Biaxial strain induced electrical inhomogenities and phase separation in the ferromagnetic metallic phase in thin films of La0.7Ca0.3MnO3: A scanning tunneling potentiometry/spectroscopy study

We have investigated the effect of biaxial strain on local electrical/electronic properties in thin films of La0.7Ca0.3MnO3 with varying degrees of biaxial strain in them. The local electrical properties were investigated as a function of temperature by scanning tunneling spectroscopy (STS) and scanning tunneling potentiometry (STP), along with the bulk probe like conductance fluctuations.The results indicate a positive correlation between the lattice mismatch biaxial strain and the local electrical/electronic inhomogenities observed in the strained sample. This is plausible since the crystal structure of the manganites interfere rather strongly with the magnetic/electronic degrees of freedom. Thus even a small imbalance (biaxial strain) can induce significant changes in the electrical properties of the system.

The effect of T-stress on plane strain dynamic crack growth in elastic-plastic materials

In this paper, the effects of T -stress on steady, dynamic crack growth in an elastic-plastic material are examined using a modified boundary layer formulation. The analyses are carried out under mode I, plane strain conditions by employing a special finite element procedure based on moving crack tip coordinates. The material is assumed to obey the J (2) flow theory of plasticity with isotropic power law hardening. The results show that the crack opening profile as well as the opening stress at a finite distance from the tip are strongly affected by the magnitude and sign of the T -stress at any given crack speed. Further, it is found that the fracture toughness predicted by the analyses enhances significantly with negative T -stress for both ductile and cleavage mode of crack growth.

The carboxy terminal WD domain of the pre-mRNA splicing factor Prp17p is critical for function

In Saccharomyces cerevisiae, Prp17p is required for the efficient completion of the second step of pre-mRNA splicing. The function and interacting factors for this protein have not been elucidated. We have performed a mutational analysis of yPrp17p to identify protein domains critical for function. A series of deletions were made throughout the region spanning the N-terminal 158 amino acids of the protein, which do not contain any identified structural motifs. The C-terminal portion (amino acids 160–455) contains a WD domain containing seven WD repeats. We determined that a minimal functional Prp17p consists of the WD domain and 40 amino acids N-terminal to it. We generated a three-dimensional model of the WD repeats in Prp17p based on the crystal structure of the [beta]-transducin WD domain. This model was used to identify potentially important amino acids for in vivo functional characterization. Through analysis of mutations in four different loops of Prp17p that lie between [beta] strands in the WD repeats, we have identified four amino acids, 235TETG238, that are critical for function. These amino acids are predicted to be surface exposed and may be involved in interactions that are important for splicing. Temperature-sensitive prp17 alleles with mutations of these four amino acids are defective for the second step of splicing and are synthetically lethal with a U5 snRNA loop I mutation, which is also required for the second step of splicing. These data reinforce the functional significance of this region within the WD domain of Prp17p in the second step of splicing.

Size-dependent and strain rate effects in quantum dot nanostructures with molecular dynamic simulations

Size and strain rate effects are among several factors which play an important role in determining the response of nanostructures, such as their deformations, to the mechanical loadings. The mechanical deformations in nanostructure systems at finite temperatures are intrinsically dynamic processes. Most of the recent works in this context have been focused on nanowires [1, 2], but very little attention has been paid to such low dimensional nanostructures as quantum dots (QDs). In this contribution, molecular dynamics (MD) simulations with an embedded atom potential method(EAM) are carried out to analyse the size and strain rate effects in the silicon (Si) QDs, as an example. We consider various geometries of QDs such as spherical, cylindrical and cubic. We choose Si QDs as an example due to their major applications in solar cells and biosensing. The analysis has also been focused on the variation in the deformation mechanisms with the size and strain rate for Si QD embedded in a matrix of SiO2 [3] (other cases include SiN and SiC matrices).It is observed that the mechanical properties are the functions of the QD size, shape and strain rate as it is in the case for nanowires [2]. We also present the comparative study resulted from the application of different EAM potentials in particular, the Stillinger-Weber (SW) potential, the Tersoff potentials and the environment-dependent interatomic potential (EDIP) [1]. Finally, based on the stabilized structural properties we compute electronic bandstructures of our nanostructures using an envelope function approach and its finite element implementation.

