scholarly journals MXenes as Flow Electrodes for Capacitive Deionization of Wastewater

2020 ◽  
Author(s):  
Naqsh E. Mansoor
Keyword(s):  
Transition Metal ◽  
Applied Voltage ◽  
Energy Efficient ◽  
Performance Metrics ◽  
Industrial Applications ◽  
Operating Conditions ◽  
Water Remediation ◽  
Capacitive Deionization ◽  
Ion Removal ◽  
Ionic Impurities

The energy-water nexus poses an integrated research challenge, while opening up an opportunity space for the development of energy efficient technologies for water remediation. Capacitive Deionization (CDI) is an upcoming reclamation technology that uses a small applied voltage applied across electrodes to electrophoretically remove dissolved ionic impurities from wastewater streams. Similar to a supercapacitor, the ions are stored in the electric double layer of the electrodes. Reversing the polarity of applied voltage enables recovery of the removed ionic impurities, allowing for recycling and reuse. Simultaneous materials recovery and water reclamation makes CDI energy efficient and resource conservative, with potential to scale it up for industrial applications. The efficiency of the technology depends on the architectural design of the CDI cell, control of operating conditions, and the nature of the electrodes used. In this project we report on the performance of Ti3C2Tx MXenes flow electrodes in a CDI cell design. MXenes are a novel class of two-dimensional (2D) transition metal carbides, nitrides and carbonitrides with the general formula Mn+1XnTx where M is an early transition metal, X is carbon and/or nitrogen, Tx represents the surface terminations. Ti3C2Tx MXenes synthesized at Boise State, were employed as a flow electrode solution in an established CDI cell for targeted and selective ion removal. Performance metrics of achieved adsorption capacity, ion removal efficiency, regeneration efficiency, energy consumption, and charge efficiency, exceed those of currently prevalent electrode systems. In addition, rheological properties of the Ti3C2Tx MXenes colloidal solution were evaluated. This work establishes the deionization performance of Ti3C2Tx MXene based flow electrodes while providing further insight towards understanding the effect of structure and surface functionalization on the resultant deionization efficiency.

Electron energy loss near edge structures of intermetallic alloys and grain boundaries in NiAl

1996 ◽  
Vol 54 ◽  
pp. 522-523
Author(s):  
G.A. Botton ◽  
C.J. Humphreys
Keyword(s):  
High Temperature ◽  
Transition Metal ◽  
Energy Loss ◽  
Grain Boundaries ◽  
Industrial Applications ◽  
Edge Structure ◽  
Structural Applications ◽  
Yield Behaviour ◽  
Late Transition ◽  
Metal Aluminides

Transition metal aluminides are of great potential interest for high temperature structural applications. Although these materials exhibit good mechanical properties at high temperature, their use in industrial applications is often limited by their intrinsic room temperature brittleness. Whilst this particular yield behaviour is directly related to the defect structure, the properties of the defects (in particular the mobility of dislocations and the slip system on which these dislocations move) are ultimately determined by the electronic structure and bonding in these materials. The lack of ductility has been attributed, at least in part, to the mixed bonding character (metallic and covalent) as inferred from ab-initio calculations. In this work, we analyse energy loss spectra and discuss the features of the near edge structure in terms of the relevant electronic states in order to compare the predictions on bonding directly with spectroscopic experiments. In this process, we compare spectra of late transition metal (TM) to early TM aluminides (FeAl and TiAl) to assess whether differences in bonding can also be detected. This information is then discussed in terms of bonding changes at grain boundaries in NiAl.

scholarly journals Simplified Prediction of Ion Removal in Capacitive Deionization of Multi-Ion Solutions

Langmuir ◽  
2020 ◽  
Vol 36 (5) ◽  
pp. 1338-1344 ◽  
Author(s):  
Johan Nordstrand ◽  
Joydeep Dutta
Keyword(s):  
Capacitive Deionization ◽  
Ion Removal

scholarly journals Opportunistic Large Array Propagation Models: A Comprehensive Survey

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4206
Author(s):  
Farhan Nawaz ◽  
Hemant Kumar ◽  
Syed Ali Hassan ◽  
Haejoon Jung
Keyword(s):  
Energy Efficient ◽  
Large Scale ◽  
Performance Metrics ◽  
Experimental Studies ◽  
Cooperative Transmission ◽  
Analytical Models ◽  
Future Research ◽  
Large Array ◽  
Propagation Models ◽  
Comprehensive Survey

