Prospects of Supercritical Fluids in Realizing Graphene‐Based Functional Materials

Supercritical‐fluids science and technology predate all the approaches that are currently established for graphene production by several decades in advanced materials design. However, it has only recently been proposed as a plausible approach for graphene processing. Since then, supercritical fluids have emerged into contention as an alternative to existing technologies because of their scalability and versatility in processing graphene materials, which include composites, aerogels, and foams. Here, an overview is presented of such materials prepared through supercritical fluids from an advanced materials science standpoint, with a discussion on their fundamental properties and technological applications. The benefits of supercritical‐fluid processing over conventional liquid‐phase processing are presented. The benefits include not only better performances for advanced applications but also environmental issues associated with the synthesis process. Nevertheless, the limitations of supercritical‐fluid processing are also stressed, along with challenges that are still faced toward the achievement of the great expectations from graphene materials.     

Adaptive RTRL based neurocontroller for damping subsynchronous oscillations using TCSC

Modern interconnected electrical power systems are complex and require perfect planning, design and operation. Hence the recent trends towards restructuring and deregulation of electric power supply has put great emphasis on the system operation and control. Flexible AC transmission system (FACTS) devices such as thyristor controlled series capacitor (TCSC) are capable of controlling power flow, improving transient stability and mitigating subsynchronous resonance (SSR). In this paper an adaptive neurocontroller is designed for controlling the firing angle of TCSC to damp subsynchronous oscillations. This control scheme is suitable for non-linear system control, where the exact linearised mathematical model of the system is not required. The proposed controller design is based on real time recurrent learning (RTRL) algorithm in which the neural network (NN) is trained in real time. This control scheme requires two sets of neural networks. The first set is a recurrent neural network (RNN) which is a fully connected dynamic neural network with all the system outputs fed back to the input through a delay. This neural network acts as a neuroidentifier to provide a dynamic model of the system to evaluate and update the weights connected to the neurons. The second set of neural network is the neurocontroller which is used to generate the required control signals to the thyristors in TCSC. This is a single layer neural network. Performance of the system with proposed neurocontroller is compared with two linearised controllers, a conventional controller and with a discrete linear quadratic Gaussian (DLQG) compensator which is an optimal controller. The linear controllers are designed based on a linearised model of the IEEE first benchmark system for SSR studies in which a modular high bandwidth (six-samples per cycle) linear time-invariant discrete model of TCSC is interfaced with the rest of the system. In the proposed controller, since the response time is highly dependent on the number of states of the system, it is often desirable to approximate the system by its reduced model. By using standard Hankels norm approximation technique, the system order is reduced from 27 to 11th order by retaining the dominant dynamic characteristics of the system. To validate the proposed controller, computer simulation using MATLAB is performed and the simulation studies show that this controller can provide simultaneous damping of swing mode as well as torsional mode oscillations, which is difficult with a conventional controller. Moreover the fast response of the system can be used for real-time applications. The performance of the controller is tested for different operating conditions.     

In situ growth of SiC wires on CVI densification of SiC foam

Silicon carbide (SiC) foam prepared by polymer infiltration and pyrolysis (PIP) process was further densified with β-SiC by chemical vapor infiltration (CVI) technique. Scanning electron microscopy and high-resolution transmission electron microscopy images confirmed the presence of highly entangled and branched in situ grown SiC wires of uniform diameter (∼500 nm) over the struts of open-cell SiC foam. A uniform rate increase in diameter from nanometer to micron range (∼11 μm) was observed with an increase in the CVI reaction period. X-ray diffraction results showed the formation of highly crystalline β-SiC structure along the <111> direction with stacking faults. The formation of SiC wires was explained by the vapor–liquid–solid mechanism and evenness of the surface and uniform growth rate of SiC confirmed the homogeneous concentration of gaseous species during CVI reaction. The compressive strength increased with relative density, with maximum values of 5.5 ± 1.26 MPa for ultimate SiC foam (ρ = 400 kg/m³) prepared by hybrid PIP/CVI technique. The thermo-oxidative stability of the resultant foam was evaluated up to 1650°C under air and shows excellent thermal stability compared to SiC foam prepared by PIP route. The densified SiC foam can find potential applications in the field of hot gas filters, catalyst supports, microwave absorption properties, and heat insulation for high-temperature applications.     

Nanoscale Assembly of 2D Materials for Energy and Environmental Applications

Rational design of 2D materials is crucial for the realization of their profound implications in energy and environmental fields. The past decade has witnessed significant developments in 2D material research, yet a number of critical challenges remain for real-world applications. Nanoscale assembly, precise control over the orientational and positional ordering, and complex interfaces among 2D layers are essential for the continued progress of 2D materials, especially for energy storage and conversion and environmental remediation. Herein, recent progress, the status, future prospects, and challenges associated with nanoscopic assembly of 2D materials are highlighted, specifically targeting energy and environmental applications. Geometric dimensional diversity of 2D material assembly is focused on, based on novel assembly mechanisms, including 1D fibers from the colloidal liquid crystalline phase, 2D films by interfacial tension (Marangoni effect), and 3D nanoarchitecture assembly by electrochemical processes. Relevant critical advantages of 2D material assembly are highlighted for application fields, including secondary batteries, supercapacitors, catalysts, gas sensors, desalination, and water decontamination.     

