Effect of layer thickness on the high temperature mechanical properties of Al/SiC nanolaminates

Composite laminates on the nanoscale have shown superior hardness and toughness, but little is known about their high temperature behavior. The mechanical properties (elastic modulus and hardness) were measured as a function of temperature by means of nanoindentation in Al/SiC nanolaminates, a model metal–ceramic nanolaminate fabricated by physical vapor deposition. The influence of the Al and SiC volume fraction and layer thicknesses was determined between room temperature and 150 °C and, the deformation modes were analyzed by transmission electron microscopy, using a focused ion beam to prepare cross-sections through selected indents. It was found that ambient temperature deformation was controlled by the plastic flow of the Al layers, constrained by the SiC, and the elastic bending of the SiC layers. The reduction in hardness with temperature showed evidence of the development of interface-mediated deformation mechanisms, which led to a clear influence of layer thickness on the hardness.

A highly resistive layer within the crust of X-ray pulsars limits their spin periods

The lack of isolated X-ray pulsars with spin periods longer than 12 s raises the question of where the population of evolved high-magnetic-field neutron stars has gone. Unlike canonical radiopulsars, X-ray pulsars are not subject to physical limits to the emission mechanism nor observational biases against the detection of sources with longer periods. Here we show that a highly resistive layer in the innermost part of the crust of neutron stars naturally limits the spin period to a maximum value of about 10–20 s. This highly resistive layer is expected if the inner crust is amorphous and heterogeneous in nuclear charge, possibly owing to the existence of a nuclear ‘pasta’ phase. Our findings suggest that the maximum period of isolated X-ray pulsars may be the first observational evidence for an amorphous inner crust, whose properties can be further constrained by future X-ray timing missions combined with more detailed models.

(Table 1) Physical properties of ODP Site 129-801

Compressional wave velocities and densities were measured for 6 basalt samples from ODP Hole 801B and 16 samples from ODP Hole 801C, a site that represents the first drilling of Jurassic-age crustal rocks in the Pacific basin. Incremental measurements, taken to a total pressure of 200 MPa, show a systematic decrease in velocity with increasing porosity and a related increase with increasing wet-bulk density. A comparison of the plot of porosity vs. compressional wave velocity with the theoretical equation from Wyllie et al. (1958) suggests this equation is inappropriate for oceanic basalts because of mineral alteration in high porosity samples. Also of interest is the dramatic change in velocity across a hydrothermal boundary. Basalts below this hydrothermal layer have a mean velocity of 6.05 km/s at 60 MPa while those above show a mean velocity of 4.55 km/s at 60 MPa. The low velocity values of the basalts above the hydrothermal deposit may be attributed to the higher porosity and composition observed in these rocks; the higher porosity is possibly the result of increased exposure to circulating seawater.

Physical models of dilatant normal faulting in jointed cohesive rocks

Dilatant faults often form in rocks containing pre-existing joints, but the effects of joints on fault segment linkage and fracture connectivity is not well understood. We present an analogue modeling study using cohesive powder with pre-formed joint sets in the upper layer, varying the angle between joints and a rigid basement fault. We analyze interpreted map-view photographs at maximum displacement for damage zone width, number of connected joints, number of secondary fractures, degree of segmentation and area fraction of massively dilatant fractures. Particle imaging velocimetry helps provide insights on deformation history of the experiments and illustrate the localization pattern of fault segments. Results show that with increasing angle between joint-set and basement-fault strike the number of secondary fractures and the number of connected joints increases, while the area fraction of massively dilatant fractures shows only a minor increase. Models without pre-existing joints show far lower area fractions of massively dilatant fractures while forming distinctly more secondary fractures.

Adsorption of Supercritical fluids on graphitised thermal carbon black: Molecular layer structure theory versus grand canonical Monte Carlo simulation

This paper presents a detailed analysis of adsorption of supercritical fluids on nonporous graphitized thermal carbon black. Two methods are employed in the analysis. One is the molecular layer structure theory (MLST), proposed recently by our group, and the other is the grand canonical Monte Carlo (GCMC) simulation. They were applied to describe the adsorption of argon, krypton, methane, ethylene, and sulfur hexafluoride on graphitized thermal carbon black. It was found that the MLST describes all the experimental data at various temperatures well. Results from GCMC simulations describe well the data at low pressure but show some deviations at higher pressures for all the adsorbates tested. The question of negative surface excess is also discussed in this paper.

Ion beam modification and analysis of metal/polymer bi-layer thin films

A set of varying-thickness Au-films were thermally evaporated onto poly(styrene-co-acrylonitrile) thin film surfaces. The Au/PSA bi-layer targets were then implanted with 50 keV N+ ions to a fluence of 1 × 1016 ions/cm2 to promote metal-to-polymer adhesion and to enhance their mechanical and electrical performance. Electrical conductivity measurements of the implanted Au/PSA thin films showed a sharp percolation behavior versus the pre-implant Au-film thickness with a percolation threshold near the nominal thickness of 44 Å. The electrical conductivity results are discussed along with the film microstructure and the elemental diffusion/mixing within the Au/PSA interface obtained by scanning electron microscopy (SEM) and ion beam analysis techniques (RBS and ERD).

