A facile template-free approach to metal oxide spheres with well-defined nanopore structures

Nanoporous Al₂O₃ with well-defined pore structure, crystallized framework and spherical morphology has been prepared by a facile template-free approach, which involves the preparation via homogeneous precipitation and subsequent decomposition of spherical basic aluminium sulphate particles. The particle size of the spheres can be tuned by controlling the holding time from the beginning of precipitation, and a proper decomposition temperature is important to get high surface area, high pore volume and well-defined pore structures. By the similar way, nanoporous ZrO₂ and TiO₂ spherical particles can also be prepared. These nanoporous oxides all have moderately high surface area (50–70 m²/g) and well-defined nanopores of around 4–12 nm with very narrow pore size distribution. The frameworks of these oxide spheres consist of many small nanocrystallites, between which the nanopores exist. Compared with the soft and hard template routes, this decomposition strategy of sulphates for nanoporous oxides has the advantages of simplicity and low cost.     

The threshold of nanopore formation in ion-implanted platinum

The method of field-ion microscopy was used to determine the threshold of nanopore formation in ion-implanted platinum. The threshold for ion-implanted platinum corresponds to fluence F = 10₁₇ ions/cm². The size of nanopores is determined: 1?C5 nm (transverse) and 1?C9 nm (lateral, across the target depth). It is found that up to 40% of nanopores are located in the subsurface layer with a thickness of 10 nm. The obtained results can be used for prediction of radiation stability of materials based on fcc metals.     

A network approach to cell formation in cellular manufacturing

Formation of machine cells often results in some intercellular movements between the cells. These movements cause lack of segregation among the cells. This is in conflict with the main objective of group technology which aims at independently operating cells. This paper presents a non-heuristic network approach to form manufacturing cells with minimum intercellular interactions. The machine-part matrix containing machining times is represented as a network which is subsequently partitioned by using a modified Gomory-Hu algorithm to find a minimum intercellular interaction. The modified algorithm improves the computational efficiency.     

A fuzzy clustering approach to manufacturing cell formation

Cell formation, one of the most important problems faced in designing cellular manufacturing systems, is to group parts with similar geometry, function, material and process into part families and the corresponding machines into machine cells. There has been an extensive amount of work in this area and, consequently, numerous analytical approaches have been developed. One common weakness of these conventional approaches is that they implicitly assume that disjoint part families exist in the data; therefore, a part can only belong to one part family. In practice, it is clear that some parts definitely belong to certain part families, whereas there exist parts that may belong to more than one family.

In this study, we propose a fuzzy c-means clustering algorithm to formulate the problem. The fuzzy approach offers a special advantage over conventional clustering. It not only reveals the specific part family that a part belongs to, but also provides the degree of membership of a part associated with each part family. This information would allow users flexibility in determining to which part family a part should be assigned so that the workload balance among machine cells can be taken into consideration. We have also developed a computer program to simplify the implementation and to study the impact of the model's parameters on the clustering results.     

A functional-target approach to synthesis of systems controlling integrated industrial complexes

The necessity and sufficiency of the functional-target approach to the analysis and synthesis of models of control systems of complex integrated industrial complexes (IIC) is substantiated. The general model of IIC is based on formalization of a typical activity of designers of control systems for IIC as a process of purposeful replenishment and modification of a knowledge base. Translated from Izmeritel’naya Tekhnika, No. 7, pp. 19–22, July, 1999.     

A BEM approach to static and dynamic analysis of plates with internal supports

A boundary element approach is developed for the static and dynamic analysis of Kirchhoff's plates of arbitrary shape which, in addition to the boundary supports, are also supported inside the domain on isolated points (columns), lines (walls) or regions (patches). All kinds of boundary conditions are treated. The supports inside the domain of the plate may yield elastically. The method uses the Green's function for the static problem without the internal supports to establish an integral representation for the solution which involves the unknown internal reactions and inertia forces within the integrand of the domain integrals. The Green's function is established numerically using BEM. Subsequently, using an effective Gauss integration for the domain integrals and a BEM technique for line integrals a system of simultaneous, in general, nonlinear algebraic equations is obtained which is solved numerically. Several examples for both the static and dynamic problem are presented to illustrate the efficiency and the accuracy of the proposed method.     

