Effect of pressure on the properties of DH diode lasers in AlxGa1-xAsySb1-y/GaSb system

Abstract

A helium pressure appparatus for diode laser studies up to 1.4 GPa at 77–300 K has been developed. DH lasers with Al_xGa_1-xAs_ySb_1-y active layers (x=0-0.05) lattice-matched to GaSb substrates have been investigated. It has been shown that in lasers with x,y=0 pressure dependences of the threshold current density (J_th) and the average electron lifetime at the threshold (τ) measured at 80 K depend strongly on the quadratic recombination of L^c ₆ electrons, the characteristic coefficient being 1.5×10^?11 cm³s^?1. The pressure-composition equivalence coefficient dx/dP=2.2×10^?10 Pa^?1 has been obtained for the lowest temperatures used.     

Reference materials for large-scale metal deposition surveys

 In order to ensure quality assurance in large-scale environmental contamination studies involving many different analytical laboratories, the use of calibrated reference materials is essential. Prior to a survey of atmospheric metal deposition in 1995 comprising 20 countries and covering large parts of Europe, the lack of suitable reference materials of moss and organic-rich soil was apparent. In order to improve the quality of analytical data to be produced in this international survey, candidate analytical laboratories were invited to participate in an intercomparison exercise. Three moss and three soil humus reference samples specifically prepared for this purpose were distributed anonymously among the laboratories, which were asked to report data for ten priority elements (V, Cr, Fe, Ni, Cu, Zn, As, Cd, Hg, Pb) and as many additional elements as they determined normally. In this paper the analytical data from the intercomparison are evaluated, and recommended values for the ten priority elements and 17 additional elements (B, Na, Mg, Al, S, K, Ca, Mn, Co, Se, Rb, Sr, Sb, Cs, Ba, La, Th) in each of the six reference samples are established. These samples should be useful for similar future studies including areas where the contamination levels are very low. Received: 17 October 1996 Accepted: 2 January 1997     

Preference programming for robust portfolio modeling and project selection

In decision analysis, difficulties of obtaining complete information about model parameters make it advisable to seek robust solutions that perform reasonably well across the full range of feasible parameter values. In this paper, we develop the Robust Portfolio Modeling (RPM) methodology which extends Preference Programming methods into portfolio problems where a subset of project proposals are funded in view of multiple evaluation criteria. We also develop an algorithm for computing all non-dominated portfolios, subject to incomplete information about criterion weights and project-specific performance levels. Based on these portfolios, we propose a project-level index to convey (i) which projects are robust choices (in the sense that they would be recommended even if further information were to be obtained) and (ii) how continued activities in preference elicitation should be focused. The RPM methodology is illustrated with an application using real data on road pavement projects.     

Robust portfolio modeling with incomplete cost information and project interdependencies

Robust portfolio modeling (RPM) [Liesiö, J., Mild, P., Salo, A., 2007. Preference programming for robust portfolio modeling and project selection. European Journal of Operational Research 181, 1488–1505] supports project portfolio selection in the presence of multiple evaluation criteria and incomplete information. In this paper, we extend RPM to account for project interdependencies, incomplete cost information and variable budget levels. These extensions lead to a multi-objective zero-one linear programming problem with interval-valued objective function coefficients for which all non-dominated solutions are determined by a tailored algorithm. The extended RPM framework permits more comprehensive modeling of portfolio problems and provides support for advanced benefit–cost analyses. It retains the key features of RPM by providing robust project and portfolio recommendations and by identifying projects on which further attention should be focused. The extended framework is illustrated with an example on product release planning.     

FREE RADICALS FROM PHOTODECOMPOSITION OF BISPHENOL-A

Abstract— Irradiation of 2,2-bis-(4-hydroxyphenyl)-propane (bisphenol-A) with UV light causes photo-decomposition of the compound. Spin-trapping with α-phenyl-N-tert-butyl-nitrone showed that free radicals were cleaved from the molecule. No direct ESR-spectroscopic information concerning the structure of the remaining radical skeleton could be obtained. Gas chromatographic mass spectrometric analysis of the decomposition products indicated the existence of a semiquinone structure following cleavage of a methyl radical from 2,2-bis-4–(hydroxyphenyl)-propane. The capacity of 2,2-bis-(4- hydroxyphenyl)-propane to give rise to radicals might explain its photoallergenic properties.     