Algorithms for dense graphs and networks on the random access computer

We improve upon the running time of several graph and network algorithms when applied to dense graphs. In particular, we show how to compute on a machine with word size = (logn) a maximal matching in ann-vertex bipartite graph in timeO(n ²+n ^2.5/)=O(n ^2.5/logn), how to compute the transitive closure of a digraph withn vertices andm edges in timeO(n ²+nm/), how to solve the uncapacitated transportation problem with integer costs in the range [O.C] and integer demands in the range [–U.U] in timeO ((n ³ (log log/logn)^1/2+n² logU) lognC), and how to solve the assignment problem with integer costs in the range [O.C] in timeO(n ^2.5 lognC/(logn/loglogn)^1/4).Assuming a suitably compressed input, we also show how to do depth-first and breadth-first search and how to compute strongly connected components and biconnected components in timeO(n+n ²/), and how to solve the single source shortest-path problem with integer costs in the range [O.C] in time0 (n ²(logC)/logn). For the transitive closure algorithm we also report on the experiences with an implementation.Most of this research was carried out while both authors worked at the Fachbereich Informatik, Universität des Saarlandes, Saarbrücken, Germany. The research was supported in part by ESPRIT Project No. 3075 ALCOM. The first author acknowledges support also from NSERC Grant No. OGPIN007.     

On Rooted Node-Connectivity Problems

Let G be a graph which is k -outconnected from a specified root node r , that is, G has k openly disjoint paths between r and v for every node v . We give necessary and sufficient conditions for the existence of a pair rv,rw of edges for which replacing these edges by a new edge vw gives a graph that is k -outconnected from r . This generalizes a theorem of Bienstock et al. on splitting off edges while preserving k -node-connectivity. We also prove that if C is a cycle in G such that each edge in C is critical with respect to k -outconnectivity from r , then C has a node v , distinct from r , which has degree k . This result is the rooted counterpart of a theorem due to Mader. We apply the above results to design approximation algorithms for the following problem: given a graph with nonnegative edge weights and node requirements c _u for each node u , find a minimum-weight subgraph that contains max {c _u ,c _v } openly disjoint paths between every pair of nodes u,v . For metric weights, our approximation guarantee is 3 . For uniform weights, our approximation guarantee is \min{ 2, (k+2q-1)/k} . Here k is the maximum node requirement, and q is the number of positive node requirements. Received September 15, 1998; revised March 10, 2000, and April 17, 2000.     

Humic acid-immobilized polymer/bentonite composite as an adsorbent for the removal of copper(II) ions from aqueous solutions and electroplating industry wastewater

In this study, humic acid (HA) was immobilized onto amine-modified polyacrylamide/bentonite composite (Am-PAA-B) which was prepared by direct intercalation polymerization technique and the product (HA-Am-PAA-B) was used as an adsorbent for the removal of copper(II) ions from aqueous solutions. The surface characteristics of bentonite, Am-PAA-B and HA-Am-PAA-B were investigated. The adsorbent behaved like a cation exchanger and more than 99.0% Cu(II) ions’ removal was observed at the pH range 5.0–6.0. Kinetic and isotherm experiments showed that amount of Cu(II) ions adsorbed increases with increase of the initial concentration and temperature. The adsorption kinetic data were interpreted by pseudo-first-order and pseudo-second-order rate equations. The suitability of Langmuir, Freundlich and Dubinin–Radushkevich (D-R) adsorption models to the equilibrium data was investigated. The Langmuir isotherm was found to provide the best theoretical correlation of the experimental equilibrium data. The thermodynamic and kinetic activation parameters were derived to predict the nature of adsorption process and discussed in detail. The isosteric heat of adsorption was constant even after increase in surface loading. The removal efficiency of HA-Am-PAA-B was tested using electroplating industry wastewater. The desorption of adsorbed Cu(II) ions was achieved by 0.1 M HCl and four adsorption/desorption cycles were performed without significant decrease in the adsorption capacity.     

Synthesis and characterization of humic acid immobilized-polymer/bentonite composites and their ability to adsorb basic dyes from aqueous solutions

A new polyacrylamide-bentonite composite with amine functionality (Am-PAA-B) was prepared by direct polymerization in the presence of N,N'-methylenebisacrylamide as a crosslinking agent and potassium peroxydisulphate as an initiator followed by reaction with ethylenediammine. The Am-PAA-B was modified by immobilizing humic acid and tested as an adsorbent to remove basic dyes (Malachite Green, Methylene Blue and Crystal Violet) from aqueous solutions. XRD, conductometric and potentiometric titrations were used to characterize the adsorbent. The adsorbent behaved like a cation exchanger and more than 99.0% removal of dyes was observed at the pH range 5.0 to 8.0. The adsorption kinetic data were interpreted by pseudo-second-order rate equation and the film diffusion was the rate-limiting step. The equilibrium data were fitted well with the Freundlich isotherm model. Desorption of dyes was achieved by treatment with 0.1 M HNO₃ and four adsorption desorption cycles were performed without significant decrease in adsorption capacity.