Effect of shotpeening on sliding wear and tensile behavior of titanium implant alloys

Titanium has good biocompatibility and so its alloys are used as implant materials, but they suffer from having poor wear resistance. This research aims to improve the wear resistance and the tensile strength of titanium alloys potentially for implant applications. Titanium alloys Ti–6Al–4V and Ti–6Al–7Nb were subjected to shotpeening process to study the wear and tensile behavior. An improvement in the wear resistance has been achieved due to surface hardening of these alloys by the process of shotpeening. Surface microhardness of shotpeened Ti–6Al–4V and Ti–6Al–7Nb alloys has increased by 113 and 58 HV(0.5), respectively. After shotpeening, ultimate tensile strength of Ti–6Al–4V increased from 1000 MPa to 1150 MPa, higher than improvement obtained for heat treated titanium specimens. The results confirm that shotpeening pre-treatment improved tensile and sliding wear behavior of Ti–6Al–4V and Ti–6Al–7Nb alloys. In addition, shotpeening increased surface roughness.

Low pressure methane solubility in lithium-ion batteries based solvents and electrolytes as a function of temperature. Measurement and prediction

The methane solubility in five pure electrolyte solvents and one binary solvent mixture for lithium ion batteries – such as ethylene carbonate (EC), propylene carbonate (PC), dimethyl carbonate (DMC), ethyl methyl carbonate (EMC), diethyl carbonate (DEC) and the (50:50 wt%) mixture of EC:DMC was studied experimentally at pressures close to atmospheric and as a function of temperature between (280 and 343) K by using an isochoric saturation technique. The effect of the selected anions of a lithium salt LiX (X = hexafluorophosphate,

Viscosity and Carbon Dioxide Solubility for LiPF6, LiTFSI, and LiFAP in Alkyl Carbonates: Lithium Salt Nature and Concentration Effect

Deep Eutectic Solvents Based on N-Methylacetamide and a Lithium Salt as Electrolytes at Elevated Temperature for Activated Carbon-Based Supercapacitors

An integrated approach for real-time model-based state-of-charge estimation of lithium-ion batteries

Lithium-ion batteries have been widely adopted in electric vehicles (EVs), and accurate state of charge (SOC) estimation is of paramount importance for the EV battery management system. Though a number of methods have been proposed, the SOC estimation for Lithium-ion batteries, such as LiFePo4 battery, however, faces two key challenges: the flat open circuit voltage (OCV) vs SOC relationship for some SOC ranges and the hysteresis effect. To address these problems, an integrated approach for real-time model-based SOC estimation of Lithium-ion batteries is proposed in this paper. Firstly, an auto-regression model is adopted to reproduce the battery terminal behaviour, combined with a non-linear complementary model to capture the hysteresis effect. The model parameters, including linear parameters and non-linear parameters, are optimized off-line using a hybrid optimization method that combines a meta-heuristic method (i.e., the teaching learning based optimization method) and the least square method. Secondly, using the trained model, two real-time model-based SOC estimation methods are presented, one based on the real-time battery OCV regression model achieved through weighted recursive least square method, and the other based on the state estimation using the extended Kalman filter method (EKF). To tackle the problem caused by the flat OCV-vs-SOC segments when the OCV-based SOC estimation method is adopted, a method combining the coulombic counting and the OCV-based method is proposed. Finally, modelling results and SOC estimation results are presented and analysed using the data collected from LiFePo4 battery cell. The results confirmed the effectiveness of the proposed approach, in particular the joint-EKF method.

Potential applications of shape memory alloys in seismic retrofitting of exterior RC beam-column joints

Shape memory alloys (SMAs) have the ability to undergo large deformations with minimum residual strain and also the extraordinary ability to undergo reversible hysteretic shape change known as the shape memory effect. The shape memory effect of these alloys can be utilised to develop a convenient way of actively confine concrete sections to improve their shear strength, flexural ductility and ultimate strain. Most of the previous work on active confinement of concrete using SMA has been carried out on circular sections. In this study retrofitting strategies for active confinement of non-circular sections have been proposed. The proposed schemes presented in this paper are conceived with an aim to seismically retrofit beam-column joints in non-seismically designed reinforced concrete buildings. SMAs are complex materials and their material behaviour depends on number of parameters. Depending upon the alloying elements, SMAs exhibit different behaviour in different conditions and are highly sensitive to variation in temperature, phase in which it is used, loading pattern, strain rate and pre-strain conditions. Therefore, a detailed discussion on the behaviour of SMAs under different thermo-mechanical conditions is presented first.

