Semiconductors and transistors.

Bibliography: p. 253.

Effects of carbon surface chemistry and solution pH on the adsorption of binary aromatic solutes

Adsorption of p-cresol, nitrobenzene and p-nitrophenol on treated and untreated carbons is investigated systematically. The effects of carbon surface chemistry and solution pH are studied and discussed. All adsorption experiments were carried out in pH-controlled solutions to examine the adsorption properties of the adsorption systems where the solutes are in molecular as well as ionic forms. Using the homogeneous Langmuir equation, the single solute parameters are determined. These parameters are then used to predict the binary solute adsorption isotherms and gain further insights into the adsorption process. (C) 2002 Elsevier Science Ltd. All rights reserved.

Charge-based quantum computing using single donors in semiconductors

Solid-state quantum computer architectures with qubits encoded using single atoms are now feasible given recent advances in the atomic doping of semiconductors. Here we present a charge qubit consisting of two dopant atoms in a semiconductor crystal, one of which is singly ionized. Surface electrodes control the qubit and a radio-frequency single-electron transistor provides fast readout. The calculated single gate times, of order 50 ps or less, are much shorter than the expected decoherence time. We propose universal one- and two-qubit gate operations for this system and discuss prospects for fabrication and scale up.

Permeation of binary gas mixtures in ultramicroporous membranes

High-quality nanometer thick ultramicroporous membranes were prepared from silica sol-gel processes and tested for the permeation of binary gas mixtures of He, H-2, CO2, and CH4 across different temperature and partial pressure regimens. Pore size distribution by molecular probing showed that the majority of pore sizes had dimensions below 2.9 Angstrom. In 50:50 binary mixtures, the fluxes of gases increased as a function of temperature, indicating an activated transport mechanism. The ultramicroporous membranes showed high selectivities at 150 degreesC for He/CO2 (30), He/CH4 (93), H-2/CO2 (10), and H-2/CH4 (9) with lower selectivities for CO2/CH4 (5). High activation energies (E-a) were observed for the permeance of 50:50 binary mixtures containing He and H-2 of 22.1-27.5 and 17.6-23.1 kJ.mol(-1), respectively. The E-a for the permeance of the total mixture approached the E-a for the permeance of the molecule with the smaller kinetic diameter (He or H-2).

A small-molecule lead compound for the treatment of Alzheimer's disease

At autopsy, Alzheimer's disease is characterised by the presence of amyloid plaques and neurofibrillary tangles, made up of two peptide sequences, amyloid-beta(1-40) (A beta 40) and amyloid-beta(1-42) (A beta 42). In Tyrode's solution (2 mM Ca2+), 10 mu M A beta 42 peptide almost immediately aggregates and eventually forms p-sheets. This aggregation can be inhibited with 4,5-dianilinophthalimide (DAPH). Ca2+-permeant AMPA receptors are involved in the neuronal Ca2+ influx (neurotoxicity) induced by the A beta 42 peptide in cultured neuronal cells. The Ca2+ influx observed with pre-incubated A beta 42 peptide was inhibited by DAPH. DAPH also inhibits epidermal growth factor receptor kinase, and this will prevent its development for use in Alzheimer's disease. The potential of DAPH as a small-molecule lead compound for the treatment of Alzheimer's disease next requires the separation of the structural requirements that reverse fibril formation and inhibit epidermal growth factor receptor kinase.

Single patient (n-of-1) trials with binary treatment preference

The use of a fully parametric Bayesian method for analysing single patient trials based on the notion of treatment 'preference' is described. This Bayesian hierarchical modelling approach allows for full parameter uncertainty, use of prior information and the modelling of individual and patient sub-group structures. It provides updated probabilistic results for individual patients, and groups of patients with the same medical condition, as they are sequentially enrolled into individualized trials using the same medication alternatives. Two clinically interpretable criteria for determining a patient's response are detailed and illustrated using data from a previously published paper under two different prior information scenarios. Copyright (C) 2005 John Wiley & Sons, Ltd.

The effect of aluminium content on the mechanical properties and microstructure of die cast binary magnesium-aluminium alloys

This paper investigates the relationship between mechanical properties and microstructure in high pressure die cast binary Mg-Al alloys. As-cast test bars produced using high pressure die casting have been tested in tension in order to determine the properties for castings produced using this technique. It has been shown that increasing aluminium levels results in increases in yield strength and a decrease in ductility for these alloys. Higher aluminium levels also result in a decrease in creep rate at 150 degrees C. It has also been shown that an increase in aluminium levels results in an increase in the volume fraction of eutectic Mg17Al12 in the microstructure.

Dynamic binary translation using run-time feedbacks

Dynamic binary translation is the process of translating, modifying and rewriting executable (binary) code from one machine to another at run-time. This process of low-level re-engineering consists of a reverse engineering phase followed by a forward engineering phase. UQDBT, the University of Queensland Dynamic Binary Translator, is a machine-adaptable translator. Adaptability is provided through the specification of properties of machines and their instruction sets, allowing the support of different pairs of source and target machines. Most binary translators are closely bound to a pair of machines, making analyses and code hard to reuse. Like most virtual machines, UQDBT performs generic optimizations that apply to a variety of machines. Frequently executed code is translated to native code by the use of edge weight instrumentation, which makes UQDBT converge more quickly than systems based on instruction speculation. In this paper, we describe the architecture and run-time feedback optimizations performed by the UQDBT system, and provide results obtained in the x86 and SPARC® platforms.

