Coupling in situ experiments and modeling – Opportunities for data fusion,machine learning,and discovery of emergent behavior

This paper reviews recent studies, that not only includes both experiments and modeling components, but celebrates a close coupling between these techniques, in order to provide insights into the plasticity and failure of polycrystalline metals. Examples are provided of studies across multiple-scales, including, but not limited to, density functional theory combined with atom probe tomography, molecular dynamics combined with in situ transmission electron miscopy, discrete dislocation dynamics combined with nanopillars experiments, crystal plasticity combined with digital image correlation, and crystal plasticity combined with in situ high energy X-ray diffraction. The close synergy between in situ experiments and modeling provides new opportunities for model calibration, verification, and validation, by providing direct means of comparison, thus removing aspects of epistemic uncertainty in the approach. Further, data fusion between in situ experimental and model-based data, along with data driven approaches, provides a paradigm shift for determining the emergent behavior of deformation and failure, which is the foundation that underpins the mechanical behavior of polycrystalline materials.     

The robust knapsack problem with queries

We consider robust knapsack problems where item weights are uncertain. We are allowed to query an item to find its exact weight,where the number of such queries is bounded by a given parameter Q. After these queries are made, we need to pack the items robustly, i.e., so that the choice of items is feasible for every remaining possible scenario of item weights.The central question that we consider is: Which items should be queried in order to gain maximum profit? We introduce the notion of query competitiveness for strict robustness to evaluate the quality of an algorithm for this problem, and obtain lower and upper bounds on this competitiveness for interval-based uncertainty. Similar to the study of online algorithms, we study the competitiveness under different frameworks, namely we analyze the worst-case query competitiveness for deterministic algorithms, the expected query competitiveness for randomized algorithms and the average case competitiveness for known distributions of the uncertain input data. We derive theoretical bounds for these different frameworks and evaluate them experimentally. We also extend this approach to Γ-restricted uncertainties introduced by Bertsimas and Sim.Furthermore, we present heuristic algorithms for the problem. In computational experiments considering both the interval-based and the Γ-restricted uncertainty, we evaluate their empirical performance. While the usage of a Γ-restricted uncertainty improves the nominal performance of a solution (as expected), we find that the query competitiveness gets worse.     

A model for semiconductor quantum dot molecule based on the current spin density functional theory

Based on the current spin density functional theory, a theoretical model of three vertically aligned semiconductor quantum dots is proposed and numerically studied. This quantum dot molecule (QDM) model is treated with realistic hard-wall confinement potential and external magnetic field in three-dimensional setting. Using the effective-mass approximation with band nonparabolicity, the many-body Hamiltonian results in a cubic eigenvalue problem from a finite difference discretization. A self-consistent algorithm for solving the Schrödinger-Poisson system by using the Jacobi-Davidson method and GMRES is given to illustrate the Kohn-Sham orbitals and energies of six electrons in the molecule with some magnetic fields. It is shown that the six electrons residing in the central dot at zero magnetic field can be changed to such that each dot contains two electrons with some feasible magnetic field. The Förster-Dexter resonant energy transfer may therefore be generated by two individual QDMs. This may motivate a new paradigm of Fermionic qubits for quantum computing in solid-state systems.     

空气钻井技术在普光气田的应用

普光气田是四川盆地已发现的最大天然气田。普光气田已钻井实践表明,常规钻井液钻井技术机械钻速低,钻井周期长,钻井复杂及事故多,无法满足普光气田开发要求。为了提高钻井速度,缩短钻井周期,加快普光气田的开发进程,在PD-1井、P2-2井、PA-2井、P4-2井、P6-3井等5口井进行了空气钻井试验。文中分析了普光气田进行空气钻井的可行性,介绍了空气钻井技术在普光气田的实践情况,并对空气钻井的效果进行了评价,分析了空气钻井技术在普光气田进一步应用需要重视和解决的问题,并提出了今后的研究方向。     

Attribute Allocation and Retrieval Scheme for Large-Scale Sensor Networks

Wireless sensor network is an emerging technology that enables remote monitoring of large geographical regions. In this paper, we address the problem of distributing attributes over such a large-scale sensor network so that the cost of data retrieval is minimized. The proposed scheme is a data-centric storage scheme where the attributes are distributed over the network depending on the correlations between them. The problem addressed here is similar to the Allocation Problem of distributed databases. In this paper, we have defined the Allocation Problem in the context of sensor networks and have proposed a scheme for finding a good distribution of attributes to the sensor network. We also propose an architecture for query processing given such a distribution of attributes. We analytically determine the conditions under which the proposed architecture is beneficial and present simulation results to demonstrate the same. To the best of our knowledge, this is the first attempt to determine an allocation of attributes over a sensor network based on the correlations between attributes.     

