Self-assembled InAs/GaAs quantum dots and quantum dot laser

Systematic study of molecular beam epitaxy-grown self-assembled In(Ga)As/GaAs, In-AlAs/AlGaAs/GaAs, and InAs/InAlAs/InP quantum dots (QDs) is demonstrated. By adjusting growth conditions, surprising alignment, preferential elongation, and pronounced sequential coalescence of dots under the specific condition are realized. Room-temperature (RT) continuous-wave (CW) lasing at the wavelength of 960 nm with output power of 1 W is achieved from vertical coupled InAs/GaAs QDs ensemble. The RT threshold current density is 218 A/cm(2). An RT CW output power of 0.53 W ensures at least 3 000 h lasing (only drops 0.83 db). This is one of the best results ever reported.

Ordering of Ge islands on Si(001) substrates patterned by nanoindentation

Spatial organization of Ge islands, grown by physical vapor deposition, on prepatterned Si(001) substrates has been investigated. The substrates were patterned prior to Ge deposition by nanoindentation. Characterization of Ge dots is performed by atomic force microscopy and scanning electron microscopy. The nanoindents act as trapping sites, allowing ripening of Ge islands at those locations during subsequent deposition and diffusion of Ge on the surface. The results show that island ordering is intrinsically linked to the nucleation and growth at indented sites and it strongly depends on pattern parameters.

Towards a controlled growth of self-assembled nanostructures: shaping, ordering and localization in Ge/Si heteroepitaxy.

The strain-induced self-assembly of suitable semiconductor pairs is an attractive natural route to nanofabrication. To bring to fruition their full potential for actual applications, individual nanostructures need to be combined into ordered patterns in which the location of each single unit is coupled with others and the surrounding environment. Within the Ge/Si model system, we analyze a number of examples of bottom-up strategies in which the shape, positioning, and actual growth mode of epitaxial nanostructures are tailored by manipulating the intrinsic physical processes of heteroepitaxy. The possibility of controlling elastic interactions and, hence, the configuration of self-assembled quantum dots by modulating surface orientation with the miscut angle is discussed. We focus on the use of atomic steps and step bunching as natural templates for nanodot clustering. Then, we consider several different patterning techniques which allow one to harness the natural self-organization dynamics of the system, such as: scanning tunneling nanolithography, focused ion beam and nanoindentation patterning. By analyzing the evolution of the dot assembly by scanning probe microscopy, we follow the pathway which leads to lateral ordering, discussing the thermodynamic and kinetic effects involved in selective nucleation on patterned substrates.

Driving Ge island ordering on nanostructured Si surfaces

Semiconductor epitaxial nanostructures have been recently proposed as the key building blocks of many innovative applications in materials science and technology. To bring their tremendous potential to fruition, a fine control of nanostructure size and placement is necessary. We present a detailed investigation of the self-ordering process in the prototype case of Ge/Si heteroepitaxy. Starting from a bottom-up strategy (step-bunching instabilities), our analysis moves to lithographic techniques (scanning tunneling lithography, nanomechanical stamping, focused ion beam patterning) with the aim of developing a hybrid approach in which the exogenous intervention is specifically designed to suit and harness the natural self-organization dynamics of the system.

Tension between privacy and justice : ordering medical tests

Courts set guidelines for when genetic testing would be ordered - medical testing - life insurers - use of test results - confidentiality.

A quantification of the interaction and spatial ordering in nano-arrays

This paper reports on the use of a local order measure to quantify the spatial ordering of a quantum dot array (QDA). By means of electron ground state energy analysis in a quantum dot pair, it is demonstrated that the length scale required for such a measure to characterize the opto-electronic properties of a QDA is of the order of a few QD radii. Therefore, as local order is the primary factor that affects the opto-electronic properties of an array of quantum dots of homogeneous size, this order was quantified through using the standard deviation of the nearest neighbor distances of the quantum dot ensemble. The local order measure is successfully applied to quantify spatial order in a range of experimentally synthesized and numerically generated arrays of nanoparticles. This measure is not limited to QDAs and has wide ranging applications in characterizing order in dense arrays of nanostructures.

A queuing approach for inventory planning with batch ordering in multi-echelon supply chains

This paper presents stylized models for conducting performance analysis of the manufacturing supply chain network (SCN) in a stochastic setting for batch ordering. We use queueing models to capture the behavior of SCN. The analysis is clubbed with an inventory optimization model, which can be used for designing inventory policies . In the first case, we model one manufacturer with one warehouse, which supplies to various retailers. We determine the optimal inventory level at the warehouse that minimizes total expected cost of carrying inventory, back order cost associated with serving orders in the backlog queue, and ordering cost. In the second model we impose service level constraint in terms of fill rate (probability an order is filled from stock at warehouse), assuming that customers do not balk from the system. We present several numerical examples to illustrate the model and to illustrate its various features. In the third case, we extend the model to a three-echelon inventory model which explicitly considers the logistics process.

Ordering transformation in icosahedral quasicrystals and related crystalline phases

Arcs of diffuse intensity appear in various shapes and positions in the diffraction patterns from the icosahedral phase, violating the parity rule for simple icosahedral (SI) symmetry. In the process of annealing treatment, the diffuse spots also evolve in the centre of the arcs and become sharp. These extra diffuse spots change the symmetry of the quasilattice from P-type to F-type. The ordered and disordered structures in quasicrystal have been linked to the ordered and disordered structures present in the crystalline alpha (Al-Mn-Si) and alpha (Al-Fe-Si) alloys.