Microstructure of MmM(5)/Mg multi-layer films prepared by magnetron sputtering

Microstructure of MmNi(3.5)(CoAlMn)(1.5)/Mg (here Mm denotes La-rich mischmetal) multi-layer hydrogen storage thin films prepared by direct current magnetron sputtering was investigated by cross-sectional transmission electron microscopy (XTEM). It was shown that the MMM5 layers are composed of two regions: an amorphous region with a thickness of similar to 4nm at the bottom of the layers and a randomly orientated nanocrystallite region on the top of the amorphous region and the Mg layers consist of typical columnar crystallite with their [001] direction nearly parallel to the growth direction. The mechanism for the formation of the above microstructure characteristics in the multi-layer thin films has been proposed. Based on the microstructure feature of the multi-layer films, mechanism for the apparent improvement of hydrogen absorption/desorption kinetics was discussed. (c) 2005 Elsevier B.V. All rights reserved.

Adsorption in slit pores and pore-size distribution: A molecular layer structure theory

A new approach is developed to analyze the thermodynamic properties of a sub-critical fluid adsorbed in a slit pore of activated carbon. The approach is based on a representation that an adsorbed fluid forms an ordered structure close to a smoothed solid surface. This ordered structure is modelled as a collection of parallel molecular layers. Such a structure allows us to express the Helmholtz free energy of a molecular layer as the sum of the intrinsic Helmholtz free energy specific to that layer and the potential energy of interaction of that layer with all other layers and the solid surface. The intrinsic Helmholtz free energy of a molecular layer is a function (at given temperature) of its two-dimensional density and it can be readily obtained from bulk-phase properties, while the interlayer potential energy interaction is determined by using the 10-4 Lennard-Jones potential. The positions of all layers close to the graphite surface or in a slit pore are considered to correspond to the minimum of the potential energy of the system. This model has led to accurate predictions of nitrogen and argon adsorption on carbon black at their normal boiling points. In the case of adsorption in slit pores, local isotherms are determined from the minimization of the grand potential. The model provides a reasonable description of the 0-1 monolayer transition, phase transition and packing effect. The adsorption of nitrogen at 77.35 K and argon at 87.29 K on activated carbons is analyzed to illustrate the potential of this theory, and the derived pore-size distribution is compared favourably with that obtained by the Density Functional Theory (DFT). The model is less time-consuming than methods such as the DFT and Monte-Carlo simulation, and most importantly it can be readily extended to the adsorption of mixtures and capillary condensation phenomena.

Effects of graphene layer size on the adsorption of fluids on graphitized thermal carbon black. A computer simulation study

The adsorption of Lennard-Jones fluids (argon and nitrogen) onto a graphitized thermal carbon black surface was studied with a Grand Canonical Monte Carlo Simulation (GCMC). The surface was assumed to be finite in length and composed of three graphene layers. When the GCMC simulation was used to describe adsorption on a graphite surface, an over-prediction of the isotherm was consistently observed in the pressure regions where the first and second layers are formed. To remove this over-prediction, surface mediation was accounted for to reduce the fluid-fluid interaction. Do and co-workers have introduced the so-called surface-mediation damping factor to correct the over-prediction for the case of a graphite surface of infinite extent, and this approach has yielded a good description of the adsorption isotherm. In this paper, the effects of the finite size of the graphene layer on the adsorption isotherm and how these would affect the extent of the surface mediation were studied. It was found that this finite-surface model provides a better description of the experimental data for graphitized thermal carbon black of high surface area (i.e. small crystallite size) while the infinite- surface model describes data for carbon black of very low surface area (i.e. large crystallite size).

An exploration of the effect of super large n-tuples on single layer RAMnets

N-tuple recognition systems (RAMnets) are normally modeled using a small number of input lines to each RAM, because the address space grows exponentially with the number of inputs. It is impossible to implement an arbitrarily-large address space as physical memory. But given modest amounts of training data, correspondingly modest numbers of bits will be set in that memory. Hash arrays can therefore be used instead of a direct implementation of the required address space. This paper describes some exploratory experiments using the hash array technique to investigate the performance of RAMnets with very large numbers of input lines. An argument is presented which concludes that performance should peak at a relatively small n-tuple size, but the experiments carried out so far contradict this. Further experiments are needed to confirm this unexpected result.

The role of biases in on-line learning of two-layer networks

The influence of biases on the learning dynamics of a two-layer neural network, a normalized soft-committee machine, is studied for on-line gradient descent learning. Within a statistical mechanics framework, numerical studies show that the inclusion of adjustable biases dramatically alters the learning dynamics found previously. The symmetric phase which has often been predominant in the original model all but disappears for a non-degenerate bias task. The extended model furthermore exhibits a much richer dynamical behavior, e.g. attractive suboptimal symmetric phases even for realizable cases and noiseless data.

On-line learning with adaptive back-propagation in two-layer networks

An adaptive back-propagation algorithm parameterized by an inverse temperature 1/T is studied and compared with gradient descent (standard back-propagation) for on-line learning in two-layer neural networks with an arbitrary number of hidden units. Within a statistical mechanics framework, we analyse these learning algorithms in both the symmetric and the convergence phase for finite learning rates in the case of uncorrelated teachers of similar but arbitrary length T. These analyses show that adaptive back-propagation results generally in faster training by breaking the symmetry between hidden units more efficiently and by providing faster convergence to optimal generalization than gradient descent.