Modeling of titanium alloys by using artificial neural networks

Titanium alloy exhibits an excellent combination of bio-compatibility, corrosion resistance, strength and toughness. The microstructure of an alloy influences the properties. The microstructures depend mainly on alloying elements, method of production, mechanical, and thermal treatments. The relationships between these variables and final properties of the alloy are complex, non-linear in nature, which is the biggest hurdle in developing proper correlations between them by conventional methods. So, we developed artificial neural networks (ANN) models for solving these complex phenomena in titanium alloys.

In the present work, ANN models were used for the analysis and prediction of the correlation between the process parameters, the alloying elements, microstructural features, beta transus temperature and mechanical properties in titanium alloys. Sensitivity analysis of trained neural network models were studied which resulted a better understanding of relationships between inputs and outputs. The model predictions and the analysis are well in agreement with the experimental results. The simulation results show that the average output-prediction error by models are less than 5% of the prediction range in more than 95% of the cases, which is quite acceptable for all metallurgical purposes.

Sandwich nanoarchitecture of LiV3O8/graphene multilayer nanomembranes via layer-by-layer self-assembly for long-cycle-life lithium-ion battery cathodes

A lack of suitable high-performance cathode materials has become the major barrier to their applications in future advanced communication equipment and electric vehicle power systems. In this paper, we have developed a layer-by-layer self-assembly approach for fabricating a novel sandwich nanoarchitecture of multilayered LiV₃O₈ nanoparticle/graphene nanosheet (M-nLVO/GN) hybrid electrodes for potential use in high performance lithium ion batteries by using a porous Ni foam as a substrate. The prepared sandwich nanoarchitecture of M-nLVO/GN hybrid electrodes exhibited high performance as a cathode material for lithium-ion batteries, such as high reversible specific capacity (235 mA h g^-1 at a current density of 0.3 A g^-1), high coulombic efficiency (over 98%), fast rate capability (up to a current density of 10 A g^-1), and superior capacity retention during cycling (90% capacity retention with a current density of 0.3 A g^-1 after 300 cycles). Very significantly, this novel insight into the design and synthesis of sandwich nanoarchitecture would extend their application to various electrochemical energy storage devices, such as fuel cells and supercapacitors.

A design strategy of large grain lithium-rich layered oxides for lithium-ion batteries cathode

Li-rich materials are considered the most promising for Li-ion battery cathodes, as high capacity can be achieved. However, poor cycling stability is a critical drawback that leads to poor capacity retention. Here a strategy is used to synthesize a large-grain lithium-rich layered oxides to overcome this difficulty without sacrificing rate capability. This material is designed with micron scale grain with a width of about 300 nm and length of 1-3 μm. This unique structure has a better ability to overcome stress-induced structural collapse caused by Li-ion insertion/extraction and reduce the dissolution of Mn ions, which enable a reversible and stable capacity. As a result, this cathode material delivered a highest discharge capacity of around 308 mAh g^-1 at a current density of 30 mA g^-1 with retention of 88.3% (according to the highest discharge capacity) after 100 cycles, 190 mAh g^-1 at a current density of 300 mA g^-1 and almost no capacity fading after 100 cycles. Therefore, Lithium-rich material of large-grain structure is a promising cathode candidate in Lithium-ion batteries with high capacity and high cycle stability for application. This strategy of large grain may furthermore open the door to synthesize the other complex architectures for various applications.

