Growth of low-density InAs/GaAs quantum dots on a substrate with an intentional temperature gradient by molecular beam epitaxy

InAs was deposited by molecular beam epitaxy (MBE) on a GaAs substrate with an intentional temperature gradient from centre to edge. Two-dimensional (2D) to three-dimensional (3D) morphology evolution was found along the direction in which the substrate temperature was decreasing. Quantum dots (QDs) with density as low as similar to 8 x 10(6) cm(-2) were formed in some regions. We attribute the morphological evolution to the temperature-dependent desorption of deposited indium and the intermixing between deposited indium and gallium from the buffer.

Investigation on a pressure-gradient fiber laser hydrophone

In this paper, a pressure-gradient fiber laser hydrophone is demonstrated. Two brass diaphragms are installed at the end of a metal cylinder as sensing elements. A distributed feedback fiber laser, fixed at the center of the two diaphragms, is elongated or shortened due to the acoustic wave. There are two orifices at the middle of the cylinder. So this structure can work as a pressure-gradient microphone in the acoustic field. Furthermore, the hydrostatic pressure is self-compensated and an ultra-thin dimension is achieved. Theoretical analysis is given based on the electro-acoustic theory. Field trials are carried out to test the performance of the hydrophone. A sensitivity of 100 nm MPa-1 has been achieved. Due to the small dimensions, no directivity is found in the test.

Investigation of Interfacial Tensions for Carbon Dioxide Aqueous Solutions by Perturbed-Chain Statistical Associating Fluid Theory Combined with Density-Gradient Theory

The perturbed-chain statistical associating fluid theory and density-gradient theory are used to construct an equation of state (EOS) applicable for the phase behaviors of carbon dioxide aqueous solutions. With the molecular parameters and influence parameters respectively regressed from bulk properties and surface tensions of pure fluids as input, both the bulk and interfacial properties of carbon dioxide aqueous solutions are satisfactorily correlated by adjusting the binary interaction parameter (k(ij)). Our results show that the constructed EOS is able to describe the interfacial properties of carbon dioxide aqueous solutions in a wide temperature range, and illustrate the influences of temperature, pressure, and densities in each phase on the interfacial properties.

Phase reconstruction from three interferograms based on integral of phase gradient

A novel algorithm of phase reconstruction based on the integral of phase gradient is presented. The algorithm directly derives two real-valued partial derivatives from three phase-shifted interferograms. Through integrating the phase derivatives, the desired phase is reconstructed. During the phase reconstruction process, there is no need for an extra rewrapping manipulation to ensure values of the phase derivatives lie in the interval [-pi, pi] as before, thus this algorithm can prevent error or distortion brought about by the phase unwrapping operation. Additionally, this algorithm is fast and easy to implement, and insensitive to the nonuniformity of the intensity distribution of the interferogram. The feasibility of the algorithm is demonstrated by both computer simulation and experiment.

Density Gradient Ultracentrifugation of Nanotubes: Interplay of Bundling and Surfactants Encapsulation

Density gradient ultracentrifugation (DGU) has emerged as a promising tool to prepare chirality enriched nanotube samples. Here, we assess the performance of different surfactants for DGU. Bile salts (e.g., sodium cholate (SC), sodium deoxycholate (SDC), and sodium taurodeoxycholate (TDC)) are more effective in individualizing Single Wall Carbon Nanotubes (SWNTs) compared to linear chain surfactants (e.g., sodium dodecylbenzene sulfonate (SDBS) and sodium dodecylsulfate (SDS)) and better suited for DGU. Using SC, a narrower diameter distribution (0.69-0.81 nm) is achieved through a single DGU step on CoMoCAT tubes, when compared to SDC and TDC (0.69-0.89 nm). No selectivity is obtained using SDBS. due to its ineffectiveness in debundling. We assign the reduce selectivity of dihydroxy bile salts (S DC and TDC) in comparison with trihydroxy SC to the formation of secondary micelles. This is determined by the number and position of hydroxyl ( OH) groups on the a-side of the steroid backbone. We also enrich CoMoCAT SWNT in the 0.84-0.92 nm range using the Pluronic F98 triblock copolymer. Mixtures of bile salts (SC) and linear chain surfactants (SOS) are used to enrich metallic and semiconducting laser-ablation grown SWNTs. We demonstrate enrichment of a single chirality, (6,5), combining diameter and metallic versus semiconductillg separation on CoMoCAT samples.

Strain gradient theory based on a new framework of non-local model

A new framework of non-local model for the strain energy density is proposed in this paper. The global strain energy density of the representative volume element is treated as a non-local variable and can be obtained through a special integral of the local strain energy density. The local strain energy density is assumed to be dependent on both the strain and the rotation-gradient. As a result of the non-local model, a new strain gradient theory is derived directly, in which the first and second strain gradients, as well as the triadic and tetradic stress, are introduced in the context of work conjugate. For power law hardening materials, size effects in thin metallic wire torsion and ultra-thin cantilever beam bend are investigated. It is found that the result predicted by the theoretical model is well consistent with the experimental data for the thin wire torsion. On the other hand, the calculation result for the micro-cantilever beam bend clearly shows the size effect.

delta C-13 variation of C-3 and C-4 plants across an Asian monsoon rainfall gradient in arid northwestern China

IEECAS SKLLQG

Repeatedly usable immobilized pH gradient in a monolithic capillary column

Glycidyl methacrylate (GMA) and ethylene dimethacrylate (EDMA) were used to synthesize a monolithic capillary column containing reactive epoxy groups. Glutaraldehyde was introduced and linked to the monolith after a process of amination. An aqueous solution of commercial carrier ampholytes (CAs, Ampholine) was focused in such a polymer column. The primary amino groups of CAs reacted with glutaraldehyde along the capillary. CAs were immobilized at different positions in the column according to their isoelectric points (pl), resulting in a monolithic immobilized pH gradient (M-IPG). Isoelectric focusing (IEF) was performed without CAs in such an M-IPG column. Due to the covalent attachment of the CAs this M-IPG can be repeatedly used after its preparation. Good stability, linearity, and reproducibility were obtained.

New uniform algorithm to predict reversed phase retention values under different gradient conditions

A new numerical emulation algorithm was established to calculate retention parameters in RP-HPLC with several retention times under different linear or nonlinear binary gradient elution conditions and further predict the retention time under any other binary gradient conditions. A program was written according to this algorithm and nine solutes were used to test the program. The prediction results were excellent. The maximum relative error of predicted retention time was less than 0.45%. (C) 2002 Elsevier Science B.V. All rights reserved.

Retention modeling and simultaneous optimization of pH value and gradient steepness in RP-HPLC using feed-forward neural networks

A novel approach is proposed for the simultaneous optimization of mobile phase pH and gradient steepness in RP-HPLC using artificial neural networks. By presetting the initial and final concentration of the organic solvent, a limited number of experiments with different gradient time and pH value of mobile phase are arranged in the two-dimensional space of mobile phase parameters. The retention behavior of each solute is modeled using an individual artificial neural network. An "early stopping" strategy is adopted to ensure the predicting capability of neural networks. The trained neural networks can be used to predict the retention time of solutes under arbitrary mobile phase conditions in the optimization region. Finally, the optimal separation conditions can be found according to a global resolution function. The effectiveness of this method is validated by optimization of separation conditions for amino acids derivatised by a new fluorescent reagent.