Search results for: metal deep eutectic solvents
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4700

Search results for: metal deep eutectic solvents

4430 Isotopic Evidence (He, Ne, Ar) for Deep Fluid in the Caucasus Continental Collision Zone

Authors: Larisa Liamina, Vasily Lavrushin, Salvatore Inguaggiato

Abstract:

This study presents and summarizes the results of researching the isotopic signature of helium in the deep fluid eastern part of the Southern slope of the Greater Caucasus and the Lesser Caucasus (Azerbaijan and Armenia) for the period from 2010 to 2016. The results of isotope ratios of 3He/4He in 59 samples of the gas phase of geothermal fluids and mud volcanoes are presented. New data have been obtained not only on the isotopic ratios of helium, but also neon and argon. The R/Ra ratio was analyzed along the Ankara-Sevan ophiolite structure. The patterns of lateral variations of the 3He/4He ratio of different geological structural elements of the studied region are revealed.

Keywords: isotopes helium, deep fluids, tectonic structures, Caucasus

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4429 Non-Destructive Testing of Metal Pipes with Ultrasonic Sensors Based on Determination of Maximum Ultrasonic Frequency

Authors: Herlina Abdul Rahim, Javad Abbaszadeh, Ruzairi Abdul Rahim

Abstract:

In this research, the non-invasive ultrasonic transmission tomography is investigated. In order to model the ultrasonic wave scattering for different thickness of metal pipes, two-dimensional (2D) finite element modeling (FEM) has been utilized. The wall thickness variation of the metal pipe and its influence on propagation of the ultrasonic pressure wave are explored in this paper, includes frequency analysing in order to find the maximum applicable frequency. The simulation results have been compared to experimental data and are shown to provide key insight for this well-defined experimental case by explaining the achieved reconstructed images from experimental setup. Finally, the experimental results which are useful for further investigation for the application of ultrasonic transmission tomography in industry are illustrated.

Keywords: ultrasonic transmission tomography, ultrasonic sensors, ultrasonic wave, non-invasive tomography, metal pipe

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4428 Development of Swing Valve for Gasoline Turbocharger Using Hybrid Metal Injection Molding

Authors: B. S. So, Y. H. Yoon, J. O. Jung, K. S. Bae

Abstract:

Metal Injection Molding (MIM) is a technology that combines powder metallurgy and injection molding. Particularly, it is widely applied to the manufacture of precision mobile parts and automobile turbocharger parts because compact precision parts with complicated three-dimensional shapes that are difficult to machining are formed into a large number of finished products. The swing valve is a valve that adjusts the boost pressure of the turbocharger. Since the head portion is exposed to the harsh temperature condition of about 900 degrees in the gasoline GDI engine, it is necessary to use Inconel material with excellent heat resistance and abrasion resistance, resulting in high manufacturing cost. In this study, we developed a swing valve using a metal powder injection molding based hybrid material (Inconel 713C material with heat resistance is applied to the head part, and HK30 material with low price is applied to the rest of the body part). For this purpose, the process conditions of the metal injection molding were optimized to minimize the internal defects, and the effectiveness was confirmed by the fracture strength and fatigue test.

Keywords: hybrid metal injection molding, swing valve, turbocharger, double injection

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4427 AI-based Radio Resource and Transmission Opportunity Allocation for 5G-V2X HetNets: NR and NR-U Networks

Authors: Farshad Zeinali, Sajedeh Norouzi, Nader Mokari, Eduard Jorswieck

Abstract:

The capacity of fifth-generation (5G) vehicle-to-everything (V2X) networks poses significant challenges. To ad- dress this challenge, this paper utilizes New Radio (NR) and New Radio Unlicensed (NR-U) networks to develop a heterogeneous vehicular network (HetNet). We propose a new framework, named joint BS assignment and resource allocation (JBSRA) for mobile V2X users and also consider coexistence schemes based on flexible duty cycle (DC) mechanism for unlicensed bands. Our objective is to maximize the average throughput of vehicles while guaranteeing the WiFi users' throughput. In simulations based on deep reinforcement learning (DRL) algorithms such as deep deterministic policy gradient (DDPG) and deep Q network (DQN), our proposed framework outperforms existing solutions that rely on fixed DC or schemes without consideration of unlicensed bands.

