Unambiguous atomic structural determination of single-walled carbon nanotubes by electron diffraction

We introduce a novel non-dimensional “intrinsic layer-line spacing” concept for electron diffraction analysis of single-walled carbon nanotubes (SWCNTs). Accordingly, we develop a unique method for direct determination of chiral indices (n, m) of the carbon nanotubes from their electron diffraction patterns (EDPs). The new method is totally calibration-free. Errors due to the nanotube inclination are specified. The tilt angle of the carbon nanotube with respect to the incident electron beam is simultaneously evaluated, thus the effect of the tube tilting is compensated for in the (n, m) determination. Several effective procedures are proposed to cross-check the results by using abundant information contained in the diffraction patterns. The efficiency of the method is demonstrated on both simulated and experimental diffraction patterns from single-walled nanotubes. The technique can be extended to structural analysis of nanotubes of structure similar to carbon nanotubes, such as boron nitride nanotubes.     

Dense subgraph maintenance under streaming edge weight updates for real-time story identification

Recent years have witnessed an unprecedented proliferation of social media. People around the globe author, everyday, millions of blog posts, social network status updates, etc. This rich stream of information can be used to identify, on an ongoing basis, emerging stories, and events that capture popular attention. Stories can be identified via groups of tightly coupled real-world entities, namely the people, locations, products, etc, that are involved in the story. The sheer scale and rapid evolution of the data involved necessitate highly efficient techniques for identifying important stories at every point of time. The main challenge in real-time story identification is the maintenance of dense subgraphs (corresponding to groups of tightly coupled entities) under streaming edge weight updates (resulting from a stream of user-generated content). This is the first work to study the efficient maintenance of dense subgraphs under such streaming edge weight updates. For a wide range of definitions of density, we derive theoretical results regarding the magnitude of change that a single edge weight update can cause. Based on these, we propose a novel algorithm, DynDens, which outperforms adaptations of existing techniques to this setting and yields meaningful, intuitive results. Our approach is validated by a thorough experimental evaluation on large-scale real and synthetic datasets.     

Solvent free liquid phase oxidation of benzyl alcohol using Au supported catalysts prepared using a sol immobilization technique

Solvent free oxidation of benzyl alcohol was investigated in the absence of a base using Au catalysts prepared by sol immobilization on titania and carbon supports. Comparison between the Au supported catalysts revealed that activity and distribution of products was dependent on the nature of support and heat treatment. Specifically, heat pre-treatment of the Au catalysts has a beneficial effect in terms of activity, but is detrimental in terms of selectivity to the benzaldehyde. We conclude that sol immobilization is a suitable technique for preparing gold catalysts with small particle size and narrow particle size distributions and very high activity and selectivity for benzyl alcohol oxidation.     

Direct synthesis of hydrogen peroxide from H2 and O2 using zeolite-supported Au catalysts

The direct synthesis of hydrogen peroxide from H₂ and O₂ using zeolite-supported Au catalysts is described and their activity is contrasted with silica- and alumina-supported Au catalysts. Two zeolites were investigated, ZSM-5 and zeolite Y. The effect of calcination of these catalysts is studied and it is found that for uncalcined catalysts high rates of hydrogen peroxide formation are observed, but these catalysts are unstable and lose Au during use. Consequently, reuse of these catalysts leads to lower rates of hydrogen peroxide formation. However, catalysts calcined at 400 °C are more stable and can be reused without loss of gold. The use of zeolites as a support for Au gives comparable rates of hydrogen peroxide formation to alumina-supported Au catalysts and higher rates when compared with silica-supported catalysts. prepared using a similar method. Zeolite Y-supported catalysts are more active than ZSM-5-supported catalysts for the stable calcined materials. It is considered that the overall activity of these supported catalysts may be related to the aluminium content as the activity increases with increasing aluminium content.     

Development of a virtual reality laboratory stressor

Virtual Reality - This research report describes the development of a virtual reality (VR) laboratory stressor to study the effects of exposure to stressful events. The aim of the research was to...     

High-throughput drilling of titanium alloys

Experiments of high-throughput drilling of Ti–6Al–4V at 183 m/min cutting speed and 156 mm³/s material removal rate (MRR) using a 4 mm diameter WC–Co spiral point drill were conducted. The tool material and geometry and drilling process parameters, including cutting speed, feed, and fluid supply, were studied to evaluate the effect on drill life, thrust force, torque, energy, and burr formation. The tool wear mechanism, hole surface roughness, and chip light emission and morphology for high-throughput drilling were investigated. Supplying the cutting fluid via through-the-drill holes has proven to be a critical factor for drill life, which can be increased by 10 times compared to that of dry drilling at 183 m/min cutting speed and 0.051 mm/rev feed. Under the same MRR of 156 mm³/s with a doubled feed of 0.102 mm/rev (91 m/min cutting speed), over 200 holes can be drilled. The balance of cutting speed and feed is essential to achieve long drill life and good hole surface roughness. This study demonstrates that, using proper drilling process parameters, spiral point drill geometry, and fine-grained WC–Co tool material, the high-throughput drilling of Ti alloy is technically feasible.     

A fuzzy expert system for the design of machining operations

In this paper, a fuzzy expert system called Smart Assistant to Machinist, or SAM, is introduced. The system consists of four modules: a database, a cutter selection module, a cutting condition design module and a learning module. The database consists of four data files: work material data file, machine tool data file, machining plan data file (which defines desirable material removal rate, surface finish, cutting speed, feed, depth of cut, etc.) and cutter data file. The cutter selection module is developed based on fuzzy logic, in which the cutter selection is conducted in three steps. First, the input information is “fuzzyized” Next, using the fuzzy correlation functions, cutter grades and cutters are selected. Then, the selected grades and cutters are searched against the cutter data file to check the availability. The cutting condition design module is developed based on fuzzy non-linear programming and user interactive graphics. The learning module is developed so that users can fine-tune the fuzzy functions to further improve the performance of the system. The system has two distinct features: (1) it can select cutters and design cutting conditions based on partial and imprecise information, and (2) it selects commercial cutter products used on shop floors. The use of the system is demonstrated using two examples.     

Speeding up the spatial adiabatic passage of matter waves in optical microtraps by optimal control

We numerically investigate the performance of atomic transport in optical microtraps via the so called spatial adiabatic passage technique. Our analysis is carried out by means of optimal control methods, which enable us to determine suitable transport control pulses. We investigate the ultimate limits of the optimal control in speeding up the transport process in a triple well configuration for both a single atomic wave packet and a Bose-Einstein condensate within a regime of experimental parameters achievable with current optical technology.     

Inferring (Biological) Signal Transduction Networks via Transitive Reductions of Directed Graphs

In this paper we consider the p-ary transitive reduction (TR _p ) problem where p>0 is an integer; for p=2 this problem arises in inferring a sparsest possible (biological) signal transduction network consistent with a set of experimental observations with a goal to minimize false positive inferences even if risking false negatives. Special cases of TR _p have been investigated before in different contexts; the best previous results are as follows: