Nanogrooved carbon microtubes for wet three‐dimensional printing of conductive composite structures

Recent advances in three‐dimensional (3D) printing have enabled the fabrication of interesting structures which are not achievable using traditional fabrication approaches. The 3D printing of carbon microtube composite inks allows fabrication of conductive structures for practical applications in soft robotics and tissue engineering. However, it is challenging to achieve 3D printed structures from solution‐based composite inks, which requires an additional process to solidify the ink. Here, we introduce a wet 3D printing technique which uses a coagulation bath to fabricate carbon microtube composite structures. We show that through a facile nanogrooving approach which introduces cavitation and channels on carbon microtubes, enhanced interfacial interactions with a chitosan polymer matrix are achieved. Consequently, the mechanical properties of the 3D printed composites improve when nanogrooved carbon microtubes are used, compared to untreated microtubes. We show that by carefully controlling the coagulation bath, extrusion pressure, printing distance and printed line distance, we can 3D print composite lattices which are composed of well‐defined and separated printed lines. The conductive composite 3D structures with highly customised design presented in this work provide a suitable platform for applications ranging from soft robotics to smart tissue engineering scaffolds. © 2019 Society of Chemical Industry     

Single-step ahead prediction based on the principle of concatenation using grey predictors

In literature a number of different methods are proposed to improve the prediction accuracy of grey models. However, most of them are computationally expensive, and this may prohibit their extensive use. This paper describes a much simpler scheme, based on the principle of concatenation, in which unit step predictions are concatenated by replacing the missing outputs by their previously predicted values. Despite its extreme simplicity, it is shown that the predicted values thus derived results in a better performance than the methods proposed in the literature. Simulation studies show the effectiveness of the proposed algorithm when applied to nonlinear function predictions.     

Non-isothermal kinetics of pyrolysis of Turkish petroleum pitches

Non-isothermal thermogravimetric data of two Turkish petroleum pitches were used to evaluate kinetic parameters of pyrolysis reactions. The article reports the application of Ozawa–Flynn–Wall model to deal with non-isothermal TG data for the evaluation of the activation energy corresponding to the pyrolysis of two different petroleum pitches. Non-isothermal kinetic studies of pyrolysis of the pitches based on the TGA measurements at different heating rates resulted that average activation energy of pyrolysis of pitch B (213 kJ/mol) was higher than that of average activation energy of pitch A (186 kJ/mol). Reaction orders of pitch A and pitch B were calculated as 0.6 and 0.9, respectively.     

Hydrogen liberation from the dehydrocoupling of dimethylamine–borane at room temperature by using novel and highly monodispersed RuPtNi nanocatalysts decorated with graphene oxide

Addressed herein, we reported the fabrication of the graphene oxide (GO) supported monodispersed ruthenium–platinum–nickel (RuPtNi) nanomaterials (3.40 ± 0.32 nm) to be utilized as a catalyst in the process of dimethylamine borane (DMAB) dehydrogenation. The nanoparticles were fabricated through the ultrasonication method by co-reducing the Ru³⁺, Pt²⁺ and Ni²⁺ cations and then the nanomaterials were characterized by X-ray diffraction (XRD), Raman spectroscopy, transmission electron microscopy (TEM), high resolution transmission electron microscopy (HRTEM), electron energy loss spectroscopy (EELS), inductively coupled plasma optical emission spectrometry (ICP-OES), and X-ray photoelectron spectroscopy (XPS). The fabricated nanomaterials showed outstanding efficiency and remarkable reusability in addition to their record catalytic activity at low temperatures and with extreme low concentrations. They had a significantly high turnover frequency (TOF) (727 h^?1) and low activation energy (E_a) (49.43 ± 2 kJ mol^?1) for DMAB dehydrocoupling. To the best of our knowledge, RuPtNi@GO NPs become a very promising candidate as the best catalyst ever.     

Belief Propagation over SISO/MIMO Frequency Selective Fading Channels

In this letter, we propose an iterative belief propagation (BP) channel detector (equalizer) over single-input single- output (SISO) and multiple-input multiple-output (MIMO) frequency selective fading channels as an alternative to the typically used maximum a-posteriori (MAP) or maximum likelihood (ML) detectors. The proposed detector has a parallel structure, resulting in fast hardware implementations. Moreover, BP detector is less complex than the MAP detector and it has a short decoding delay. We analyze the bit error rate and the mutual information and show that, over frequency selective fading channels, the proposed BP detector achieves a near-optimal performance, even in the presence of the length 4 cycles in the corresponding channel factor graph.     