Enabled by the fifth-generation (5G) and beyond 5G communications, large-scale deployments of Internet-of-Things (IoT) networks are expected in various application fields to handle massive machine-type communication (mMTC) services. Device-to-device (D2D) communications can be an effective solution in massive IoT networks to overcome the inherent hardware limitations of small devices. In such D2D scenarios, given that a receiver can benefit from the signal-to-noise-ratio (SNR) advantage through diversity and array gains, cooperative transmission (CT) can be employed, so that multiple IoT nodes can create a virtual antenna array. In particular, Opportunistic Large Array (OLA), which is one type of CT technique, is known to provide fast, energy-efficient, and reliable broadcasting and unicasting without prior coordination, which can be exploited in future mMTC applications. However, OLA-based protocol design and operation are subject to network models to characterize the propagation behavior and evaluate the performance. Further, it has been shown through some experimental studies that the most widely-used model in prior studies on OLA is not accurate for networks with networks with low node density. Therefore, stochastic models using quasi-stationary Markov chain are introduced, which are more complex but more exact to estimate the key performance metrics of the OLA transmissions in practice. Considering the fact that such propagation models should be selected carefully depending on system parameters such as network topology and channel environments, we provide a comprehensive survey on the analytical models and framework of the OLA propagation in the literature, which is not available in the existing survey papers on OLA protocols. In addition, we introduce energy-efficient OLA techniques, which are of paramount importance in energy-limited IoT networks. Furthermore, we discuss future research directions to combine OLA with emerging technologies.

scholarly journals STOCHASTIC CARBON EMISSION ESTIMATION METHOD FOR CONSTRUCTION OPERATION

2016 ◽  
Vol 23 (1) ◽  
pp. 137-149 ◽  
Author(s):  
Chang-Yong YI ◽  
Han-Seong GWAK ◽  
Dong-Eun LEE
Keyword(s):  
Carbon Emission ◽  
Performance Metrics ◽  
Ghg Emissions ◽  
Estimation Method ◽  
Operating Conditions ◽  
Analysis Tool ◽  
Micro Scale ◽  
Work Tasks ◽  
Emission Estimation ◽  
Construction Operation

Low carbon construction is an important operation management goal because greenhouse gas (GHG) reduc­tion has become a global concern. Major construction resources that contribute GHG, such as equipment and labour, are being targeted to achieve this goal. The GHG emissions produced by the resources vary with their operating conditions. It is commendable to provide a statistical GHG emission estimation method that models the transitory nature of resource states at micro-scale of construction operations. This paper proposes a computational method called Stochastic Carbon Emission Estimation (SCE2) that measures the variability of GHG emissions. It creates construction operation models consisting of atomic work tasks, utilizes hourly equipment fuel consumption and hourly labourer respiratory rates that change according to their operating conditions classified into five categories, and identifies an optimal resource combi­nation by trading off eco-economic performance metrics such as the amount of GHG emissions, operation completion time, operation completion cost, and productivity. The study is of value to researchers because SCE2 fill in a gap to eco-economic operation modelling and analysis tool which considers operating conditions at micro-scale of construction operation having many stochastic work tasks. This study is also relevance to practitioners because it allows project man­agers to achieve eco-economic goals while honouring predefined constraints associated with time and cost.

Identification of Bearing Coefficients of Flexible Rotor-Bearing Systems

2000 ◽  
Author(s):  
Tachung Yang ◽  
Wei-Ching Chaung
Keyword(s):  
Industrial Applications ◽  
Operating Conditions ◽  
Least Square ◽  
Flexible Rotor ◽  
Fem Modeling ◽  
Identification Method ◽  
Reaction Forces ◽  
Manufacturing Assembly ◽  
Stiffness And Damping

The accuracy of stiffness and damping coefficients of bearings is critical for the rotordynamic analysis of rotating machinery. However, the influence of bearings depends on the design, manufacturing, assembly, and operating conditions of the bearings. Uncertainties occur quite often in manufacturing and assembly, which causes the inaccuracy of bearing predictions. An accurate and reliable in-situ identification method for the bearing coefficients is valuable to both analyses and industrial applications. The identification method developed in this research used the receptance matrices of flexible shafts from FEM modeling and the unbalance forces of trial masses to derive the displacements and reaction forces at bearing locations. Eight bearing coefficients are identified through a Total Least Square (TLS) procedure, which can handle noise effectively. A special feature of this method is that it can identify bearing coefficients at a specific operating speed, which make it suitable for the measurement of speed-dependent bearings, like hydrodynamic bearings. Numerical validation of this method is presented. The configurations of unbalance mass arrangements are discussed.

