Electrothermal flow on electrodes arrays at physiological conductivities

AC electrothermal (ET) flow is inevitable for microfluidic systems dissipating electric energy in a conducting medium. Therefore, many practical applications of biomicrofluidics are prone to ET flow. Here, a series of observations are reported on ET flow in a microfluidic chamber that houses three electrode pairs. The observations indicate that the variations in liquid conductivity and channel height critically impact the structure and magnitude of the flow field. Observations indicate that after a critical conductivity a global ET flow is present in the chamber, while at lower conductivities a vortex is present at every electrode edge. In addition, no ET flow is observed when the chamber height is kept below a critical value at physiological conductivity (∼1.5 S/m). The experimental observations are compared with the numerical simulations of ET flow. The validity of the assumptions made in the current AC ET flow theory is also discussed in the light of the experimental data. The observations can be critical while designing microfluidic systems that involve power dissipation in conductive fluids.Inspec keywords: bioelectric phenomena, microfluidics, numerical analysis, bioMEMSOther keywords: electrode array, physiological conductivity, AC electrothermal flow, microfluidic system, electric energy, biomicrofluidics, microfluidic chamber, liquid conductivity, flow field structure, flow field magnitude, global ET flow, ET flow numerical simulation, AC ET flow theory, power dissipation, conductive fluid     

Mesoporous nanocrystalline ZnO microspheres by ethylene glycol mediated thermal decomposition

Zinc oxide (ZnO) nanostructures with various morphologies have been fabricated in literature owing to their potential applications in various emerging fields. In this study, we report a facile, one-step gram-scale synthesis of nanocrystalline mesoporous ZnO microspheres by thermal decomposition of zinc acetate dihydrate in ethylene glycol at 250?°C for 12?h. The average size of the hollow microspheres is found to be 3.01?±?0.52?µm, which are formed by loosely bonded nanocrystallites with average sizes of 17?±?4?nm. We propose a formation mechanism for the mesoporous microspheres, Ostwald ripening of spherical-like nanocrystallites, on the basis of the results obtained by different synthesis durations. We also report the possibility of tuning the morphologies of the obtained ZnO by simply modifying the thermal decomposition solution, where porous ZnO nanoplates are obtained when a mixture of ethylene glycol and water is used and ZnO nanorods with aspect ratios of ～3 are synthesized by using diethylene glycol. ZnO nanowires with lengths up to several microns are fabricated when no solvent is used, i.e. thermal decomposition in air atmosphere. Microstructural and phase characterizations of the samples are conducted by using a field-emission gun scanning electron microscope and X-ray diffractometer. Performances of the obtained nanocrystalline mesoporous ZnO microspheres in photocatalytic degradation of Rhodamine B and as active anode materials in lithium-ion batteries are also presented.     

Development of a quick credibility scoring decision support system using fuzzy TOPSIS

In this study, a quick credibility scoring decision support system is developed for the banks to determine the credibility of manufacturing firms in Turkey. The proposed decision support system is expected to be used by the banks when they want to determine whether an applicant firm is worth a detailed credit check or not. Using such a quick credit scoring decision model reduces the banks’ workload. The proposed credit scoring model is based on the financial ratios and fuzzy TOPSIS approach. It obtains two separate scores which reflect the attractiveness of manufacturing industries within the overall economy and manufacturing firms’ performance with respect to its competitors belonging to the same industry. These two scores are then used to determine the credibility of applicant manufacturing firms. The developed decision support system is tested with various real cases and satisfactory results are obtained. An application is also provided in the paper for illustrative purposes.     

Finite‐time distributed control with time transformation

In this article, we propose distributed control algorithms for first‐ and second‐order multiagent systems for addressing finite‐time control problem with a priori given, user‐defined finite‐time convergence guarantees. The proposed control frameworks are predicated on a recently developed time transformation approach. Specifically, our contribution is twofold: First, a generalized time transformation function is proposed that converts the user‐defined finite‐time interval to a stretched infinite‐time interval, where one can design a distributed control algorithm on this stretched interval and then transform it back to the original finite‐time interval for achieving a given multiagent system objective. Second, for a specific time transformation function, we analytically establish the robustness properties of the resulting finite‐time distributed control algorithms against vanishing and nonvanishing system uncertainties. By contrast to existing finite‐time approaches, it is shown that the proposed algorithms can preserve a priori given, user‐defined finite‐time convergence regardless of the initial conditions of the multiagent system, the graph topology, and without requiring a knowledge of the upper bounds of the considered class of system uncertainties. Illustrative numerical examples are included to further demonstrate the efficacy of the presented results.     

