15 research outputs found

    Supercapacitor Performance of Nickel-Cobalt Sulfide Nanotubes Decorated Using Ni Co-Layered Double Hydroxide Nanosheets Grown in Situ on Ni Foam

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    In this study, to fabricate a non-binder electrode, we grew nickel-cobalt sulfide (NCS) nanotubes (NTs) on a Ni foam substrate using a hydrothermal method through a two-step approach, namely in situ growth and an anion-exchange reaction. This was followed by the electrodeposition of double-layered nickel-cobalt hydroxide (NCOH) over a nanotube-coated substrate to fabricate NCOH core-shell nanotubes. The final product is called NCS@NCOH herein. Structural and morphological analyses of the synthesized electrode materials were conducted via SEM and XRD. Different electrodeposition times were selected, including 10, 20, 40, and 80 s. The results indicate that the NCSNTs electrodeposited with NCOH nanosheets for 40 s have the highest specific capacitance (SC), cycling stability (2105 Fg-1 at a current density of 2 Ag-1), and capacitance retention (65.1% after 3,000 cycles), in comparison with those electrodeposited for 10, 20, and 80 s. Furthermore, for practical applications, a device with negative and positive electrodes made of active carbon and NCS@NCOH was fabricated, achieving a high-energy density of 23.73 Whkg-1 at a power density of 400 Wkg-1

    Investigation of the Electrochemical Properties of CoAl-Layered Double Hydroxide/Ni(OH)2

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    Layered double hydroxides (LDH) as active electrode materials have become the focus of research in energy storage applications. The manufacturing of excellent electrochemical performance of the LDH electrode is still a challenge. In this paper, the production of CoAl-LDH@Ni(OH)2 is carried out in two steps, including hydrothermal and electrodeposition techniques. The prominent features of this electrode material are shown in the structural and morphological aspects, and the electrochemical properties are investigated by improving the conductivity and cycle stability. The core of this experimental study is to investigate the properties of the materials by depositing different amounts of nickel hydroxide and changing the loading of the active materials. The experimental results show that the specific capacity is 1810.5F·g−1 at 2 A/g current density and the cycle stability remained at 76% at 30 A g−1 for 3000 cycles. Moreover, a solid-state asymmetric supercapacitor with CoAl-LDH@Ni(OH)2 as the positive electrode and multi-walled carbon nanotube coated on the nickel foam as the negative electrode delivers high energy density (16.72 Wh kg−1 at the power density of 350.01 W kg−1). This study indicates the advantages of the design and synthesis of layered double hydroxides, a composite with excellent electrochemical properties that has potential applications in energy storage

    Tribo-mechanical properties evaluation of HA/TiO2/CNT nanocomposite

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    In this study, a combination of reverse microemulsion and hydrothermal techniques were used to synthesize HA. A hydrothermal method was used to synthesize HA/TiO2/CNT nanocomposite powders. Cold and hot isostatic pressing techniques were used to fabricate tablet-shaped samples. To investigate the biocompatibility and tribo-mechanical properties of HA/TiO2 and HA/TiO2/CNTs, four samples were prepared with different percentages of CNTs, namely, HA/TiO2 (S0), HA/TiO2/CNT (S1.0), HA/TiO2/CNT (S2.0), and HA/TiO2/CNT (S3.0). The microstructure and morphology of the HA/TiO2/CNTs were characterized by transmission electron microscopy, scanning electron microscopy, energy-dispersive X-ray spectroscopy, and X-ray diffraction. Hardness test results show that S3.0 displayed the highest surface hardness (285 HV) compared to other samples. The wear rate of HA/TiO2/CNT with the highest CNT content showed a decrease compared with those of the other samples. The results from nanoindentation tests showed that Young's modulus of the S3.0 sample was 58.1% greater than that of the S0 sample. Furthermore, the human MDA-MB-231 cell line demonstrated good binding to the surface of the samples in the in-vitro biocompatibility evaluation of the HA/TiO2/CNT composites. 2021, The Author(s).This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. NRF-2020R1A4A1019074).Scopu

    HipXNet: Deep Learning Approaches to Detect Aseptic Loos-Ening of Hip Implants Using X-Ray Images