Development of an End-Effector for Mitigation of Collisions

2021 ◽  
Author(s):  
Domenico Tommasino ◽  
Matteo Bottin ◽  
Giulio Cipriani ◽  
Alberto Doria ◽  
Giulio Rosati
Keyword(s):  
Numerical Simulations ◽  
Industrial Applications ◽  
Operating Conditions ◽  
Contact Forces ◽  
Design Parameters ◽  
End Effector ◽  
Linear Behavior ◽  
Stable Mechanism ◽  
Robot Tasks ◽  
The Impact

Abstract In robotics the risk of collisions is present both in industrial applications and in remote handling. If a collision occurs, the impact may damage both the robot and external equipment, which may result in successive imprecise robot tasks or line stops, reducing robot efficiency. As a result, appropriate collision avoidance algorithms should be used or, if it is not possible, the robot must be able to react to impacts reducing the contact forces. For this purpose, this paper focuses on the development of a special end-effector that can withstand impacts and is able to protect the robot from impulsive forces. The novel end-effector is based on a bi-stable mechanism that decouples the dynamics of the end-effector from the dynamics of the robot. The intrinsically non-linear behavior of the end-effector is investigated with the aid of numerical simulations. The effect of design parameters and the operating conditions are analyzed and the interaction between the functioning of the bi-stable mechanism and the control system is studied. In particular, the effect of the mechanism in different scenarios characterized by different robot velocities is shown. Results of numerical simulations assess the validity of the proposed end-effector, which can lead to large reductions in impact forces.

A Starved Mixed Elastohydrodynamic Lubrication Model for the Prediction of Lubrication Performance, Friction and Flash Temperature With Arbitrary Entrainment Angle

2017 ◽  
Vol 140 (3) ◽  
Author(s):  
Wei Pu ◽  
Dong Zhu ◽  
Jiaxu Wang
Keyword(s):  
Surface Roughness ◽  
Film Thickness ◽  
Elastohydrodynamic Lubrication ◽  
Industrial Applications ◽  
Operating Conditions ◽  
Flash Temperature ◽  
Machined Surface ◽  
Lubrication Performance ◽  
Wide Range ◽  
Starved Lubrication

In this study, a modified mixed lubrication model is developed with consideration of machined surface roughness, arbitrary entraining velocity angle, starvation, and cavitation. Model validation is executed by means of comparison between the obtained numerical results and the available starved elastohydrodynamic lubrication (EHL) data found from some previous studies. A comprehensive analysis for the effect of inlet oil supply condition on starvation and cavitation, mixed EHL characteristics, friction and flash temperature in elliptical contacts is conducted in a wide range of operating conditions. In addition, the influence of roughness orientation on film thickness and friction is discussed under different starved lubrication conditions. Obtained results reveal that inlet starvation leads to an obvious reduction of average film thickness and an increase in interasperity cavitation area due to surface roughness, which results in significant increment of asperity contacts, friction, and flash temperature. Besides, the effect of entrainment angle on film thickness will be weakened if the two surfaces operate under starved lubrication condition. Furthermore, the results show that the transverse roughness may yield thicker EHL films and lower friction than the isotropic and longitudinal if starvation is taken into account. Therefore, the starved mixed EHL model can be considered as a useful engineering tool for industrial applications.

scholarly journals Design and Analysis of High-Efficient Driver Model for LED Luminaires

2021 ◽  
pp. 96-106
Author(s):  
Onur Akalp ◽  
Harun Ozbay ◽  
Serhat Berat Efe
Keyword(s):  
Energy Efficient ◽  
Supply System ◽  
Operating Conditions ◽  
Driver Model ◽  
Zero Voltage Switching ◽  
Proposed Model ◽  
High Efficient ◽  
Driver Circuit ◽  
Low Volume ◽  
Zero Voltage

LED luminaires need a driver circuit for working properly. Most of the drivers have disadvantages such as losses during operation. This issue becomes more important while supplying with limited sources such as renewables. To overcome the problem, this study proposes a novel energy efficient driver for LED luminaires based on zero voltage switching (ZVS) single-ended primary inductance converter (SEPIC) technology. Driver and hence luminaires were designed to be fed from photovoltaic (PV) panels. In addition, an adaptive MPPT algorithm was developed to obtain optimum efficiency from supply system. SEPIC approach was preferred for MPPT application due to its advantages such as non-reversing polarity. This feature allows energy efficiency in corporation with ZVS. Proposed model was designed under PSIM platform with all components; PV panels, ZVS, SEPIC, and LED luminaires. A detailed analysis was performed by using system graphs under various operating conditions as different irradiance levels. Results show that proposed model is energy efficient and modular because of its low-volume structure. Therefore the model can lead smaller driver circuits with minimum losses.

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