Using anodic aluminum oxide templates and electrochemical method to deposit BiSbTe-based thermoelectric nanowires

In this study, the cyclic voltammetry method was first used to find the reduced voltages and anodic peaks of Bi³⁺, Sb³⁺, and Te⁴⁺ ions as the judgments for the growth of the (Bi,Sb)_{2 - x} Te_{3 + x}-based materials. Ethylene glycol (C₂H₆O₂) was used as a solvent, and 0.3 M potassium iodide (KI) was used to improve the conductivity of the solution. Two different electrolyte formulas were first used: (a) 0.01 M Bi(NO₃)₃-5H₂O, 0.01 M SbCl₃, and 0.01 M TeCl₄ and (b) 0.015 M Bi(NO₃)₃-5H₂O, 0.005 M SbCl₃, and 0.0075 M TeCl₄. The potentiostatic deposition process was first used to find the effect of reduced voltage on the variation of compositions of the (Bi,Sb)_{2 - x}Te_{3 + x}-based materials. After finding the better reduced voltage, 0.01 M Bi(NO₃)₃-5H₂O, 0.01 M SbCl₃, and 0.01 M TeCl₄ were used as the electrolyte formula. The pulse deposition process was successfully used to control the composition of the (Bi,Sb)_{2 - x}Te_{3 + x}-based materials and grow the nanowires in anodic aluminum oxide (AAO) templates.     

A three-dimensional inverse geometry problem in estimating simultaneously two interfacial configurations in a composite domain

A three-dimensional inverse geometry problem, i.e. shape identification problem, in estimating simultaneously two interfacial configurations in a composite domain with three regions is examined in the present work by using the conjugate gradient method (CGM) and commercial package CFD-ACE+. Two over-utilized conditions should be utilized in determining two gradient equations. Numerical experiments using different measurement errors and different interfacial configurations were performed to justify the validity of the conjugate gradient method in solving this inverse geometry problem. Finally it is concluded that accurate interfacial configurations can be estimated by utilizing the present inverse algorithm.     

A stable adaptive fuzzy sliding-mode control for affine nonlinearsystems with application to four-bar linkage systems

In this paper, a stable adaptive fuzzy sliding-mode control for affine highly nonlinear systems is developed. First, the external part of a transformed system via a feedback linearizing control evolves a linear dynamic system with uncertainties. A reference model with the desired amplitude and phase properties is given to obtain an error model. Since the uncertainties are assumed to be large, a fuzzy model is employed to model these uncertainties. A learning law with e-modification for the weight of a fuzzy model is considered to ensure the boundedness of learning weight without the requirement of persistent excitation condition. Then, an equivalent control using the known part of system dynamics and the learning fuzzy model is designed to achieve the desired control behavior. Furthermore, the uncertainties caused by the approximation of fuzzy model and the error of learning weight are tackled by a switching control. Finally, the stability of the overall system is verified by the Lyapunov theory. Simulations and experiments of the velocity control of a four-bar-linkage system are presented to verify the usefulness of the proposed control     

Topology optimization of three dimensional tissue engineering scaffold architectures for prescribed bulk modulus and diffusivity

Tissue engineering scaffolds play critical roles in skeletal tissue regeneration by supporting physiological loads as well as enhancing cell/tissue migration and formation. These roles can be fulfilled by the functional design of scaffold pore architectures such that the scaffold provides proper mechanical and mass transport environments for new tissue formation. These roles require simultaneous design of mechanical and mass transport properties. In this paper, a numerical homogenization based topology optimization scheme was applied to the design of three dimensional unit microstructures for tissue engineering scaffolds. As measures of mechanical and mass transport environments, target effective bulk modulus and isotropic diffusivity were achieved by optimal design of porous microstructure. Cross property bounds between bulk modulus and diffusivity were adapted to determine feasible design targets for a given porosity. Results demonstrate that designed microstructures could reach cross property bounds for porosity ranging from 30% to 60%.     

Precipitation Kinetics During Post-heat Treatment of an Additively Manufactured Ferritic Stainless Steel

Metallurgical and Materials Transactions A - The microstructure response of laser-powder bed fusion (L-PBF)-processed ferritic stainless steel (AISI 441) during post-heat treatments is studied in...     