A process planning-orientated approach to part family formation problem in group technology applications

The paper reports on constrained hierarchical clustering applied to similarity analysis, the grouping of process plans and, consequently, the parts manufactured in accordance with them. It proposes solutions to some important problems such as: determining a metric of process plan similarity evaluation; the study of a cluster-creating technique with two process plans and a rule for singling out the standard plan; the determination of a logical threshold value for partitioning into families. Validation of the method creates a family set. The ‘strong forms’ of this set constitute definitive partition into families of the process plan set.     

A study on formation of titanium oxide nanoribbons

The transformation process of nanoribbons produced by the hydrothermal treatment in 10 M NaOH solution at 200 degrees C was investigated systematically via electron microscopy. Field emission scanning electron microscope (FE-SEM) observation showed that the treatment duration had a strong effect on the product morphology from the hollow nanotubes to nanoribbons. The details of transformation were studied by transmission electron miscroscopy. Some nanotubes assembled into clusters and grew into nanowires as the grain to form the nanoribbons, whilemost of nanotubes dissolved into the solution again.     

A strategic approach for preparation of oxide nanomaterials

A microwave assisted solvothermal method is described for rapid preparation of nano-oxides. This method is based on exploiting differential dielectric constants to induce preferred heating and decomposition of the oxide precursors in the presence of suitable capping agents. This strategic approach has been used to prepare nanopowders of MgO, NiO, ZnO, Al₂O₃, Fe₂O₃ and ZrO₂. Under graduate Summer Research Fellow of the Indian Academy of Sciences from IIT Madras.     

An integrated approach to evaluate policies for controlling traffic law violations

Modeling dynamics of the driver behavior is a complex problem. In this paper a system approach is introduced to model and to analyze the driver behavior related to traffic law violations in the Emirate of Abu Dhabi. This paper demonstrates how the theoretical relationships between different factors can be expressed formally, and how the resulting model can assist in evaluating potential benefits of various policies to control the traffic law violations Using system approach, an integrated dynamic simulation model is developed, and model is tested to simulate the driver behavior for violating traffic laws during 2002-2007 in the Emirate of Abu Dhabi. The dynamic simulation model attempts to address the questions: (1) “what” interventions should be implemented to reduce and eventually control traffic violations which will lead to improving road safety and (2) “how” to justify those interventions will be effective or ineffective to control the violations in different transportation conditions. The simulation results reveal promising capability of applying system approach in the policy evaluation studies.     

Cell formation in group technology: A combinatorial search approach

This paper addresses the cell formation problem in group technology (GT). We develop two heuristic methods for generating solutions to the problem. These methods are based on two powerful combinatorial search methods simulated annealing and tabu search. The performance of the heuristics is examined using randomly generated, published and industry data. The results indicate that the simulated annealing based heuristic is the preferred technique in the context of the problem addressed in this paper. Further, we also demonstrate that the simulated annealing based heuristic generates near-optimal solutions to the cell formation model formulated in this paper.     

A novel approach for transferring oleic acid capped iron oxide nanoparticles to water phase

A novel and simple method was described to transfer oleic acid stabilized iron oxide nanoparticles from organic solutions to water. The oxidation of OA by sodium periodate in mixed solvents formed a carboxyl group or vicinal diol to make the hydrophobic groups to hydrophilic groups on the surface of the nanoparticles. The characterization of nanoparticles indicated that the phase transfer based on the oxidation of OA was successful performed without change in the size and shape of the iron oxide nanoparticles. The hydrophilic groups on the iron oxide surface stabilized the nanoparticles in aqueous solution and the oxidized nanoparticles can be applied to bimolecular immobilization.     

A general approach to increasing the radiation hardness of complex structure oxide scintillation crystals

An approach to increasing the radiation hardness of scintillation materials based on complex structure oxide single crystals is proposed. It is shown that damage of the scintillation mechanism and radiation-induced optical absorption are strongly suppressed when a crystal is doped by a specific impurity. The necessary impurity properties are formulated. The proposed approach is illustrated by radiation hardness improvement of the lead tungstate PbWO₄ and yttrium perovskite YAlO₃:Ce scintillation materials.     

A biocompatible approach to surface modification: Biodegradable polymer functionalized super-paramagnetic iron oxide nanoparticles

In the study, Fe₃O₄ nanoparticles with a size range of 10–20 nm were firstly prepared by the modified controlled chemical coprecipitation method from the solution of ferrous/ferric mixed salt-solution in alkaline medium. Then, the super-paramagnetic iron oxide nanoparticles were covalently modified by biodegradable polymers such as polyethylene glycol (PEG) and poly(ethylene glycol)-co-poly(d,l-lactide) (PELA). The size and its distribution of the nanoparticles were determined by dynamic light scattering measurements (DLS). The magnetic nanoparticles was characterized by X-ray powder diffraction (XRD), transmission electron microscopy (TEM), electron diffraction (ED), Fourier transform infrared spectroscopy (FT-IR) and UV–visible spectrophotometry (UV). Magnetic properties were measured using a vibrating sample magnetometer. And the 5-dimethylthiazol-2-yl-2,5-diphenyltetrazolium bromide (MTT) assay was performed to evaluate the biocompatibility of the magnetic nanoparticles. The results showed that the Fe₃O₄ nanoparticles functionalized by PEG and PELA possessed a mean size of 43.2 and 79.3 nm, respectively, and exhibited an excellent biocompatibility.     

A green approach to the synthesis of reduced graphene oxide nanosheets under UV irradiation

We present a totally green approach towards the synthesis and stabilization of aqueous graphene dispersions through UV-irradiated reduction of exfoliated graphene oxide (GO). Polyvinyl pyrrolidone (PVP) is used to enhance the dispersibility of reduced graphene oxide (RGO) by one-step functionalization. The proposed method is low cost and easy without using any photocatalysts or reducing agents, which can open up a new possibility for green preparation of stable RGO dispersions in large-scale production.     

Reversible nanopore formation in Ge nanowires during lithiation-delithiation cycling: an in situ transmission electron microscopy study

Retaining the high energy density of rechargeable lithium ion batteries depends critically on the cycle stability of microstructures in electrode materials. We report the reversible formation of nanoporosity in individual germanium nanowires during lithiation-delithiation cycling by in situ transmission electron microscopy. Upon lithium insertion, the initial crystalline Ge underwent a two-step phase transformation process: forming the intermediate amorphous Li(x)Ge and final crystalline Li(15)Ge(4) phases. Nanopores developed only during delithiation, involving the aggregation of vacancies produced by lithium extraction, similar to the formation of porous metals in dealloying. A delithiation front was observed to separate a dense nanowire segment of crystalline Li(15)Ge(4) with a porous spongelike segment composed of interconnected ligaments of amorphous Ge. This front sweeps along the wire with a logarithmic time law. Intriguingly, the porous nanowires exhibited fast lithiation/delithiation rates and excellent mechanical robustness, attributed to the high rate of lithium diffusion and the porous network structure for facile stress relaxation, respectively. These results suggest that Ge, which can develop a reversible nanoporous network structure, is a promising anode material for lithium ion batteries with superior energy capacity, rate performance, and cycle stability.     

Morphological instability leading to formation of porous anodic oxide films

Electrochemical oxidation of metals, in solutions where the oxide is somewhat soluble, produces anodic oxides with highly regular arrangements of pores. Although porous aluminium and titanium oxides have found extensive use in functional nanostructures, pore initiation and self-ordering are not yet understood. Here we present an analysis that examines the roles of oxide dissolution and ionic conduction in the morphological stability of anodic films. We show that patterns of pores with a minimum spacing are possible only within a narrow range of the oxide formation efficiency (the fraction of oxidized metal atoms retained in the film), which should exist when the metal ion charge exceeds two. Experimentally measured efficiencies, over diverse anodizing conditions on both aluminium and titanium, lie within the different ranges predicted for each metal. On the basis of these results, the relationship between dissolution chemistry and the conditions for pore initiation can now be understood in quantitative terms.     

A variable-parameter unsupervised learning clustering neural network approach with application to machine-part group formation

In this paper, we develop a new unsupervised learning clustering neural network method for clustering problems in general and for solving machine-part group formation problems in particular. We show that our new approach solves a very challenging problem in the area of machine-part group formation. A review of machine-part group formation methods and unsupervised learning artificial neural network methods is given. We modify the well-known competitive learning algorithm by using the generalized Euclidean distance, and a momentum term in the weight vector updating equations. The cluster structure can be adjusted by changing the coefficients in the generalized Euclidean distance. The algorithm is flexible and applicable to many practical problems. We also develop a neural network clustering system which can be used to cluster a 0-1 matrix into diagonal blocks. The developed neural network clustering system is independent of the initial matrix and gives clear final clustering results which specify the machines and parts in each group. We use the developed neural network clustering system to solve several machine-part group formation problems, in which the machine-part incidence matrix is to be clustered into a diagonal block structure. An algorithm is developed to consider lower and upper bounds on the number of machines for each cell. The computational results are compared with those from the well-known rank order clustering and directive clustering analysis methods.