Extraction equilibria in the system GaCl3-AlCl3-HCl-H2O-tributyl phosphate

Partition equilibria and solution chemistry of the system GaCl₃-AlCl₃-HCl-H₂O-tributyl phosphate is characterized by a simultaneous extraction of gallium chloride, hydrochloric acid, and water by a solvating mechanism. The salting-out power of the aqueous phase was explained by taking into account the stability of aluminum chloride and gallium chloride complex species and the calculated concentration of free chloride ions actually available for the extraction of gallium. Three gallium extraction mechanisms in the range of compositions studied are the extraction of GaCl₃ at low H⁺ and salt concentrations, the extraction of GaCl^- ₄ at moderate H⁺ and salt concentrations, and the competition between the extraction of GaCL^-4 and an HC1-TBP complex at high H+ and salt concentrations. The extraction of gallium over a wide range of distribution ratios (D = 1 to 1 x 10⁴) could be represented by a chemically based model taking into account the free chloride concentration and the activity coefficient of the total chloride ions. Formerly Visiting Scientist, Ames Laboratory, USDOE     

An Efficient Heuristic Approach to Recognize the Infeasibility of a Loading Problem

The success of hierarchical production planning approaches for flexible manufacturing systems lies in the consistency of decision outcomes at various decision levels. For instance, the loading problem, which is solved at a lower level, may not yield a feasible loading solution to a set of part types selected at a higher level. This paper attemps to address the issue of recognizing the infeasibility of a loading solution. We present a modified loading model that includes a penalty for each operation not assigned to any machine. We develop a Lagrangian-based heuristic procedure and provide a sufficient condition on the quality of heuristic solutions that, if satisfied, will enable us to use the heuristic solutions to recognize the infeasibility of a loading problem. The proposed model and the dual-based heuristic can be effectively incorporated in an FMS hierarchical production planning approach that finds a good loading solution by iteratively comparing different part grouping scenarios.     

Gate delay variability estimation method for parametric yield improvement in nanometer CMOS technology

In digital CMOS circuits, parametric yield improvement may be achieved by reducing the variability of performance and power consumption of individual cell instances. Such improvement of variation robustness can be attained by evaluating parameter variation impact at gate level. Statistical characterization of logic gates are usually obtained by computationally expensive electrical simulations. An efficient gate delay variability estimation method is proposed for variability-aware design. The proposed method has been applied to different topologies (transistor network arrangements) and CMOS gates, and it has been compared to Monte Carlo simulations for data validation, resulting in computation time savings.     

Soft‐Lithographed Up‐Converted Distributed Feedback Visible Lasers Based on CdSe–CdZnS–ZnS Quantum Dots

The development of a solution‐deposited up‐converted distributed feedback laser prototype is presented. It employs a sol–gel silica/germania soft‐lithographed microcavity and CdSe–CdZnS–ZnS quantum dot/sol–gel zirconia composites as optical gain material. Characterization of the linear and nonlinear optical properties of quantum dots establishes their high absorption cross‐sections in the one‐ and two‐ photon absorption regimes to be 1 × 10^?14 cm² and 5 × 10⁴ GM, respectively. In addition, ultrafast transient absorption dynamics measurements of the graded seal quantum dots reveal that the Auger recombination lifetime is 220 ps, a value two times higher than that of the corresponding CdSe core. These factors enable the use of such quantum dots as optically pumped gain media, operating in the one‐ and two‐photon absorption regime. The incorporation of CdSe–CdZnS–ZnS quantum dots within a zirconia host matrix affords a quantum‐dot ink that can be directly deposited on our soft‐lithographed distributed feedback grating to form an all‐solution‐processed microcavity laser.     

Hybrid integral transforms analysis of the bioheat equation with variable properties

Pennes’ equation is the most frequently employed model to describe heat transfer processes within living tissues, with numerous applications in clinical diagnostics and thermal treatments. A number of analytical solutions were provided in the literature that represent the temperature distribution across tissue structures, but considering simplifying assumptions such as uniform and linear thermophysical properties and blood perfusion rates. The present work thus advances such analysis path by considering a heterogeneous medium formulation that allows for spatially variable parameters across the tissue thickness. Besides, the eventual variation of blood perfusion rates with temperature is also accounted for in the proposed model. The Generalized Integral Transform Technique (GITT) is employed to yield a hybrid numerical–analytical solution of the bioheat model in heterogeneous media, which reduces to the exact solution obtained via the Classical Integral Transform Method for a linear formulation with uniform coefficients. The open source UNIT code (“UNified Integral Transforms”) is utilized to obtain numerical results for a set of typical values of the governing parameters, in order to illustrate the convergence behavior of the proposed eigenfunction expansions and inspect the importance of accounting for spatially variable properties in predicting the thermal response of living tissues to external stimulus.     

Using roadmaps to classify regions of space for autonomous robot navigation

The roadmap approach to robot path planning is one of the earliest methods. Since then, many different algorithms for building roadmaps have been proposed and widely implemented in mobile robots but their use has always been limited to planning in static, totally known environments. In this paper we combine the use of dynamic analogical representations of the environment with an efficient roadmap extraction method, to guide the robot navigation and to classify the different regions of space in which the robot moves. The paper presents the general reference architecture for the robotic system and then focuses on the algorithms for the construction of the roadmap, the classification of the regions of space and their use in robot navigation. Experimental results indicate the applicability and robustness of this approach in real situations.     

A co-evolutionary differential evolution algorithm for solving min–max optimization problems implemented on GPU using C-CUDA

Several areas of knowledge are being benefited with the reduction of the computing time by using the technology of graphics processing units (GPU) and the compute unified device architecture (CUDA) platform. In case of evolutionary algorithms, which are inherently parallel, this technology may be advantageous for running experiments demanding high computing time. In this paper, we provide an implementation of a co-evolutionary differential evolution (DE) algorithm in C-CUDA for solving min–max problems. The algorithm was tested on a suite of well-known benchmark optimization problems and the computing time has been compared with the same algorithm implemented in C. Results demonstrate that the computing time can significantly be reduced and scalability is improved using C-CUDA. As far as we know, this is the first implementation of a co-evolutionary DE algorithm in C-CUDA.