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    Radiographic images are commonly used to detect aseptic loosening of the hip implant in patients with total hip replacement (THR) surgeries. These techniques of manual assessment by medical professionals can suffer from the drawback of low accuracy, poor inter-observer reliability, and delays due to the unavailability of experienced clinicians. Thus, the paper provides a reliable Deep Convolutional Neural Networks (DCNNs) based novel stacking approach (HipXNet) for detecting loosening of the hip implant using X-ray images. Two major investigations were done in this study. Firstly, the performance of four different state-of-the-art object detection YOLOv5 models was evaluated to detect the implant region from the hip X-ray images. Secondly, the study developed a stacking classifier using three different Convolutional neural networks (CNN) models to classify aseptic hip loosening and compared the performance with eight different state-of-the-art CNN networks. Moreover, one publicly accessible dataset with two sub-sets was created for these two experiments, where 200 hip implant X-ray images were collected and annotated by two expert radiologists for implant detection and 206 hip implant X-ray images were collected for loosening detection. YOLOv5m model outperformed the other variants of YOLOv5 to detect the implant region with the precision, recall, mean average precision (mAP)0.5, mAP0.5-0.95 of 100%, 100%, 100%, and 87.8%, respectively. Densenet201 CNN model outperformed other CNN models with the accuracy, precision, sensitivity, F1 score, and specificity of 94.66%, 94.66%, 94.66%, 94.66%, and 94.5%, respectively while the stacking technique with Random Forest meta learner classifier produced the best performance with the accuracy, precision, sensitivity, F1 score and specificity of 96.11%, 96.42%, 96.42%, 96.42%, and 96.74% respectively for loosening detection. The reliability of the performance was confirmed by the popular Score-CAM visualization. This study can help in the early and fast identification of hip implant loosening with the help of simple X-ray images and computed aided diagnosis. 2013 IEEE.This work was supported in part by the Qatar National Research Fund (QNRF) under Grant NPRP11S-0102-180178, and in part by the Qatar National Library.Scopu

    Wear resistance investigation of titanium nitride-based coatings

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    The wear of components while they are in service is a predominant factor controlling the life of machine components. Metal parts are often damaged because of wear-driven failures causing the loss of dimensions and functionality. In order to reduce wear, researchers follow two paths: (i) use new, wear resistant materials or (ii) improve the wear resistance of materials by adding alloying elements or performing surface treatments. Thin film hard nitride coatings are seen as a viable way to enhance the wear resistance of metallic materials, thus extending the lifespan of products. This paper reviews the wear resistance of titanium nitride-based coatings obtained using physical vapor deposition (PVD), chemical vapor deposition (CVD), and thermal spraying techniques. The results of thin film coatings deposition on the wear performance and on the coefficient of friction are investigated. The advantages and disadvantages of coating methods are discussed. Finally, recent developments and new possibilities for coating manufacturers to produce films with enhanced wear performance are briefly discussed.NPRP award NPRP 5–423–2–167 from the Qatar National Research Fund (a member of The Qatar Foundation). Hanyang University (201500000000438)

    Estimation of Tsunami Bore Forces on a Coastal Bridge Using an Extreme Learning Machine

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    This paper proposes a procedure to estimate tsunami wave forces on coastal bridges through a novel method based on Extreme Learning Machine (ELM) and laboratory experiments. This research included three water depths, ten wave heights, and four bridge models with a variety of girders providing a total of 120 cases. The research was designed and adapted to estimate tsunami bore forces including horizontal force, vertical uplift and overturning moment on a coastal bridge. The experiments were carried out on 1:40 scaled concrete bridge models in a wave flume with dimensions of 24 m × 1.5 m × 2 m. Two six-axis load cells and four pressure sensors were installed to the base plate to measure forces. In the numerical procedure, estimation and prediction results of the ELM model were compared with Genetic Programming (GP) and Artificial Neural Networks (ANNs) models. The experimental results showed an improvement in predictive accuracy, and capability of generalization could be achieved by the ELM approach in comparison with GP and ANN. Moreover, results indicated that the ELM models developed could be used with confidence for further work on formulating novel model predictive strategy for tsunami bore forces on a coastal bridge. The experimental results indicated that the new algorithm could produce good generalization performance in most cases and could learn thousands of times faster than conventional popular learning algorithms. Therefore, it can be conclusively obtained that utilization of ELM is certainly developing as an alternative approach to estimate the tsunami bore forces on a coastal bridge