X-ray diffraction and Raman scattering in SbSI nanocrystals

Lattice structure and rod-like shaped SbSI nanocrystals obtained by ball milling with rod thickness down to 70 nm, as estimated from X-ray diffraction (XRD) and electron microscopy, is similar to that of the bulk crystals. The dependence of the grain size on the milling duration is discussed in view of the chain-like crystalline structure of SbSI. Possible factors, responsible for the observed Raman line broadening, are discussed, scattering by surface phonons being considered the predominant one.     

STATIONARY TANGENT: THE DISCRETE AND NON-SMOOTH CASE

Abstract. In Keich (2000 ),we define a stationary tangent process, or a locally optimal stationary approximation, to a real non-stationary smooth Gaussian process. This paper extends the idea by constructing a discrete tangent – a `locally' optimal stationary approximation – for a discrete time, real Gaussian process. Analogously to the smooth case, our construction relies on a generalization of the recursion formula for the orthogonal polynomials of the spectral distribution function. More precisely, we use a generalization of the Schur parameters to identify the stationary tangent. By way of discretizing, we later demonstrate how this tangent can be used to obtain `good' local stationary approximations to non-smooth continuous time, real Gaussian processes. Further, we demonstrate how, analogously to the curvatures in the smooth case, the Schur parameters can be used to determine the order of stationarity of a non-smooth process.     

Chemische Zusammensetzung und Mikrostruktur polymerabgeleiteter Gläser und Keramiken im System Si–C–O. Teil 2: Charakterisierung der Gefügeausbildung mittels hochauflösender Durchstrahlungselektronenmikroskopie und Feinbereichsbeugung

Chemical Composition and Microstructure of Polymer‐Derived Glasses and Ceramics in the Si–C–O System. Part 2: Characterization of microstructure formation by means of high‐resolution transmission electron microscopy and selected area diffraction Liquid or solid silicone resins represent the economically most interesting class of organic precursors for the pyrolytic production of glass and ceramics materials on silicon basis. As dense, dimensionally stable components can be cost‐effectively achieved by admixing reactive filler powders, chemical composition and microstructure development of the polymer‐derived residues must be exactly known during thermal decomposition. Thus, in the present work, glasses and ceramics produced by pyrolysis of the model precursor polymethylsiloxane at temperatures from 525 to 1550 °C are investigated. In part 1, by means of analytical electron microscopy, the bonding state of silicon was determined on a nanometre scale and the phase separation of the metastable Si–C–O matrix into SiO₂, C and SiC was proved. The in‐situ crystallization could be considerably accelerated by adding fine‐grained powder of inert fillers, such as Al₂O₃ or SiC, which permits effective process control. In part 2, the microstructure is characterized by high‐resolution transmission electron microscopy and selected area diffraction. Turbostratic carbon and cubic β‐SiC precipitate as crystallization products. Theses phases are embedded in an amorphous matrix. Inert fillers reduce the crystallization temperature by several hundred °C. In this case, the polymer‐derived Si–C–O material acts as a binding agent between the powder particles. Reaction layer formation does not occur. On the investigated pyrolysis conditions, no crystallization of SiO₂ was observed.     

The magnetic structure of TbNiSiD1.78

TbNiSiD_1.78 has been studied by powder neutron diffraction below 100 K. The compound takes the hexagonal room temperature structure at 100 and 50 K (P6₃/mmc). At 2 K, below the antiferromagnetic ordering temperature of 10 K, there is a small orthorhombic distortion of the lattice. The refined unit-cell dimensions at 2 K (space group Pnma) are a=7.9505(2), b=4.02502(14), c=6.9823(2) Å. The magnetic moments of Tb are 8.71(6) μ_B, and are ordered antiferromagnetically along a.