High-speed Imaging of a Bulk Metallic Glass During Uniaxial Compression

High-speed imaging directly correlates the propagation of a particular shear band with mechanical measurements during uniaxial compression of a bulk metallic glass. Imaging shows shear occurs simultaneously over the entire shear plane, and load data, synced and time-stamped to the same clock as the camera, reveal that shear sliding is coincident with the load drop of each serration. Digital image correlation agrees with these results. These data demonstrate that shear band sliding occurs with velocities on the order of millimeters per second. Fracture occurs much more rapidly than the shear banding events, thereby readily leading to melting on fracture surfaces.

A Laboratory Experiment Using Nanoindentation to Demonstrate the Indentation Size Effect

A laboratory experiment using nanoindentation to demonstrate the indentation size effect is described. This laboratory introduces students to sophisticated instrumentation at low cost and low risk and utilizes recent research in the materials community as its foundation. The motivation, learning objectives, experimental details, data, and data analysis are presented. This experiment is intended for use in an upper-division materials science elective at the university level and has been successfully used in laboratory courses for senior undergraduates and first-year graduate students at Stanford University and Santa Clara University.

Slow Strain Rate Testing and Stress Corrosion Cracking of Ultra-Fine Grained and Conventional Al-Mg Alloy

Stress corrosion cracking susceptibility was investigated for an ultra-fine grained (UFG) AI-7.5Mg alloy and a conventional 5083 H111 alloy in natural seawater using slow strain rate testing (SSRT) at very slow strain rates between 1E(-5) s(-1), 1E(-6) s(-1) and 1E(-7) s(-1). The UFG Al-7.5Mg alloy was produced by cryomilling, while the 5083 H111 alloy is considered as a wrought manufactured product. The response of tensile properties to strain rate was analyzed and compared. Negative strain rate sensitivity was observed for both materials in terms of the elongation to failure. However, the UFG alloy displayed strain rate sensitivity in relation to strength while the conventional alloy was relatively strain rate insensitive. The mechanical behavior of the conventional 5083 alloy was attributed to dynamic strain aging (DSA) and delayed pit propagation while the performance of the UFG alloy was related to a diffusion-mediated stress relaxation mechanism that successfully delayed crack initiation events, counteracted by exfoliation and pitting which enhanced crack initiation. (C) 2014 Elsevier B.V. All rights reserved.

Mining for Class-Specific Motifs in Protein Sequence Classification

Background: In protein sequence classification, identification of the sequence motifs or n-grams that can precisely discriminate between classes is a more interesting scientific question than the classification itself. A number of classification methods aim at accurate classification but fail to explain which sequence features indeed contribute to the accuracy. We hypothesize that sequences in lower denominations (n-grams) can be used to explore the sequence landscape and to identify class-specific motifs that discriminate between classes during classification. Discriminative n-grams are short peptide sequences that are highly frequent in one class but are either minimally present or absent in other classes. In this study, we present a new substitution-based scoring function for identifying discriminative n-grams that are highly specific to a class. Results: We present a scoring function based on discriminative n-grams that can effectively discriminate between classes. The scoring function, initially, harvests the entire set of 4- to 8-grams from the protein sequences of different classes in the dataset. Similar n-grams of the same size are combined to form new n-grams, where the similarity is defined by positive amino acid substitution scores in the BLOSUM62 matrix. Substitution has resulted in a large increase in the number of discriminatory n-grams harvested. Due to the unbalanced nature of the dataset, the frequencies of the n-grams are normalized using a dampening factor, which gives more weightage to the n-grams that appear in fewer classes and vice-versa. After the n-grams are normalized, the scoring function identifies discriminative 4- to 8-grams for each class that are frequent enough to be above a selection threshold. By mapping these discriminative n-grams back to the protein sequences, we obtained contiguous n-grams that represent short class-specific motifs in protein sequences. Our method fared well compared to an existing motif finding method known as Wordspy. We have validated our enriched set of class-specific motifs against the functionally important motifs obtained from the NLSdb, Prosite and ELM databases. We demonstrate that this method is very generic; thus can be widely applied to detect class-specific motifs in many protein sequence classification tasks. Conclusion: The proposed scoring function and methodology is able to identify class-specific motifs using discriminative n-grams derived from the protein sequences. The implementation of amino acid substitution scores for similarity detection, and the dampening factor to normalize the unbalanced datasets have significant effect on the performance of the scoring function. Our multipronged validation tests demonstrate that this method can detect class-specific motifs from a wide variety of protein sequence classes with a potential application to detecting proteome-specific motifs of different organisms.