    Instrumented Hip Implant: A Review

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    About 20% of people older than forty years old face more bone degenerative diseases. The older population is increasing quite rapidly than before which increases the need for knee or hip implants tremendously. One of the major problems of the current implants is their short lifetime and their impact on the surrounding human tissue. The short life can be attributed to implant wear, loosening, and misalignment, which often cause pain and discomfort to the patient. Functional failure of the implant may be followed by a revision surgery, which is often painful and has a relatively low success rate. Moreover, to avoid unexpected failure and unnoticed deterioration of the implant, it is important to make provision for monitoring implants' performance. Instrumented implants can provide accurate monitoring of the loosening state of the implant, which can delay the revision surgeries and its consequences. This study provides a comprehensive review of the technological development of instrumented hip implants to monitor the status of the implants. The main requirements for the implants are highlighted by reviewing different aspects of the instrumented hip implant systems. In-vivo studies reported in the literature were summarized. Vibration and Acoustic Emission (AE) measurement based loosening detection were found to be the most common methods for in-vitro studies. A comprehensive review of power supply and communication modules was presented. Despite the advancement in this field, current systems are not yet able to provide effective monitoring of the implant's status during the daily activities of patients. 2001-2012 IEEE.Manuscript received November 24, 2020; accepted December 10, 2020. Date of publication December 16, 2020; date of current version February 17, 2021. This work was supported in part by the Qatar National Research Fund under Grant NPRP11S-0102-180178 and in part by a member of the Qatar Foundation, Doha, Qatar. The associate editor coordinating the review of this article and approving it for publication was Prof. Kea-Tiong (Samuel) Tang. (Corresponding author: Muhammad E. H. Chowdhury.) Yazan Qiblawey, Muhammad E. H. Chowdhury, and Amith Khandakar are with the Department of Electrical Engineering, Qatar University, Doha, Qatar (e-mail: [email protected]; [email protected]; [email protected]).Scopu

    Structural and morphological study of mechanochemically synthesized crystalline nanoneedles of Zr-doped carbonated chlorapatite

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    Nanosize Zr-doped carbonated chlorapatite (n-ZCCA) was developed as a novel bioceramic by a ball milling process. Results showed that the microstructural characteristics of the product were affected significantly by the degree of substitution and subsequent annealing at 800 °C for 1 h. In the absence of zirconium, mechanical activation for 3 h resulted in the formation of carbonated hydroxyapatite (CHA). With the addition of various amounts of zirconium, nanosize Zr-doped carbonated chlorhydroxyapatite (n-ZCCHA) and n-ZCCA were formed as a result of progressive mechanochemical reactions. From the HR-TEM images, the preferential substitution of Zr onto the ac or bc chlorapatite crystal facets (rich in calcium ions) led to a c-axis oriented crystal growth of crystalline nanoneedles with an average size of around 40–60 nm in length and 10–20 nm in width.UM High Impact Research Grant UM-MOHE UM.C/625/1/HIR/MOHE/ENG/44 (Regenerative Biomechanics of Human Body) from the Ministry of Higher Education Malaysia and University of Malaya Grant number RP021C-13AE

    Finite Element Analysis of the Mechanism of Traumatic Aortic Rupture (TAR)

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    As many as 80% of patients with TAR die on the spot while out of those reaching a hospital, 30% would die within 24 hours. Thus, it is essential to better understand and prevent this injury. The exact mechanics of TAR are unknown. Although most researchers approve it as a common-sense deceleration injury, the exact detailed mechanism of TRA still remains unidentified. In this work, a deceleration mechanism of TAR was carried out using finite element analysis (FEA). The FE analysis aimed to predict internal kinematics of the aorta and assist to comprehend the mechanism of aorta injury. The model contains the heart, lungs, thoracic aorta vessel, and rib cage. High-resolution computerized tomography (HR CT scan) was used to provide pictures that were reconstructed by MIMICS software. ANSYS FE simulation was carried out to investigate the behavior of the aorta in the thoracic interior after deceleration occurred during a car crash. The finite element analysis indicated that maximum stress and strain applied to the aorta were from 5.4819e5 to 2.614e6 Pa and 0.21048 to 0.62676, respectively, in the Y-direction when the initial velocity increased from 10 to 25 m/s. Furthermore, in the X-direction when the velocity changed from 15 to 25 m/s, the stress and strain values increased from 5.17771e5 to 2.3128e6 and from 0.22445 to 0.618, respectively

    Synthesis and characterization of α-Fe2O3/polyaniline nanotube composite as electrochemical sensor for uric acid detection

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    We report the synthesis of α-Fe2O3/polyaniline nanotube (PAn NTs) composite as an electrochemical sensor for uric acid (UA) detection. Field emission scanning electron microscopy (FESEM) indicates a hexagonal shape of the α-Fe2O3 while a nanotube morphology of the PAn. Impedance spectroscopy results confirm a significant decrease in the charge transfer resistance of the glassy carbon electrode (GCE) modified with α-Fe2O3/PAn NTs due to the presence of PAn NTs. The results show that the increase in the conductivity of α-Fe2O3 in the presence of PAnNTs could improve the catalytic performance of α-Fe2O3/PAn NTs composite, compared to the pure α-Fe2O3 nanoparticles. From differential pulse voltammetry, a linear working range for the concentration of UA between 0.01 µM and 5 µM, with a LOD of 0.038 µM (S/N = 3) was obtained. The sensitivity of the linear segment is 0.433 μA µM−1. The reliability of the modified electrode towards the detection of UA was investigated in the presence of interfering acids such as ascorbic acid, citric acid and succinic acid
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