Au@NiSx Yolk@Shell Nanostructures as Dual-Functional Electrocatalysts for Concomitant Production of Value-Added Tartronic Acid and Hydrogen Fuel

Efficient glycerol electrooxidation reaction (GEOR) over gold@nickel sulfide (Au@NiS_x) yolk@shell nanostructures is demonstrated, achieving ≈50.4% glycerol conversion at 10 h, 92.6% selectivity toward three-carbon products, and 90.7% total Faradaic efficiency. By regulating the electrode potential, tartronic acid (TART), one of the highest value-added intermediates, can be produced with a selectivity as high as 43.1% and a yield of 45.6 µmol cm⁻² h⁻¹. A combination of ex situ microstructural analysis, operando Raman, and operando X-ray absorption measurements reveals a dynamic surface reconstruction course from Au@NiS_x to Au@NiS_x/NiOOH during the glycerol oxidation process. The unique reconstructed architectures featuring conductive interior NiS_x components and active surface high-valence Ni³⁺ species account for the superior GEOR performance. Further integration of GEOR with hydrogen evolution reaction is realized by employing Au@NiS_x as both anode and cathode electrocatalysts in a two-electrode configuration. Concomitantly production of TART and hydrogen fuel is accomplished. This study demonstrates that Au@NiS_x not only can convert glycerol to TART with remarkable efficiency and selectivity, but also can produce hydrogen at a moderate level. The findings from this study can facilitate the development of dual-functional electrocatalysts capable of producing high-value products at both the cathode and anode sides.     

Intrusion detection by machine learning: A review

The popularity of using Internet contains some risks of network attacks. Intrusion detection is one major research problem in network security, whose aim is to identify unusual access or attacks to secure internal networks. In literature, intrusion detection systems have been approached by various machine learning techniques. However, there is no a review paper to examine and understand the current status of using machine learning techniques to solve the intrusion detection problems. This chapter reviews 55 related studies in the period between 2000 and 2007 focusing on developing single, hybrid, and ensemble classifiers. Related studies are compared by their classifier design, datasets used, and other experimental setups. Current achievements and limitations in developing intrusion detection systems by machine learning are present and discussed. A number of future research directions are also provided.     

Separation and identification of a novel tadalafil analogue adulterant in a dietary supplement

A novel tadalafil analogue found in a dietary supplement by routine drug-adulteration screening was isolated by column chromatography and HPLC. On the basis of extensive 1D- and 2D-nuclear magnetic resonance (NMR), infrared (IR) and mass spectral analyses, the structure of the new compound YJ-02 was established as 6‐(benzo[d][1,3]dioxol‐5‐yl)‐2,3,6,7,12,12a‐hexahydro‐2‐(1E,2E)‐3‐phenylallylidene)amino)pyrazino[1?,2?:1,6]pyrido[3,4‐b]indole‐1,4‐dione. Its common name is N-phenylpropenyltadalafil.     

Modified Packing Algorithm for Dynamic Energy-Saving in Cloud Computing Servers

Since the raising of the cloud computing, the applications of web service have been extended rapidly. However, the data centers of cloud computing also cause the problem of power consumption and the resources usually have not been used effectively. Decreasing the power consumption and enhancing resource utilization become main issues in cloud computing environment. In this paper, we propose a method, called MBFDP (modified best fit decreasing packing), to decrease power consumption and enhance resource utilization of cloud computing servers. From the results of experiments, the proposed solution can reduce power consumption effectively and enhance the utilization of resources of servers. 1     

Exploring temporal relationships between scientific and technical fronts: a case of biotechnology field

Biotechnology is an expanding interdisciplinary field in which the interactions of science and technology (S&T) are more and more intensified. Question raised regarding the dynamic interactions between S&T encourages us to propose a series of methodologies for examination. Using high-impact publications and patents as the proxy measures, two document sets are transformed into the scientific and technical front trajectories respectively, and then each subject is categorized into either basic science, or applied technology, or co-existence. The results show that, in the biotechnology field, subjects of embryonic or mesenchymal stem cells, RNA interference, microRNA, and microbial fuel cell are in the basic science phase; those of plant breeding, seed diversity, and taste receptors have been applied to practice. There also exists interactions between S&T in the subjects of disease treatment and gene analysis platform, in which the behavior of technology precedes science, science precedes technology, or synchronous development can be observed.