Keywords: vehicle-to-everything (V2X), resource allocation, BS assignment, new radio (NR), new radio unlicensed (NR-U), coexistence NR-U and WiFi, deep deterministic policy gradient (DDPG), deep Q-network (DQN), joint BS assignment and resource allocation (JBSRA), duty cycle mechanism

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4426 In vitro Determination of Carbonic Anhydrase Inhibition of the Flowers of Vanda Orchid, Vanda Tessellata Roxb. (1795) by Modified Colorimetric Maren T.H. (1960) Method

Authors: John Carlo Combista, Jimbert Tan

Abstract:

The orchid, Vanda tessellata was chosen by the researchers because of the presence of the constituents in the family Orchidaceae such as alkaloids, flavonoids and glycosides that might give an inhibition activity of the carbonic anhydrase enzyme. This study aimed to determine the in vitro inhibition of carbonic anhydrase of Vanda tessellata flower extract. With the use of modified colorimetric Maren T.H. (1960) method, the time in seconds each test solution changed its color after the rate of CO2 hydration were recorded. Two solvents were used: the semi-polar, 95% ethanol and the non-polar, dichloromethane solvents. The percent inhibition activity of carbonic anhydrase of the different concentrations of solvents ethanol (1%, 25% and 50%) and dichloromethane (1% and 10%) test solutions were determined. Results showed that the ethanol-based extract of Vanda tessellata in different concentrations showed an inhibitory effect while the dichloromethane-based extract of Vanda tessellata showed no inhibitory effect of carbonic anhydrase activity. For ethanol extract, the concentration with the highest activity was 50% followed by 25% which changed its color from red to yellow with an average time of 13.11 seconds and 11.57 seconds but 1% with an average time of 7.56 seconds did not exhibit an effect. The researchers recommend the isolation of the specific active constituents of Vanda tessellata that is responsible for the inhibitory effect of carbonic anhydrase enzyme. It is also recommended to utilize different blood types to observe different reactions to the inhibition of the carbonic anhydrase.

Keywords: carbonic anhydrase, inhibition, modified colorimetric Maren TH method, Vanda orchid

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4425 Investigation of the Heavy Metal Pollution of the River Ecosystems in the Lake Sevan Basin, Armenia

Authors: G. Gevorgyan, S. Khudaverdyan, A. Vaseashta

Abstract:

The Lake Sevan basin is situated in the eastern part of the Republic of Armenia (Gegharquniq marz/district). The heavy metal pollution of the some tributaries of Lake Sevan was investigated. Water sampling was performed in August and December, 2014 from the 4 observation sites: 1) Sotq river upstream (about 600 meters upstream from the Sotq gold mine); 2) Sotq river mouth; 3) Masrik river mouth; 4) Dzknaget river mouth. Heavy metal (V, Fe, Ni, Cu, As, Mo, Pb) concentrations in the water samples were determined by the standard methods using an atomic absorption spectrophotometer. The results of the study showed that heavy metal content mainly increased from the upstream of the Sotq river to the mouth of the Masrik river which may have been conditioned by the influence of gold mining activity as the Masrik and its tributary-Sotq rivers passing through the gold mining area were exposed to heavy metal pollution. The observation sites can be ranked by pollution degree as follows: №3> №2> №1> №4. The highest heavy metal pollution degree was observed in the Masrik river mouth which may have been conditioned by the direct impact of gold mining activity and the pressure of its tributary–the Sotq river which flows through the gold mining area. The lowest heavy metal pollution degree was registered in the Dzknaget river mouth which flowing through rural areas wasn’t subject to significant heavy metal pollution. According to the observation sites of the Sotq and Masrik rivers, high positive correlation was mainly observed between the concentrations of the investigated heavy metals (except nickel) which indicated that all the heavy metals except the nickel had the same anthropogenic pollution source which was the activity of the Sotq gold mine. In general, it is possible to state that the activity of the Sotq gold mine in the Lake Sevan basin caused the heavy metal pollution of the Sotq and Masrik rivers which may have posed environmental hazards. Heavy metals are nondegradable substances, and heavy metal pollution of freshwater systems may pose risks to the environment and human health through accumulation in the tissues of aquatic organisms, water-food chain as well as oral ingestion and dermal contact.