Electrical and magneto-resistance of Co/CNT/epoxy thin film for strain and magnetic field sensing

Cobalt and iron nanoparticles are doped in carbon nanotube (CNT)/polymer matrix composites and studied for strain and magnetic field sensing properties. Characterization of these samples is done for various volume fractions of each constituent (Co and Fe nanoparticles and CNTs) and also for cases when only either of the metallic components is present. The relation between the magnetic field and polarization-induced strain are exploited. The electronic bandgap change in the CNTs is obtained by a simplified tight-binding formulation in terms of strain and magnetic field. A nonlinear constitutive model of glassy polymer is employed to account for (1) electric bias field dependent softening/hardening (2) CNT orientations as a statistical ensemble and (3) CNT volume fraction. An effective medium theory is then employed where the CNTs and nanoparticles are treated as inclusions. The intensity of the applied magnetic field is read indirectly as the change in resistance of the sample. Very small magnetic fields can be detected using this technique since the resistance is highly sensitive to strain. Its sensitivity due to the CNT volume fraction is also discussed. The advantage of this sensor lies in the fact that it can be molded into desirable shape and can be used in fabrication of embedded sensors where the material can detect external magnetic fields on its own. Besides, the stress-controlled hysteresis of the sample can be used in designing memory devices. These composites have potential for use in magnetic encoders, which are made of a magnetic field sensor and a barcode.

Stress-Strain Prediction of Jointed Rocks using Artificial Neural Networks

The applicability of Artificial Neural Networks for predicting the stress-strain response of jointed rocks at varied confining pressures, strength properties and joint properties (frequency, orientation and strength of joints) has been studied in the present paper. The database is formed from the triaxial compression tests on different jointed rocks with different confining pressures and different joint properties reported by various researchers. This input data covers a wide range of rock strengths, varying from very soft to very hard. The network was trained using a 3 layered network with feed forward back propagation algorithm. About 85% of the data was used for training and remaining15% for testing the predicting capabilities of the network. Results from the analyses were very encouraging and demonstrated that the neural network approach is efficient in capturing the complex stress-strain behaviour of jointed rocks. A single neural network is demonstrated to be capable of predicting the stress-strain response of different rocks, whose intact strength vary from 11.32 MPa to 123 MPa and spacing of joints vary from 10 cm to 100 cm for confining pressures ranging from 0 to 13.8 MPa.

Strain field measurement using digital image correlation

Digital Image Correlation and Tracking (DIC/DDIT) is an optical method that employs tracking & image registration techniques for accurate 2D and 3D measurements of changes in images. This is often used to measure deformation (engineering), displacement, and strain, but it is widely applied in many areas of science and engineering. One very common application is for measuring the motion of an optical mouse.

Effect of strain path change on the evolution of texture and microstructure during rolling of copper and nickel

The effect of strain path change during rolling has been investigated for copper and nickel using X-ray diffraction and electron back scatter diffraction as well as crystal plasticity simulations. Four different strain paths namely: (i) unidirectional rolling; (ii) reverse rolling; (iii) two-step cross rolling and (iv) multi-step cross rolling were employed to decipher the effect of strain path change on the evolution of deformation texture and microstructure. The cross rolled samples showed weaker texture with a prominent Bs {1 1 0}< 1 1 2 > and P(B(ND)) {1 1 0}< 1 1 1 > component in contrast to the unidirectional and reverse rolled samples where strong S {1 2 3}< 6 3 4 > and Cu {1 1 2}< 1 1 1 > components were formed. This was more pronounced for copper samples compared to nickel. The cross rolled samples were characterized by lower anisotropy and Taylor factor as well as less variation in Lankford parameter. Viscoplastic self-consistent simulations indicated that slip activity on higher number of octahedral slip systems can explain the weaker texture as well as reduced anisotropy in the cross rolled samples. (C) 2011 Elsevier B.V. All rights reserved.