One-dimensional porous La0.5Sr0.5CoO2.91 nanotubes as a highly efficient electrocatalyst for rechargeable lithium-oxygen batteries

The electrochemical performance of one-dimensional porous La_0.5Sr_0.5CoO_2.91 nanotubes as a cathode catalyst for rechargeable nonaqueous lithium-oxygen (Li-O₂) batteries is reported here for the first time. In this study, one-dimensional porous La_0.5Sr_0.5CoO_2.91 nanotubes were prepared by a simple and efficient electrospinning technique. These materials displayed an initial discharge capacity of 7205 mAh g^-1 with a plateau at around 2.66 V at a current density of 100 mA g^-1. It was found that the La_0.5Sr_0.5CoO_2.91 nanotubes promoted both oxygen reduction and oxygen evolution reactions in alkaline media and a nonaqueous electrolyte, thereby improving the energy and coulombic efficiency of the Li-O₂ batteries. The cyclability was maintained for 85 cycles without any sharp decay under a limited discharge depth of 1000 mAh g^-1, suggesting that such a bifunctional electrocatalyst is a promising candidate for the oxygen electrode in Li-O₂ batteries.

Surface modification of LiV3O8 nanosheets via layer-by-layer self-assembly for high-performance rechargeable lithium batteries

In this work, an economical route based on hydrothermal and layer-by-layer (LBL) self-assembly processes has been developed to synthesize unique Al ₂O₃-modified LiV₃O₈ nanosheets, comprising a core of LiV₃O₈ nanosheets and a thin Al ₂O₃ nanolayer. The thickness of the Al₂O ₃ nanolayer can be tuned by altering the LBL cycles. When evaluated for their lithium-storage properties, the 1 LBL Al₂O ₃-modified LiV₃O₈ nanosheets exhibit a high discharge capacity of 191 mA h g^-1 at 300 mA g^-1 (1C) over 200 cycles and excellent rate capability, demonstrating that enhanced physical and/or chemical properties can be achieved through proper surface modification. © 2014 Elsevier B.V. All rights reserved.

Facile synthesis of nanocrystalline LiFePO4/graphene composite as cathode material for high power lithium ion batteries

We describe a simple strategy, which is based on the idea of space confinement, for the synthesis of carbon coating on LiFePO₄ nanoparticles/graphene nanosheets composites in a water-in-oil emulsion system. The prepared composite displayed high performance as a cathode material for lithium-ion battery, such as high reversible lithium storage capacity (158 mA h g^-1 after 100 cycles), high coulombic efficiency (over 97%), excellent cycling stability and high rate capability (as high as 83 mA h g ^-1 at 60 C). Very significantly, the preparation method employed can be easily adapted and be extended as a general approach to sophisticated compositions and structures for the preparation of highly dispersed nanosized structure on graphene. 

Facile Synthesis of Anatase TiO2 Quantum-Dot/Graphene-Nanosheet Composites with Enhanced Electrochemical Performance for Lithium-Ion Batteries

A facile method to synthesize well-dispersed TiO₂ quantum dots on graphene nanosheets (TiO₂-QDs/GNs) in a water-in-oil (W/O) emulsion system is reported. The TiO₂/graphene composites display high performance as an anode material for lithium-ion batteries (LIBs), such as having high reversible lithium storage capacity, high Coulombic efficiency, excellent cycling stability, and high rate capability. The excellent electrochemical performance and special structure of the composites thus offer a way to prepare novel graphene-based electrode materials for high-energy-density and high-power LIBs. 

An in situ ionic-liquid-assisted synthetic approach to iron fluoride/graphene hybrid nanostructures as superior cathode materials for lithium ion batteries

A tactful ionic-liquid (IL)-assisted approach to in situ synthesis of iron fluoride/graphene nanosheet (GNS) hybrid nanostructures is developed. To ensure uniform dispersion and tight anchoring of the iron fluoride on graphene, we employ an IL which serves not only as a green fluoride source for the crystallization of iron fluoride nanoparticles but also as a dispersant of GNSs. Owing to the electron transfer highways created between the nanoparticles and the GNSs, the iron fluoride/GNS hybrid cathodes exhibit a remarkable improvement in both capacity and rate performance (230 mAh g^-1 at 0.1 C and 74 mAh g^-1 at 40 C). The stable adhesion of iron fluoride nanoparticles on GNSs also introduces a significant improvement in long-term cyclic performance (115 mAh g^-1 after 250 cycles even at 10 C). The superior electrochemical performance of these iron fluoride/GNS hybrids as lithium ion battery cathodes is ascribed to the robust structure of the hybrid and the synergies between iron fluoride nanoparticles and graphene. © 2013 American Chemical Society.