Keywords: Armenia, Lake Sevan basin, gold mining activity, river ecosystems, heavy metal pollution

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4424 The Effect of Austempering Temperature on Anisotropy of TRIP Steel

Authors: Abdolreza Heidari Noosh Abad, Amir Abedi, Davood Mirahmadi khaki

Abstract:

The high strength and flexibility of TRIP steels are the major reasons for them being widely used in the automobile industry. Deep drawing is regarded as a common metal sheet manufacturing process is used extensively in the modern industry, particularly automobile industry. To investigate the potential of deep drawing characteristic of materials, steel sheet anisotropy is studied and expressed as R-Value. The TRIP steels have a multi-phase microstructure consisting typically of ferrite, bainite and retained austenite. The retained austenite appears to be the most effective phase in the microstructure of the TRIP steels. In the present research, Taguchi method has been employed to study investigates the effect of austempering temperature parameters on the anisotropy property of the TRIP steel. To achieve this purpose, a steel with chemical composition of 0.196C -1.42Si-1.41Mn, has been used and annealed at 810oC, and then austempered at 340-460oC for 3, 6, and 9 minutes. The results shows that the austempering temperature has a direct relationship with R-value, respectively. With increasing austempering temperature, residual austenite grain size increases as well as increased solubility, which increases the amount of R-value. According to the results of the Taguchi method, austempering temperature’s p-value less than 0.05 is due to effective on R-value.

Keywords: Taguchi method, hot rolling, thermomechanical process, anisotropy, R-value

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4423 Deep Learning Based-Object-classes Semantic Classification of Arabic Texts

Authors: Imen Elleuch, Wael Ouarda, Gargouri Bilel

Abstract:

We proposes in this paper a Deep Learning based approach to classify text in order to enrich an Arabic ontology based on the objects classes of Gaston Gross. Those object classes are defined by taking into account the syntactic and semantic features of the treated language. Thus, our proposed approach is a hybrid one. In fact, it is based on the one hand on the object classes that represents a knowledge based-approach on classification of text and in the other hand it uses the deep learning approach that use the word embedding-based-approach to classify text. We have applied our proposed approach on a corpus constructed from an Arabic dictionary. The obtained semantic classification of text will enrich the Arabic objects classes ontology. In fact, new classes can be added to the ontology or an expansion of the features that characterizes each object class can be updated. The obtained results are compared to a similar work that treats the same object with a classical linguistic approach for the semantic classification of text. This comparison highlight our hybrid proposed approach that can be ameliorated by broaden the dataset used in the deep learning process.

Keywords: deep-learning approach, object-classes, semantic classification, Arabic

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4422 Optimization of Synergism Extraction of Toxic Metals (Lead, Copper) from Chlorides Solutions with Mixture of Cationic and Solvating Extractants

Authors: F. Hassaine-Sadi, S. Chelouaou

Abstract:

In recent years, environmental contamination by toxic metals such as Pb, Cu, Ni, Zn ... has become a worldwide crucial problem, particularly in some areas where the population depends on groundwater for drinking daily consumption. Thus, the sources of metal ions come from the metal manufacturing industry, fertilizers, batteries, paints, pigments and so on. Solvent extraction of metal ions has given an important role in the development of metal purification processes such as the synergistic extraction of some divalent cations metals ( M²⁺), the ions metals from various sources. This work consists of a water purification technique that involves the lead and copper systems: Pb²⁺, H₃O+, Cl⁻ and Cu²⁺, H₃O⁺, Cl⁻ for diluted solutions by a mixture of tri-n-octylphosphine oxide (TOPO) or Tri-n-butylphosphate(TBP) and di (2-ethyl hexyl) phosphoric acid (HDEHP) dissolved in kerosene. The study of the fundamental parameters influencing the extraction synergism: cation exchange/extraction solvent have been examined.

Keywords: synergistic extraction, lead, copper, environment

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4421 Synthesis and Characterization of Some Nano-Structured Metal Hexacyanoferrates Using Sapindus mukorossi, a Natural Surfactant

Authors: Uma Shanker, Vidhisha Jassal

Abstract:

A novel green route was used to synthesize few metal hexacyanoferrates (FeHCF, NiHCF, CoHCF and CuHCF) nanoparticles using Sapindus mukorossias a natural surfactant and water as a solvent. The synthesized nanoparticles were characterized by Powder X-ray diffraction (PXRD), Scanning electron microscopy (SEM), Transmission electron microscopy (TEM), Fourier Transform Infrared Spectroscopy (FTIR) and Thermo gravimetric techniques. Trasmission electron microscopic images showed that synthesized MHCF nanoparticles exhibited cubic and spherical shapes with exceptionally small sizes ranging from 3nm - 186 nm.

