batteries.     

Implementation of VLSI on Signal Processing-Based Digital Architecture Using AES Algorithm

Continuous improvements in very-large-scale integration (VLSI) technology and design software have significantly broadened the scope of digital signal processing (DSP) applications. The use of application-specific integrated circuits (ASICs) and programmable digital signal processors for many DSP applications have changed, even though new system implementations based on reconfigurable computing are becoming more complex. Adaptable platforms that combine hardware and software programmability efficiency are rapidly maturing with discrete wavelet transformation (DWT) and sophisticated computerized design techniques, which are much needed in today’s modern world. New research and commercial efforts to sustain power optimization, cost savings, and improved runtime effectiveness have been initiated as initial reconfigurable technologies have emerged. Hence, in this paper, it is proposed that the DWT method can be implemented on a field-programmable gate array in a digital architecture (FPGA-DA). We examined the effects of quantization on DWT performance in classification problems to demonstrate its reliability concerning fixed-point math implementations. The Advanced Encryption Standard (AES) algorithm for DWT learning used in this architecture is less responsive to resampling errors than the previously proposed solution in the literature using the artificial neural networks (ANN) method. By reducing hardware area by 57%, the proposed system has a higher throughput rate of 88.72%, reliability analysis of 95.5% compared to the other standard methods.