Wetting Behavior of Ternary Au-Ge-X (X=Sb, Sn) Alloys on Cu and Ni

Au-Ge-based alloys are potential substitutes for Pb-rich solders currently used for high-temperature applications. In the present work, the wetting behavior of two Au-Ge-X (X=Sb, Sn) ternary alloys, i.e., Au-15Ge-17Sb and Au-13.7 Ge-15.3Sn (at.%), in contact with Cu and Ni substrates has been investigated. Au-13.7Ge-15.3Sn alloy showed complete wetting on both Cu and Ni substrates. Total spreading of Au-15Ge-17Sb alloy on Cu was also observed, while the final contact angle of this alloy on Ni was about 29°. Pronounced dissolution of Cu substrates into the solder alloys investigated was detected, while the formation of Ni-Ge intermetallic compounds at the interface of both solder/Ni systems suppressed the dissolution of Ni into the solde

Wetting and Soldering Behavior of Eutectic Au-Ge Alloy on Cu and Ni Substrates

Au-Ge-based alloys are interesting as novel high-temperature lead-free solders because of their low melting point, good thermal and electrical conductivity, and high corrosion resistance. In the present work, the wetting and soldering behavior of the eutectic Au-28Ge (at.%) alloy on Cu and Ni substrates have been investigated. Good wetting on both substrates with final contact angles of 13° to 14° was observed. In addition, solder joints with bond shear strength of 30MPa to 35MPa could be produced under controlled conditions. Cu substrates exhibit pronounced dissolution into the Au-Ge filler metal. On Ni substrates, the NiGe intermetallic compound was formed at the filler/substrate interface, which prevents dissolution of Ni into the solder. Using thin filler metal foils (25μm), complete consumption of Ge in the reaction at the Ni interface was observed, leading to the formation of an almost pure Au layer in the soldering zon

Thermodynamic assessment of the Cu-Ge binary system

The Cu-Ge binary system was assessed thermodynamically using the CALPHAD method through Thermocalc (R) software package based on the evaluation of all available experimental data from the published literature. The solution phases, including liquid, fcc, hcp and diamond (Ge), were described by the substitutional solution model, of which the excess Gibbs energies were expressed with the Redlich-Kister polynomial. Due to their narrow homogeneity ranges, all intermetallic compounds, epsilon-Cu0.765Ge0.235, theta-Cu0.735Ge0.265 and eta-Cu0.75Ge0.25, were modeled as stoichiometric compounds. A set of self-consistent thermodynamic parameters formulating the Gibbs energies of various phases in the Cu-Ge binary system was obtained finally. A good agreement is achieved between the calculated results and the reported experimental data. (C) 2010 Elsevier B.V. All rights reserved

Proving Memory Safety of the ANI Windows Image Parser Using Compositional Exhaustive Testing

We report in this paper how we proved memory safety of a complex Windows image parser written in low-level C in only three months of work and using only three core tech-niques, namely (1) symbolic execution at the x86 binary level, (2) exhaustive program path enumeration and testing, and (3) user-guided program decomposition and summariza-tion. We also used a new tool, named MicroX, for executing code fragments in isolation using a custom virtual machine designed for testing purposes. As a result of this work, we are able to prove, for the first time, that a Windows image parser is memory safe, i.e., free of any buffer-overflow secu-rity vulnerabilities, modulo the soundness of our tools and several additional assumptions regarding bounding input-dependent loops, fixing a few buffer-overflow bugs, and ex-cluding some code parts that are not memory safe by design. In the process, we also discovered and fixed several limita-tions in our tools, and narrowed the gap between systematic testing and verification. 1

A formally verified compiler back-end

This article describes the development and formal verification (proof of semantic preservation) of a compiler back-end from Cminor (a simple imperative intermediate language) to PowerPC assembly code, using the Coq proof assistant both for programming the compiler and for proving its correctness. Such a verified compiler is useful in the context of formal methods applied to the certification of critical software: the verification of the compiler guarantees that the safety properties proved on the source code hold for the executable compiled code as well