Derivation of a parameter stabilizing training criterion for adaptive neuro-fuzzy inference systems in motion control

This paper presents a novel training algorithm for adaptive neuro-fuzzy inference systems. The algorithm combines the error back-propagation algorithm with the variable structure systems approach. Expressing the parameter update rule as a dynamic system in continuous time and applying sliding mode control (SMC) methodology to the dynamic model of the gradient based training procedure results in the parameter stabilizing part of training algorithm. The proposed combination therefore exhibits a degree of robustness to the unmodelled multivariable internal dynamics of the gradient-based training algorithm. With conventional training procedures, the excitation of this dynamics during a training cycle can lead to instability, which may be difficult to alleviate owing to the multidimensionality of the solution space and the ambiguities concerning the environmental conditions. This paper shows that a neuro-fuzzy model can be trained such that the adjustable parameter values are forced to settle down (parameter stabilization) while minimizing an appropriate cost function (cost optimization), which is based on state tracking performance. In the application example, trajectory control of a two degrees of freedom direct drive robotic manipulator is considered. As the controller, an adaptive neuro-fuzzy inference mechanism is used and, in the parameter tuning, the proposed algorithm is utilized.     

Gain adaptation in sliding mode control of robotic manipulators

In this paper, a novel scheme is proposed to adapt the gains of a sliding mode controller (SMC) so that the problems faced in its practical implementations as a motion controller are overcome. A Lyapunov function is selected for the design of the SMC and an MIT rule is used for gain adaptation. The criterion that is minimized for gain adaptation is selected as the sum of the squares of the control signal and the sliding surface function. This novel approach is tested on a scara-type robot manipulator. The experimental results presented prove its efficacy.     

Evaluation of machining performance in cryogenic machining of Inconel 718 and comparison with dry and MQL machining

There has been significant work on establishing relationships between machining performance and the cutting parameters for various work materials. Recent trends in machining research show that major efforts are being made to understand the impact of various cooling/lubrication methods on machining performance and surface integrity characteristics, all aimed at improving process and product performance. This study presents the experimental results of cryogenic machining of Inconel 718, a high-temperature aerospace alloy, and comparison of its performance in dry and minimum quantity lubrication machining. Experimental data on force components, progressive tool wear parameters such as flank wear, notch wear, crater wear, cutting temperature, chip morphology, and surface roughness/topography of machined samples are presented. New findings show that cryogenic machining is a promising research direction for machining of high-temperature aerospace alloy, Inconel 718, as it offers improved machining performance in terms of reduced tool wear, temperature, and improved surface quality. It was also found that the number of nozzles in cryogenic machining plays a vital role in controlling cutting forces and power consumption in cryogenic machining of Inconel 718.     

Conductive wool yarns by continuous vapour phase polymerization of pyrrole

Conducting polypyrrole (PPy) coated wool yarns were prepared by a continuous vapour polymerization technique, using a speed of 1 m/min with different iron(III) chloride (FeCl₃) as the oxidant at different concentrations. The resistivities, tensile properties, longitudinal and cross-sectional views of PPy-coated wool yarns were investigated. Optimum specific electrical resistances of 2.96 Ω g/cm² at 80 g/L FeCl₃ and 1.69 Ω g/cm² at 70 g/L FeCl₃ were obtained for 500 and 400 twist per meter (TPM) yarns, respectively. PPy-coated wool yarns exhibited higher elongation than uncoated yarns. Longitudinal and cross-sectional views of the yarns indicate that PPy coating penetrated deep into the yarn cross-section and a uniform coating was obtained on the surface of the yarn surface.     

Pars plana vitrectomy with pars plana tube implantation in eyes with intractable glaucoma

Fas Ligand (FasL) can induce apoptosis of Fas-bearing cells. It is expressed on the cell surface of many tumor cells, immune-privileged tissues and activated lymphocytes. We report here that FasL can itself transduce signals, leading to cell-cycle arrest and cell death in CD4+ T cells. In vitro, FasL engagement inhibited CD4+ T-cell proliferation, cell-cycle progression, and IL-2 secretion. In vivo, FasL engagement prevented superantigen-mediated CD4+, but not CD8+, T-cell expansion. These findings demonstrate that FasL engagement regulates cell-cycle progression, and show that FasL engagement in vivo has a potent anti-inflammatory effect specific for CD4+ T cells.