Analyzing the solutions of DEA through information visualization and data mining techniques: SmartDEA framework

Data envelopment analysis (DEA) has proven to be a useful tool for assessing efficiency or productivity of organizations, which is of vital practical importance in managerial decision making. DEA provides a significant amount of information from which analysts and managers derive insights and guidelines to promote their existing performances. Regarding to this fact, effective and methodologic analysis and interpretation of DEA results are very critical. The main objective of this study is then to develop a general decision support system (DSS) framework to analyze the results of basic DEA models. The paper formally shows how the results of DEA models should be structured so that these solutions can be examined and interpreted by analysts through information visualization and data mining techniques effectively. An innovative and convenient DEA solver, SmartDEA, is designed and developed in accordance with the proposed analysis framework. The developed software provides DEA results which are consistent with the framework and are ready-to-analyze with data mining tools, thanks to their specially designed table-based structures. The developed framework is tested and applied in a real world project for benchmarking the vendors of a leading Turkish automotive company. The results show the effectiveness and the efficacy of the proposed framework.     

Ferrofluid actuation with varying magnetic fields for micropumping applications

Magnetic nanoparticle suspensions and their manipulation are becoming an alternative research line. They have vital applications in the field of microfluidics such as microscale flow control in microfluidic circuits, actuation of fluids in microscale, and drug delivery mechanisms. In microscale, it is possible and beneficial to use magnetic fields as actuators of such ferrofluids, where these fluids could move along a dynamic gradient of magnetic field so that a micropump could be generated with this technique. Thus, magnetically actuated ferrofluids could have the potential to be used as an alternative micro pumping system. Magnetic actuation of nanofluids is becoming an emergent field that will open up new possibilities in various fields of engineering. Different families of devices actuating ferrofluids were designed and developed in this study to reveal this potential. A family of these devices actuates discrete plugs, whereas a second family of devices generates continuous flows in tubes of inner diameters ranging from 254?μm to 1.56?mm. The devices were first tested with minitubes to prove the effectiveness of the proposed actuation method. The setups were then adjusted to conduct experiments on microtubes. Promising results were obtained from the experiments. Flow rates up to 120 and 0.135?μl/s were achieved in minitubes and microtubes with modest maximum magnetic field magnitudes of 300?mT for discontinuous and continuous actuation, respectively. The proposed magnetic actuation method was proven to work as intended and is expected to be a strong alternative to the existing micropumping methods such as electromechanical, electrokinetic, and piezoelectric actuation. The results suggest that ferrofluids with magnetic nanoparticles merit more research efforts in micro pumping.     

Detection of tool breakage in milling operations—II. The neural network approach

On-line monitoring of tool cutting conditions and tool breakage is very important for automated factories of the future. In this paper, the time series based tooth period modeling technique (TPMT) is proposed for detecting tool breakage by monitoring a cutting force or torque signal in any direction. TPMT uses the fast a posteriori error sequential technique (FAEST) for on-line modeling of cutting force or torque signals. Tool breakage is detected by evaluating variations of the characteristics of the monitored signal in each tooth period. TPMT was tested on simulated and experimental end milling data. The proposed technique detected tool breakage in all of the test cases without giving any false alarms in the transition cases.     

Hydrogen effects in a dual-phase microalloy steel

A dual-phase steel containing niobium, vanadium and titanium as microalloying elements was tested for hydrogen embrittlement (HE). The susceptibility to HE was observed to be closely related to the microstructural state. Hydrogenated specimens intercritically annealed at relatively low temperatures to develop martensite islands in a ferrite matrix basically exhibited quasi-cleavage fracture with some ductile dimpling. The mode of fracture in charged specimens quenched from higher intercritical annealing temperatures was predominantly intergranular fracture along prior austenite grain boundaries and cracking of martensite laths. The detrimental role of residual stresses, retained austenite and microalloying carbides in the process of HE is discussed.     

Improved Bounds on Quantum Learning Algorithms

In this article we give several new results on the complexity of algorithms that learn Boolean functions from quantum queries and quantum examples.

Anharmonic motions of Kr in the clathrate hydrate

The anomalous glass-like thermal conductivity of crystalline clathrates has been suggested to be the result of the scattering of thermal phonons of the framework by 'rattling' motions of the guests in the clathrate cages. Using the site-specific (83)Kr nuclear resonant inelastic scattering spectroscopy in combination with conventional incoherent inelastic neutron scattering and molecular-dynamics simulations, we provide unambiguous evidence and characterization of the effects on these guest-host interactions in a structure-II Kr clathrate hydrate. The resonant scattering of phonons led to unprecedented large anharmonic motions of the guest atoms. The anharmonic interaction underlies the anomalous thermal transport in this system. Clathrates are prototypical models for a class of crystalline framework materials with glass-like thermal conductivity. The explanation of the unusual molecular dynamics has a wide implication for the understanding of the thermal properties of disordered solids and structural glasses.