Scenario-based portfolio selection of investment projects with incomplete probability and utility information

In the selection of investment projects, it is important to account for exogenous uncertainties (such as macroeconomic developments) which may impact the performance of projects. These uncertainties can be addressed by examining how the projects perform across several scenarios; but it may be difficult to assign well-founded probabilities to such scenarios, or to characterize the decision makers’ risk preferences through a uniquely defined utility function. Motivated by these considerations, we develop a portfolio selection framework which (i) uses set inclusion to capture incomplete information about scenario probabilities and utility functions, (ii) identifies all the non-dominated project portfolios in view of this information, and (iii) offers decision support for rejection and selection of projects. The proposed framework enables interactive decision support processes where the implications of additional probability and utility information or further risk constraints are shown in terms of corresponding decision recommendations.     

Atomic layer deposition of HfO2 on graphene from HfCl4 and H2O

Atomic layer deposition of HfO₂ on unmodified graphene from HfCl₄ and H₂O was investigated. Surface RMS roughness down to 0.5 nm was obtained for amorphous, 30 nm thick hafnia film grown at 180°C. HfO₂ was also deposited in a two-step temperature process where the initial growth of about 1 nm at 170°C was continued up to 10–30 nm at 300°C. This process yielded uniform, monoclinic HfO₂ films with RMS roughness of 1.7 nm for 10–12 nm thick films and 2.5 nm for 30 nm thick films. Raman spectroscopy studies revealed that the deposition process caused compressive biaxial strain in graphene, whereas no extra defects were generated. An 11 nm thick HfO₂ film deposited onto bilayer graphene reduced the electron mobility by less than 10% at the Dirac point and by 30–40% far away from it.     

Structural study of TiO2 thin films by micro-Raman spectroscopy

The Raman spectroscopy method was used for structural characterization of TiO₂ thin films prepared by atomic layer deposition (ALD) and pulsed laser deposition (PLD) on fused silica and single-crystal silicon and sapphire substrates. Using ALD, anatase thin films were grown on silica and silicon substrates at temperatures 125–425 °C. At higher deposition temperatures, mixed anatase and rutile phases grew on these substrates. Post-growth annealing resulted in anatase-to-rutile phase transitions at 750 °C in the case of pure anatase films. The films that contained chlorine residues and were amorphous in their as-grown stage transformed into anatase phase at 400 °C and retained this phase even after annealing at 900 °C. On single crystal sapphire substrates, phase-pure rutile films were obtained by ALD at 425 °C and higher temperatures without additional annealing. Thin films that predominantly contained brookite phase were grown by PLD on silica substrates using rutile as a starting material.     

Atomic layer deposition of Cr2O3 thin films: Effect of crystallization on growth and properties

Atomic layer deposition of Cr₂O₃ thin films from CrO₂Cl₂ and CH₃OH on amorphous SiO₂ and crystalline Si(1 0 0) and -Al₂O₃() substrates was investigated, and properties of the films were ascertained. Self-limited growth with a rate of 0.05–0.1 nm/cycle was obtained at substrate temperatures of 330–420 °C. In this temperature range epitaxial eskolaite was formed on the -Al₂O₃() substrates. The predominant crystallographic orientation in the epitaxial films depended, however, on the growth temperature and film thickness. Sufficiently thick films grown on the SiO₂ and Si(1 0 0) substrates contained also the eskolaite phase, but thinner films deposited at 330–375 °C on these substrates were amorphous. The growth rate data of films with different phase composition allowed a conclusion that the crystalline phase grew markedly faster than the amorphous phase did. The amorphous, polycrystalline and epitaxial films had densities of 4.9, 5.1 and 5.1–5.3 g/cm³, respectively.     

Preference Programming with incomplete ordinal information

This paper extends possibilities for analyzing incomplete ordinal information about the parameters of an additive value function. Such information is modeled through preference statements which associate sets of alternatives or attributes with corresponding sets of rankings. These preference statements can be particularly helpful in developing a joint preference representation for a group of decision-makers who may find difficulties in agreeing on numerical parameter values. Because these statements can lead to a non-convex set of feasible parameters, a mixed integer linear formulation is developed to establish a linear model for the computation of decision recommendations. This makes it possible to complete incomplete ordinal information with other forms of incomplete information.