Electrophoretic deposition of graphene oxide on carbon brush as bioanode for microbial fuel cell operated with real wastewater

Microbial fuel cell (MFC) is a promising technology for simultaneous wastewater treatment and energy harvesting. The properties of the anode material play a critical role in the performance of the MFC. In this study, graphene oxide was prepared by a modified hummer's method. A thin layer of graphene oxide was incorporated on the carbon brush using an electrophoretic technique. The deoxygenated graphene oxide formed on the surface of the carbon brush (RGO-CB) was investigated as a bio-anode in MFC operated with real wastewater. The performance of the MFC using the RGO-CB was compared with that using plain carbon brush anode (PCB). Results showed that electrophoretic deposition of graphene oxide on the surface of carbon brush significantly enhanced the performance of the MFC, where the power density increased more than 10 times (from 33 mWm^?2 to 381 mWm^?2). Although the COD removal was nearly similar for the two MFCs, i.e., with PCB and RGO-CB; the columbic efficiency significantly increased in the case of RGO-CB anode. The improved performance in the case of the modified electrode was related to the role of the graphene in improving the electron transfer from the microorganism to the anode surface, as confirmed from the electrochemical impedance spectroscopy measurements.     

Compact UWB-MIMO Triple Notched Antenna for Isolation Reduction

Wireless Personal Communications - In this article compact multiple input multiple output (MIMO) antenna with triple notch at the ultra-wideband application having two identical monopole antennas...     

The Possibility of Dense Materials Based on Obtaining an AlN–SiC Solid Solution by Self-Propagating High-Temperature Synthesis Gasostating

Russian Journal of Non-Ferrous Metals - The synthesis and sintering of the (AlN)x(SiC)1 – x solid solution have been studied under conditions of self-propagating high-temperature synthesis...     

Precise Extraction of Charge Carrier Mobility for Organic Transistors

Unreliable mobility values, and particularly greatly overestimated values and severely distorted temperature dependences, have recently hampered the development of the organic transistor field. Given that organic field‐effect transistors (OFETs) have been routinely used to evaluate mobility, precise parameter extraction using the electrical properties of OFETs is thus of primary importance. This review examines the origins of the various mobilities that must be determined for OFET applications, the relevant extraction methods, and the data selection limitations, which help in avoiding conceptual errors during mobility extraction. For increased precision, the review also discusses device fabrication considerations, calibration of both the specific gate‐dielectric capacitance and the threshold voltage, the contact effects, and the bias and temperature dependences, which must actually be handled with great care but have mostly been overlooked to date. This review serves as a systematic overview of the OFET mobility extraction process to ensure high precision and will also aid in improving future research.     

Crossing the Border: From Keto- to Imine Reduction in Short-Chain Dehydrogenases/Reductases

The family of NAD(P)H-dependent short-chain dehydrogenases/reductases (SDRs) comprises numerous biocatalysts capable of C=O or C=C reduction. The highly homologous noroxomaritidine reductase (NR) from Narcissus sp. aff. pseudonarcissus and Zt_SDR from Zephyranthes treatiae, however, are SDRs with an extended imine substrate scope. Comparison with a similar SDR from Asparagus officinalis (Ao_SDR) exhibiting keto-reducing activity, yet negligible imine-reducing capability, and mining the Short-Chain Dehydrogenase/Reductase Engineering Database indicated that NR and Zt_SDR possess a unique active-site composition among SDRs. Adapting the active site of Ao_SDR accordingly improved its imine-reducing capability. By applying the same strategy, an unrelated SDR from Methylobacterium sp. 77 (M77_SDR) with distinct keto-reducing activity was engineered into a promiscuous enzyme with imine-reducing activity, thereby confirming that the ability to reduce imines can be rationally introduced into members of the “classical” SDR enzyme family. Thus, members of the SDR family could be a promising starting point for protein approaches to generate new imine-reducing enzymes.     

3D Investigation of 8-nm Tapered n-FinFET Model

The miniaturization has become a key word for advanced integrated circuits over the last few years. It is within this context that the fin field effect tra     

Cerebral microbleeds and cognitive decline in a hemodialysis patient: Case report and review of literature

Cerebral microbleeds (CMBs) are small hemosiderin deposits indicative of prior cerebral microscopic hemorrhage and previously thought to be clinically silent. Recent population‐based cross‐sectional studies and prospective longitudinal cohort studies have revealed association between CMB and cognitive dysfunction. In the general population, CMBs are associated with age, hypertension, and cerebral amyloid angiopathy. In the chronic kidney disease (CKD) population, diminished estimated glomerular filtration rate has been found to be an independent risk factor for CMB, raising the possibility that a uremic milieu may predispose to microbleeds. In the end‐stage renal disease (ESRD) population on hemodialysis, the incidence of microbleeds is significantly higher compared with a control group without history of CKD or stroke. We present an ESRD patient on chronic hemodialysis with a history of gradual cognitive decline and progressive CMBs. Through this case and literature review, we illustrate the need to develop detection and prediction models to treat this frequent development in ESRD patients.     

Adaptive backstepping repetitive learning control design for nonlinear discrete‐time systems with periodic uncertainties

This paper addresses a tracking problem for uncertain nonlinear discrete‐time systems in which the uncertainties, including parametric uncertainty and external disturbance, are periodic with known periodicity. Repetitive learning control (RLC) is an effective tool to deal with periodic unknown components. By using the backstepping procedures, an adaptive RLC law with periodic parameter estimation is designed. The overparameterization problem is overcome by postponing the parameter estimation to the last backstepping step, which could not be easily solved in robust adaptive control. It is shown that the proposed adaptive RLC law without overparameterization can guarantee the perfect tracking and boundedness of the states of the whole closed‐loop systems in presence of periodic uncertainties. In addition, the effectiveness of the developed controller is demonstrated by an implementation example on a single‐link flexible‐joint robot. Copyright © 2014 John Wiley & Sons, Ltd.     

A practical Equivalent Electrical Circuit model for Proton Exchange Membrane Fuel Cell (PEMFC) systems

An alternative Equivalent Electrical Circuit for Proton Exchange Membrane Fuel Cells is modelled in this study. Both I–V characteristics and H₂ consumptions corresponding to generated power under load and no-load conditions are investigated. For this purpose, H₂ consumptions and I–V characteristics of three different sized PEMFCs are tested. There is a very good harmony between the model results and measured values (relative error %0.7, %6.4 and %2.5 for FC-A, FC-B and FC-C respectively). In the proposed model current passes only on parallel resistance and not on serial resistance at no-load condition. Thus, a FC with higher parallel resistance should be preferred. Another key output of this study is that based on the proposed model, performance comparison of FCs can be performed with the parameters defined in this work. Proposals made in this study can easily be used for performance analysis of FCs under for both steady state and transient analysis.