A summary of the behavior of materials at cryogenic temperatures

Summary of material behavior at cryogenic temperature

Pressure-viscosity measurements for several lubricants to 5.5 x 10 to the 8th power Newtons per square meter (8 x 10 to the 4th psi) and 149 C (300 F)

A capillary viscometer was used to measure viscosity as a function of pressure, temperature, and shear stress for a number of lubricants. The conditions under which the measurements were made are specified. The results obtained for each material are analyzed. It was determined that all pressure-viscosity coefficients decreased with increasing temperature. Data from other techniques such as optical elastohydrodynamics, oscillating crystal, and low shear capillary viscometry were compared with the results obtained

Detectability of the First Cosmic Explosions

We present a fully self-consistent simulation of a synthetic survey of the furthermost cosmic explosions. The appearance of the first generation of stars (Population III) in the Universe represents a critical point during cosmic evolution, signaling the end of the dark ages, a period of absence of light sources. Despite their importance, there is no confirmed detection of Population III stars so far. A fraction of these primordial stars are expected to die as pair-instability supernovae (PISNe), and should be bright enough to be observed up to a few hundred million years after the big bang. While the quest for Population III stars continues, detailed theoretical models and computer simulations serve as a testbed for their observability. With the upcoming near-infrared missions, estimates of the feasibility of detecting PISNe are not only timely but imperative. To address this problem, we combine state-of-the-art cosmological and radiative simulations into a complete and self-consistent framework, which includes detailed features of the observational process. We show that a dedicated observational strategy using $\lesssim 8$ per cent of total allocation time of the James Webb Space Telescope mission can provide us up to $\sim 9-15$ detectable PISNe per year.Comment: 9 pages, 8 figures. Minor corrections added to match published versio

Solution to the problem of the poor cyclic fatigue resistance of bulk metallic glasses

The recent development of metallic glass-matrix composites represents a particular milestone in engineering materials for structural applications owing to their remarkable combination of strength and toughness. However, metallic glasses are highly susceptible to cyclic fatigue damage, and previous attempts to solve this problem have been largely disappointing. Here, we propose and demonstrate a microstructural design strategy to overcome this limitation by matching the microstructural length scales (of the second phase) to mechanical crack-length scales. Specifically, semisolid processing is used to optimize the volume fraction, morphology, and size of second-phase dendrites to confine any initial deformation (shear banding) to the glassy regions separating dendrite arms having length scales of ≈2 μm, i.e., to less than the critical crack size for failure. Confinement of the damage to such interdendritic regions results in enhancement of fatigue lifetimes and increases the fatigue limit by an order of magnitude, making these “designed” composites as resistant to fatigue damage as high-strength steels and aluminum alloys. These design strategies can be universally applied to any other metallic glass systems

Geometry of random interactions

It is argued that spectral features of quantal systems with random interactions can be given a geometric interpretation. This conjecture is investigated in the context of two simple models: a system of randomly interacting d bosons and one of randomly interacting fermions in a j=7/2 shell. In both examples the probability for a given state to become the ground state is shown to be related to a geometric property of a polygon or polyhedron which is entirely determined by particle number, shell size, and symmetry character of the states. Extensions to more general situations are discussed

Fracture toughness and crack-resistance curve behavior in metallic glass-matrix composites

Nonlinear-elastic fracture mechanics methods are used to assess the fracture toughness of bulk metallic glass (BMG) composites; results are compared with similar measurements for other monolithic and composite BMG alloys. Mechanistically, plastic shielding gives rise to characteristic resistance-curve behavior where the fracture resistance increases with crack extension. Specifically, confinement of damage by second-phase dendrites is shown to result in enhancement of the toughness by nearly an order of magnitude relative to unreinforced glass

Accommodation of lattice mismatch in Ge_(x)Si_(1−x)/Si superlattices

We present evidence that the critical thickness for the appearance of misfit defects in a given material and heteroepitaxial structure is not simply a function of lattice mismatch. We report substantial differences in the relaxation of mismatch stress in Ge_(0.5)Si_(0.5)/Si superlattices grown at different temperatures on (100) Si substrates. Samples have been analyzed by x‐ray diffraction, channeled Rutherford backscattering, and transmission electron microscopy. While a superlattice grown at 365 °C demonstrates a high degree of elastic strain, with a dislocation density <10^5 cm^(−2) , structures grown at higher temperatures show increasing numbers of structural defects, with densities reaching 2×10^(10) cm^(−2) at a growth temperature of 530 °C. Our results suggest that it is possible to freeze a lattice‐mismatched structure in a highly strained metastable state. Thus it is not surprising that experimentally observed critical thicknesses are rarely in agreement with those predicted by equilibrium theories

Fock space relativistic coupled-Cluster calculations of Two-Valence Atoms

We have developed an all particle Fock-space relativistic coupled-cluster method for two-valence atomic systems. We then describe a scheme to employ the coupled-cluster wave function to calculate atomic properties. Based on these developments we calculate the excitation energies, magnetic hyperfine constants and electric dipole matrix elements of Sr, Ba and Yb. Further more, we calculate the electric quadrupole HFS constants and the electric dipole matrix elements of Sr$^+$, Ba$^+$ and Yb$^+$. For these we use the one-valence coupled-cluster wave functions obtained as an intermediate in the two-valence calculations. We also calculate the magnetic dipole hyperfine constants of Yb$^+$.Comment: 23 pages, 12 figures, 10 tables typos are corrected and some minor modifications in some of the section

Generalized seniority from random Hamiltonians

We investigate the generic pairing properties of shell-model many-body Hamiltonians drawn from ensembles of random two-body matrix elements. Many features of pairing that are commonly attributed to the interaction are in fact seen in a large part of the ensemble space. Not only do the spectra show evidence of pairing with favored J=0 ground states and an energy gap, but the relationship between ground state wave functions of neighboring nuclei show signatures of pairing as well. Matrix elements of pair creation/annihilation operators between ground states tend to be strongly enhanced. Furthermore, the same or similar pair operators connect several ground states along an isotopic chain. This algebraic structure is reminiscent of the generalized seniority model. Thus pairing may be encoded to a certain extent in the Fock space connectivity of the interacting shell model even without specific features of the interaction required.Comment: 10 pages, 7 figure

A Cost-based Optimizer for Gradient Descent Optimization

As the use of machine learning (ML) permeates into diverse application domains, there is an urgent need to support a declarative framework for ML. Ideally, a user will specify an ML task in a high-level and easy-to-use language and the framework will invoke the appropriate algorithms and system configurations to execute it. An important observation towards designing such a framework is that many ML tasks can be expressed as mathematical optimization problems, which take a specific form. Furthermore, these optimization problems can be efficiently solved using variations of the gradient descent (GD) algorithm. Thus, to decouple a user specification of an ML task from its execution, a key component is a GD optimizer. We propose a cost-based GD optimizer that selects the best GD plan for a given ML task. To build our optimizer, we introduce a set of abstract operators for expressing GD algorithms and propose a novel approach to estimate the number of iterations a GD algorithm requires to converge. Extensive experiments on real and synthetic datasets show that our optimizer not only chooses the best GD plan but also allows for optimizations that achieve orders of magnitude performance speed-up.Comment: Accepted at SIGMOD 201