On the Verification of Memory Management Mechanisms

We define physical machines as processors with physical memory and swap memory; in user mode physical machines support address translation. We report about the formal verification of a complex processor supporting address translation by means of a memory management unit (MMU). We give a paper and pencil proof that physical machines togethe

Mechanized semantics for the Clight subset of the C language

This article presents the formal semantics of a large subset of the C language called Clight. Clight includes pointer arithmetic, "struct" and "union" types, C loops and structured "switch" statements. Clight is the source language of the CompCert verified compiler. The formal semantics of Clight is a big-step operational semantics that observes both terminating and diverging executions and produces traces of input/output events. The formal semantics of Clight is mechanized using the Coq proof assistant. In addition to the semantics of Clight, this article describes its integration in the CompCert verified compiler and several ways by which the semantics was validated.Comment: Journal of Automated Reasoning (2009

First amyloid β1-42 certified reference material for re-calibrating commercial immunoassays

INTRODUCTION: Reference materials based on human cerebrospinal fluid were certified for the mass concentration of amyloid beta (Aβ)1-42 (Aβ42 ). They are intended to be used to calibrate diagnostic assays for Aβ42 . METHODS: The three certified reference materials (CRMs), ERM-DA480/IFCC, ERM-DA481/IFCC and ERM-DA482/IFCC, were prepared at three concentration levels and characterized using isotope dilution mass spectrometry methods. Roche, EUROIMMUN, and Fujirebio used the three CRMs to re-calibrate their immunoassays. RESULTS: The certified Aβ42 mass concentrations in ERM-DA480/IFCC, ERM-DA481/IFCC, and ERM-DA482/IFCC are 0.45, 0.72, and 1.22 μg/L, respectively, with expanded uncertainties (k = 2) of 0.07, 0.11, and 0.18 μg/L, respectively. Before re-calibration, a good correlation (Pearson's r > 0.97), yet large biases, were observed between results from different commercial assays. After re-calibration the between-assay bias was reduced to < 5%. DISCUSSION: The Aβ42 CRMs can ensure the equivalence of results between methods and across platforms for the measurement of Aβ42

Statistical learning of peptide retention behavior in chromatographic separations: a new kernel-based approach for computational proteomics

<p>Abstract</p> <p>Background</p> <p>High-throughput peptide and protein identification technologies have benefited tremendously from strategies based on tandem mass spectrometry (MS/MS) in combination with database searching algorithms. A major problem with existing methods lies within the significant number of false positive and false negative annotations. So far, standard algorithms for protein identification do not use the information gained from separation processes usually involved in peptide analysis, such as retention time information, which are readily available from chromatographic separation of the sample. Identification can thus be improved by comparing measured retention times to predicted retention times. Current prediction models are derived from a set of measured test analytes but they usually require large amounts of training data.</p> <p>Results</p> <p>We introduce a new kernel function which can be applied in combination with support vector machines to a wide range of computational proteomics problems. We show the performance of this new approach by applying it to the prediction of peptide adsorption/elution behavior in strong anion-exchange solid-phase extraction (SAX-SPE) and ion-pair reversed-phase high-performance liquid chromatography (IP-RP-HPLC). Furthermore, the predicted retention times are used to improve spectrum identifications by a <it>p</it>-value-based filtering approach. The approach was tested on a number of different datasets and shows excellent performance while requiring only very small training sets (about 40 peptides instead of thousands). Using the retention time predictor in our retention time filter improves the fraction of correctly identified peptide mass spectra significantly.</p> <p>Conclusion</p> <p>The proposed kernel function is well-suited for the prediction of chromatographic separation in computational proteomics and requires only a limited amount of training data. The performance of this new method is demonstrated by applying it to peptide retention time prediction in IP-RP-HPLC and prediction of peptide sample fractionation in SAX-SPE. Finally, we incorporate the predicted chromatographic behavior in a <it>p</it>-value based filter to improve peptide identifications based on liquid chromatography-tandem mass spectrometry.</p