Supramolecular ordering in oligothiophene−fullerene monolayers

Scanning tunneling microscopy (STM) of monolayers comprising oligothiophene and fullerene molecular semiconductors reveals details of their molecular-scale phase separation and ordering with potential implications for the design of organic electronic devices, in particular future bulk heterojunction solar cells. Prochiral terthienobenzenetricarboxylic acid (TTBTA) self-assembles at the solution/graphite interface into either a porous chicken wire network linked by dimeric hydrogen bonding associations of COOH groups (R22(8)) or a close-packed network linked in a novel hexameric hydrogen bonding motif (R66(24)). Analysis of high-resolution STM images shows that the chicken wire phase is racemically mixed, whereas the close-packed phase is enantiomerically pure. The cavities of the chicken wire structure can efficiently host C60 molecules, which form ordered domains with either one, two, or three fullerenes per cavity. The observed monodisperse filling and long-range co-alignment of fullerenes is described in terms of a combination of an electrostatic effect and the commensurability between the graphite and molecular network, which leads to differentiation of otherwise identical adsorption sites in the pores.

Minimizing overprocessing waste in business processes via predictive activity ordering

Overprocessing waste occurs in a business process when effort is spent in a way that does not add value to the customer nor to the business. Previous studies have identied a recurrent overprocessing pattern in business processes with so-called "knockout checks", meaning activities that classify a case into "accepted" or "rejected", such that if the case is accepted it proceeds forward, while if rejected, it is cancelled and all work performed in the case is considered unnecessary. Thus, when a knockout check rejects a case, the effort spent in other (previous) checks becomes overprocessing waste. Traditional process redesign methods propose to order knockout checks according to their mean effort and rejection rate. This paper presents a more fine-grained approach where knockout checks are ordered at runtime based on predictive machine learning models. Experiments on two real-life processes show that this predictive approach outperforms traditional methods while incurring minimal runtime overhead.

Dipole ordering in dilute solutions of ferroelectrics in antiferroelectric materials

The coefficients of thermal expansion reported by Worlton et al. [6] in the case of zircon are given in Table II along with the present data. Although Oql > or• in both cases, the anisotropy is more marked in the case of DyV04. From Table II, it is clear that the coefficient of volume expansion (,6) is almost the same for both compounds.

On the functional ordering of biomembranes : Implications for drug binding

Cells are packed with membrane structures, defining the inside and outside, and the different subcellular compartments. These membranes consisting mainly of phospholipids have a variety of functions in addition to providing a permeability barrier for various compounds. These functions involve cellular signaling, where lipids can act as second messengers, or direct regulation of membrane associating proteins. The first part of this study focuses on relating some of the physicochemical properties of membrane lipids to the association of drug compounds to membranes. A fluorescence based method is described allowing for determination of the membrane association of drugs. This method was subsequently applied to a novel drug, siramesine, previously shown to have anti-cancer activity. Siramesine was found to associate with anionic lipids. Especially interesting is its strong affinity for a second messenger lipid phosphatidic acid. This is the first example of a small molecule drug compound specifically interacting with a cellular lipid. Phosphatidic acid in cells is required for the activation of many signaling pathways mediating growth and proliferation. This provides an intriguing possibility for a simple molecular mechanism of the observed anti-cancer activity of siramesine. In the second part the thermal behavior and self assembly of charged and uncharged membrane assemblies was studied. Strong inter-lamellar co-operativity was observed for multilamellar DPPC vesicles using fluorescence techniques together with calorimetry. The commonly used membrane models, large unilamellar vesicles (LUV) and multilamellar vesicles (MLV) were found to possess different biophysical properties as interlamellar interactions of MLVs drive segregation of a pyrene labeled lipid analogue into clusters. The effect of a counter-ion lattice on the self assembly of a cationic gemini surfactant was studied. The presence of NaCl strongly influenced the thermal phase behavior of M-1 vesicles, causing formation of giant vesicles upon exceeding a phase transition temperature, followed by a subsequent transition into a more homogenous dispersion. Understanding the underlying biophysical aspects of cellular membranes is of fundamental importance as the complex picture of the structure and function of cells is evolving. Many of the cellular reactions take place on membranes and membranes are known to regulate the activity of many peripheral and intergral membrane associating proteins. From the point of view of drug design and gene technology, membranes can provide an interesting target for future development of drugs, but also a vehicle sensitive for environmental changes allowing for encapsulating drugs and targeting them to the desired site of action.

Ordering within moral orders to manage classroom trouble

This paper demonstrates how classroom trouble warranting teacher intervention can stem from transgressions in different layers of the complex moral order regulating classroom interactions. The paper builds from Durkheim’s treatment of schooling as the institution responsible for the inculcation of a shared moral order, Bernstein’s distinction between the instructional and regulative discourses in any pedagogic setting, and the concept of verticality in the instructional discourse to illuminate how curricular knowledge might apply across different contexts. This paper proposes a similar vertical dimension of moral gravity in the regulative discourse, such that some moral expectations apply across any context, while others are highly contextualized. This paper then applies this frame to data from classroom observations conducted in prevocational pathways for 16 years olds created under Australia’s “earning or learning till 17” policy. This paper describes the variety of moral premises teachers invoked in different teacher/class combinations, according to their level of moral gravity to display the dominant use of highly contextualized moral premises seeking institutional compliance, and minimal use of broader moral frames for these students on the brink of entry to the adult world.

Chemical ordering in As-Se glasses: X-ray absorption edge and XPES studies

X-ray absorption edge and X-ray photoelectron spectroscopic studies of As-Se glasses seem to support a chemical ordering model.