Influence of the film thickness and additional elements (Al,O, and N) on the properties of FeCo film structures

The magnetic properties and domain structure of FeCoAlON thin films with thicknesses varying from 55 to 550 nm have been studied, and conditions favoring preparation of FeCoAlON films with uniaxial anisotropy in the direction normal to the film plane, which is required for designing “perpendicular” super-high-density information recording, have been established. In FeCoAlON films with a thickness up to 300 nm, the domain structure consists of cross-linked domain walls, because strong demagnetizing field suppresses formation of stripe domains. After the film thickness has reached 320 nm, cross-linked domain walls transform into stripe domains, with uniaxial anisotropy in the film plane disappearing, to become replaced by uniaxial anisotropy in the direction normal to the film plane, which can be assigned to magnetoelastic stresses induced by nitrogen atoms filling up interstitial space in the (110) plane. A further increase in the film thickness (up to 550 nm) leads to a rotational anisotropy due to the increase of nitrogen concentration in interstitials and the increase of magnetoelastic stresses.     

Worst-case robust decisions for multi-period mean–variance portfolio optimization

In this paper, we extend the multi-period mean–variance optimization framework to worst-case design with multiple rival return and risk scenarios. Our approach involves a min–max algorithm and a multi-period mean–variance optimization framework for the stochastic aspects of the scenario tree. Multi-period portfolio optimization entails the construction of a scenario tree representing a discretised estimate of uncertainties and associated probabilities in future stages. The expected value of the portfolio return is maximized simultaneously with the minimization of its variance. There are two sources of further uncertainty that might require a strengthening of the robustness of the decision. The first is that some rival uncertainty scenarios may be too critical to consider in terms of probabilities. The second is that the return variance estimate is usually inaccurate and there are different rival estimates, or scenarios. In either case, the best decision has the additional property that, in terms of risk and return, performance is guaranteed in view of all the rival scenarios. The ex-ante performance of min–max models is tested using historical data and backtesting results are presented.     

Global optimization of robust chance constrained problems

We propose a stochastic algorithm for the global optimization of chance constrained problems. We assume that the probability measure with which the constraints are evaluated is known only through its moments. The algorithm proceeds in two phases. In the first phase the probability distribution is (coarsely) discretized and solved to global optimality using a stochastic algorithm. We only assume that the stochastic algorithm exhibits a weak* convergence to a probability measure assigning all its mass to the discretized problem. A diffusion process is derived that has this convergence property. In the second phase, the discretization is improved by solving another nonlinear programming problem. It is shown that the algorithm converges to the solution of the original problem. We discuss the numerical performance of the algorithm and its application to process design.     

Control of initiation, rate, and routing of spontaneous capillary-driven flow of liquid droplets through microfluidic channels on SlipChip

This Article describes the use of capillary pressure to initiate and control the rate of spontaneous liquid-liquid flow through microfluidic channels. In contrast to flow driven by external pressure, flow driven by capillary pressure is dominated by interfacial phenomena and is exquisitely sensitive to the chemical composition and geometry of the fluids and channels. A stepwise change in capillary force was initiated on a hydrophobic SlipChip by slipping a shallow channel containing an aqueous droplet into contact with a slightly deeper channel filled with immiscible oil. This action induced spontaneous flow of the droplet into the deeper channel. A model predicting the rate of spontaneous flow was developed on the basis of the balance of net capillary force with viscous flow resistance, using as inputs the liquid-liquid surface tension, the advancing and receding contact angles at the three-phase aqueous-oil-surface contact line, and the geometry of the devices. The impact of contact angle hysteresis, the presence or absence of a lubricating oil layer, and adsorption of surface-active compounds at liquid-liquid or liquid-solid interfaces were quantified. Two regimes of flow spanning a 10(4)-fold range of flow rates were obtained and modeled quantitatively, with faster (mm/s) flow obtained when oil could escape through connected channels as it was displaced by flowing aqueous solution, and slower (micrometer/s) flow obtained when oil escape was mostly restricted to a micrometer-scale gap between the plates of the SlipChip ("dead-end flow"). Rupture of the lubricating oil layer (reminiscent of a Cassie-Wenzel transition) was proposed as a cause of discrepancy between the model and the experiment. Both dilute salt solutions and complex biological solutions such as human blood plasma could be flowed using this approach. We anticipate that flow driven by capillary pressure will be useful for the design and operation of flow in microfluidic applications that do not require external power, valves, or pumps, including on SlipChip and other droplet- or plug-based microfluidic devices. In addition, this approach may be used as a sensitive method of evaluating interfacial tension, contact angles, and wetting phenomena on chip.     

Worst-case robust Omega ratio

The Omega ratio is a recent performance measure proposed to overcome the known shortcomings of the Sharpe ratio. Until recently, the Omega ratio was thought to be computationally intractable, and research was focused on heuristic optimization procedures. We have shown elsewhere that the Omega ratio optimization is equivalent to a linear program and hence can be solved exactly in polynomial time. This permits the investigation of more complex and realistic variants of the problem. The standard formulation of the Omega ratio requires perfect information for the probability distribution of the asset returns. In this paper, we investigate the problem arising from the probability distribution of the asset returns being only partially known. We introduce the robust variant of the conventional Omega ratio that hedges against uncertainty in the probability distribution. We examine the worst-case Omega ratio optimization problem under three types of uncertainty – mixture distribution, box and ellipsoidal uncertainty – and show that the problem remains tractable.     

Cloud point extraction of lanthanide(III) ions via use of Triton X-100 without and with water-soluble calixarenes as added chelating agents

The use of water-soluble calixarenes: p-sulfonato thiacalixarene (ST), tetra-sulfonatomethylated calix[4]resorcinarene (SR), calix[4]resorcinarene phosphonic acid (PhR) as chelating agents in cloud point extraction (CPE) of La(III), Gd(III) and Yb(III) ions using Triton X-100 as non-ionic surfactant is introduced. The data obtained indicate that both complexation ability and structure of calixarenes govern the extraction efficiency of lanthanides. In particular ST and SR, forming 1:1 lanthanide complexes with similar stability in aqueous media, exhibit different extractability when used as chelating agents in CPE. First synthesized PhR was found to be the most efficient chelating agent exhibiting pH-dependent selectivity within La(III), Gd(III) and Yb(III) in CPE.     

Two-step and three-step Q-superlinear convergence of SQP methods

This paper investigates the convergence rates of the variable-multiplier pair (x, ) in sequential quadratic programming methods for equality constrained optimization. The two main results of the paper are that the Q-superlinear convergence of {x _k } implies two-step Q-superlinear convergence for {(x _k , _k )} and that the two-step Q-superlinear convergence of {x _k } implies three-step Q-superlinear convergence for {(x _k , _k )}.The author is indebted to Professor Richard Tapia for many helpful comments and suggestions on the paper. The comments by Professors A. R. Conn and N. I. M. Gould on an earlier version are also acknowledged. This research was funded by SERC and ESRC research contracts.