High‐Entropy Alloys: Potential Candidates for High‐Temperature Applications – An Overview

Multi‐principal elemental alloys, commonly referred to as high‐entropy alloys (HEAs), are a new class of emerging advanced materials with novel alloy design concept. Unlike the design of conventional alloys, which is based on one or at most two principal elements, the design of HEA is based on multi‐principal elements in equal or near‐equal atomic ratio. The advent of HEA has revived the alloy design perception and paved the way to produce an ample number of compositions with different combinations of promising properties for a variety of structural applications. Among the properties possessed by HEAs, sluggish diffusion and strength retention at elevated temperature have caught wide attention. The need to develop new materials for high‐temperature applications with superior high‐temperature properties over superalloys has been one of the prime concerns of the high‐temperature materials research community. The current article shows that HEAs have the potential to replace Ni‐base superalloys as the next generation high‐temperature materials. This review focuses on the phase stability, microstructural stability, and high‐temperature mechanical properties of HEAs. This article will be highly beneficial for materials engineering and science community whose interest is in the development and understanding of HEAs for high‐temperature applications.     

Urinary proteomic analysis of chronic allograft nephropathy

The pathogenesis of progressive renal allograft injury, which is termed chronic allograft nephropathy (CAN), remains obscure and is currently defined by histology. Prospective protocol-biopsy trials have demonstrated that clinical and standard laboratory tests are insufficiently sensitive indicators of the development and progression of CAN. The study aim was to determine if CAN could be characterized by urinary proteomic data and identify the proteins associated with disease. The urinary proteome of 75 renal transplant recipients and 20 healthy volunteers was analyzed using surface enhanced laser desorption and ionization MS. Patients could be classified into subgroups with normal histology and Banff CAN grades 2-3 with a sensitivity of 86% and a specificity of 92% by applying the classification algorithm Adaboost to urinary proteomic data. Several urinary proteins associated with advanced CAN were identified including α1-microglobulin, β2-microglobulin, prealbumin, and endorepellin, the antiangiogenic C-terminal fragment of perlecan. Increased urinary endorepellin was confirmed by ELISA and increased tissue expression of the endorepellin/perlecan ratio by immunofluoresence analysis of renal biopsies. In conclusion, analysis of urinary proteomic data has further characterized the more severe CAN grades and identified urinary endorepellin, as a potential biomarker of advanced CAN.     

On the relationship between dependence tree classification error and Bayes error rate

Wong and Poon [1] showed that Chow and Liu's tree dependence approximation can be derived by minimizing an upper bound of the Bayes error rate. Wong and Poon's result was obtained by expanding the conditional entropy H(w|X). We derive the correct expansion of H(w|X) and present its implication.     

Analysis of temporal jitter in a copper vapor laser system

Temporal jitter in a magnetic pulse compression based copper vapor laser (CVL) system is analyzed by considering ripple present in the input dc power supply and ripple present in the magnetic core resetting power supply. It is shown that the jitter is a function of the ratio of operating voltage to the designed voltage, percentage ripple, and the total propagation delay of the magnetic pulse compression circuit. Experimental results from a CVL system operating at a repetition rate of 9 kHz are presented.     

Enhanced abstract data types in object-relational databases

The explosion in complex multimedia content makes it crucial for database systems to support such data efficiently. This paper argues that the “blackbox” ADTs used in current object-relational systems inhibit their performance, thereby limiting their use in emerging applications. Instead, the next generation of object-relational database systems should be based on enhanced abstract data type (E-ADT) technology. An (E-ADT) can expose the semantics of its methods to the database system, thereby permitting advanced query optimizations. Fundamental architectural changes are required to build a database system with E-ADTs; the added functionality should not compromise the modularity of data types and the extensibility of the type system. The implementation issues have been explored through the development of E-ADTs in Predator. Initial performance results demonstrate an order of magnitude in performance improvements. Received January 1, 1998 / Accepted May 27, 1998     

Deep packet inspection using parallel bloom filters

There is a class of packet processing applications that inspect packets deeper than the protocol headers to analyze content. For instance, network security applications must drop packets containing certain malicious Internet worms or computer viruses carried in a packet payload. Content forwarding applications look at the hypertext transport protocol headers and distribute the requests among the servers for load balancing. Packet inspection applications, when deployed at router ports, must operate at wire speeds. With networking speeds doubling every year, it is becoming increasingly difficult for software-based packet monitors to keep up with the line rates. We describe a hardware-based technique using Bloom filters, which can detect strings in streaming data without degrading network throughput. A Bloom filter is a data structure that stores a set of signatures compactly by computing multiple hash functions on each member of the set. This technique queries a database of strings to check for the membership of a particular string. The answer to this query can be false positive but never a false negative. An important property of this data structure is that the computation time involved in performing the query is independent of the number of strings in the database provided the memory used by the data structure scales linearly with the number of strings stored in it. Furthermore, the amount of storage required by the Bloom filter for each string is independent of its length.     

Synthesis and characterization of high molecular weight polyaniline for organic electronic applications

High molecular weight polyaniline (PANI) was synthesized by a combined procedure incorporating various synthesis methods. Temperature and open circuit potential of the reaction mixture were collected to monitor the reaction progress. The polymer is characterized by various techniques including gel permeation chromatography, dynamic light scattering, infrared spectroscopy, solid‐state nuclear magnetic resonance, and differential scanning calorimetry for elucidating the molecular architecture obtained by this method. As‐synthesized PANI was found to possess high molecular weight, reduced branching, reduced cross‐linking, and to predominantly consist of linear polymer chains. This polymer was also found to be more stable in solution form. J–V characteristics of as‐synthesized PANI films indicate a high current density which is due to increased free pathways and less traps for the charge transport to occur in PANI films. POLYM. ENG. SCI., 2012. © 2012 Society of Plastics Engineers