Modelling predicts positive and negative interactions between three Australian tropical tree species in monoculture and binary mixture

Computer modelling promises to. be an important tool for analysing and predicting interactions between trees within mixed species forest plantations. This study explored the use of an individual-based mechanistic model as a predictive tool for designing mixed species plantations of Australian tropical trees. The 'spatially explicit individually based-forest simulator' (SeXI-FS) modelling system was used to describe the spatial interaction of individual tree crowns within a binary mixed-species experiment. The three-dimensional model was developed and verified with field data from three forest tree species grown in tropical Australia. The model predicted the interactions within monocultures and binary mixtures of Flindersia brayleyana, Eucalyptus pellita and Elaeocarpus grandis, accounting for an average of 42% of the growth variation exhibited by species in different treatments. The model requires only structural dimensions and shade tolerance as species parameters. By modelling interactions in existing tree mixtures, the model predicted both increases and reductions in the growth of mixtures (up to +/- 50% of stem volume at 7 years) compared to monocultures. This modelling approach may be useful for designing mixed tree plantations. (c) 2006 Published by Elsevier B.V.

Simulation of binary mixture adsorption of methane and CO2 at supercritical conditions in carbons

Knowledge of the adsorption behavior of coal-bed gases, mainly under supercritical high-pressure conditions, is important for optimum design of production processes to recover coal-bed methane and to sequester CO2 in coal-beds. Here, we compare the two most rigorous adsorption methods based on the statistical mechanics approach, which are Density Functional Theory (DFT) and Grand Canonical Monte Carlo (GCMC) simulation, for single and binary mixtures of methane and carbon dioxide in slit-shaped pores ranging from around 0.75 to 7.5 nm in width, for pressure up to 300 bar, and temperature range of 308-348 K, as a preliminary study for the CO2 sequestration problem. For single component adsorption, the isotherms generated by DFT, especially for CO2, do not match well with GCMC calculation, and simulation is subsequently pursued here to investigate the binary mixture adsorption. For binary adsorption, upon increase of pressure, the selectivity of carbon dioxide relative to methane in a binary mixture initially increases to a maximum value, and subsequently drops before attaining a constant value at pressures higher than 300 bar. While the selectivity increases with temperature in the initial pressure-sensitive region, the constant high-pressure value is also temperature independent. Optimum selectivity at any temperature is attained at a pressure of 90-100 bar at low bulk mole fraction of CO2, decreasing to approximately 35 bar at high bulk mole fractions. (c) 2005 American Institute of Chemical Engineers.

Testing predictions of macroscopic binary diffusion coefficients using lattice models with site heterogeneity

Quantitatively predicting mass transport rates for chemical mixtures in porous materials is important in applications of materials such as adsorbents, membranes, and catalysts. Because directly assessing mixture transport experimentally is challenging, theoretical models that can predict mixture diffusion coefficients using Only single-component information would have many uses. One such model was proposed by Skoulidas, Sholl, and Krishna (Langmuir, 2003, 19, 7977), and applications of this model to a variety of chemical mixtures in nanoporous materials have yielded promising results. In this paper, the accuracy of this model for predicting mixture diffusion coefficients in materials that exhibit a heterogeneous distribution of local binding energies is examined. To examine this issue, single-component and binary mixture diffusion coefficients are computed using kinetic Monte Carlo for a two-dimensional lattice model over a wide range of lattice occupancies and compositions. The approach suggested by Skoulidas, Sholl, and Krishna is found to be accurate in situations where the spatial distribution of binding site energies is relatively homogeneous, but is considerably less accurate for strongly heterogeneous energy distributions.

Electrophysiological evidence for linear polarization sensitivity in the compound eyes of the stomatopod crustacean Gonodactylus chiragra

Gonodactyloid stomatopod crustaceans possess polarization vision, which enables them to discriminate light of different e-vector angle. Their unusual apposition compound eyes are divided by an equatorial band of six rows of enlarged, structurally modified ommatidia, the mid-band (MB). The rhabdoms of the two most ventral MB rows 5 and 6 are structurally designed for polarization vision. Here we show, with electrophysiological recordings, that the photoreceptors R1-R7 within these two MB rows in Gonodactylus chiragra are highly sensitive to linear polarized light of two orthogonal directions (PS=6.1). They possess a narrow spectral sensitivity peaking at 565 nm. Unexpectedly, photoreceptors within the distal rhabdomal tier of MB row 2 also possess highly sensitive linear polarization receptors, which are in their spectral and polarization characteristics similar to the receptors of MB rows 5 and 6. Photoreceptors R1-R7 within the remainder of the MB exhibit low polarization sensitivity (PS=2.3). Outside the MB, in the two hemispheres, R1-R7 possess medium linear polarization sensitivity (PS=3.8) and a broad spectral sensitivity peaking at around 500 nm, typical for most crustaceans. Throughout the retina the most distally situated UV-sensitive R8 cells are not sensitive to linear polarized light.

Heuristic algorithm for computing reversal distance with multigene families via binary integer programming

Hannenhalli and Pevzner developed the first polynomial-time algorithm for the combinatorial problem of sorting of signed genomic data. Their algorithm solves the minimum number of reversals required for rearranging a genome to another when gene duplication is nonexisting. In this paper, we show how to extend the Hannenhalli-Pevzner approach to genomes with multigene families. We propose a new heuristic algorithm to compute the reversal distance between two genomes with multigene families via the concept of binary integer programming without removing gene duplicates. The experimental results on simulated and real biological data demonstrate that the proposed algorithm is able to find the reversal distance accurately. ©2005 IEEE