Keywords: metal hexacyanoferrates, natural surfactant, Sapindus mukorossias, nanoparticles

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4420 A Brief Review of Titanium Powders Used in Laser Powder-Bed Fusion Additive Manufacturing

Authors: Ali Alhajeri, Tarig Makki, Mosa Almutahhar, Mohammed Ahmed, Usman Ali

Abstract:

Metal powder is the raw material used for laser powder-bed fusion (LPBF) additive manufacturing (AM). There are many metal materials that can be used in LPBF. The properties of these materials are varied between each other, which can affect the building part. The objective of this paper is to do an overview of the titanium powders available in LBPF. Comparison between different literature works will lead us to study the similarities and differences between the powder properties such as size, shape, and chemical composition. Furthermore, the results of this paper will point out the significant titanium powder properties in order to clearly illustrate their effect on the build parts.

Keywords: LPBF, titanium, Ti-6Al-4V, Ti-5553, metal powder, AM

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4419 A Case Study of Deep Learning for Disease Detection in Crops

Authors: Felipe A. Guth, Shane Ward, Kevin McDonnell

Abstract:

In the precision agriculture area, one of the main tasks is the automated detection of diseases in crops. Machine Learning algorithms have been studied in recent decades for such tasks in view of their potential for improving economic outcomes that automated disease detection may attain over crop fields. The latest generation of deep learning convolution neural networks has presented significant results in the area of image classification. In this way, this work has tested the implementation of an architecture of deep learning convolution neural network for the detection of diseases in different types of crops. A data augmentation strategy was used to meet the requirements of the algorithm implemented with a deep learning framework. Two test scenarios were deployed. The first scenario implemented a neural network under images extracted from a controlled environment while the second one took images both from the field and the controlled environment. The results evaluated the generalisation capacity of the neural networks in relation to the two types of images presented. Results yielded a general classification accuracy of 59% in scenario 1 and 96% in scenario 2.

Keywords: convolutional neural networks, deep learning, disease detection, precision agriculture

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4418 Evaluation of Deformation for Deep Excavations in the Greater Vancouver Area Through Case Studies

Authors: Boris Kolev, Matt Kokan, Mohammad Deriszadeh, Farshid Bateni

Abstract:

Due to the increasing demand for real estate and the need for efficient land utilization in Greater Vancouver, developers have been increasingly considering the construction of high-rise structures with multiple below-grade parking. The temporary excavations required to allow for the construction of underground levels have recently reached up to 40 meters in depth. One of the challenges with deep excavations is the prediction of wall displacements and ground settlements due to their effect on the integrity of City utilities, infrastructure, and adjacent buildings. A large database of survey monitoring data has been collected for deep excavations in various soil conditions and shoring systems. The majority of the data collected is for tie-back anchors and shotcrete lagging systems. The data were categorized, analyzed and the results were evaluated to find a relationship between the most dominant parameters controlling the displacement, such as depth of excavation, soil properties, and the tie-back anchor loading and arrangement. For a select number of deep excavations, finite element modeling was considered for analyses. The lateral displacements from the simulation results were compared to the recorded survey monitoring data. The study concludes with a discussion and comparison of the available empirical and numerical modeling methodologies for evaluating lateral displacements in deep excavations.

Keywords: deep excavations, lateral displacements, numerical modeling, shoring walls, tieback anchors

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4417 Expression of Metallothionein Gen and Protein on Hepatopancreas, Gill and Muscle of Perna viridis Caused by Biotoxicity Hg, Pb and Cd

Authors: Yulia Irnidayanti , J. J. Josua, A. Sugianto

Abstract:

Jakarta Bay with 13 rivers that flow into, the environment has deteriorated and is the most polluted bays in Asia. The entry of waste into the waters of the Bay of Jakarta has caused pollution. Heavy metal contamination has led to pollution levels and may cause toxicity to organisms that live in the sea, down to the cellular level and may affect the ecological balance. Various ways have been conducted to measure the impact of environmental degradation, such as by measuring the levels of contaminants in the environment, including measuring the accumulation of toxic compounds in the tissues of organisms. Biological responses or biomarkers known as a sensitive indicator but need relevant predictions. In heavy metal pollution monitoring, analysis of aquatic biota is very important from the analysis of the water itself. The content of metals in aquatic biota will usually always be increased from time to time due to the nature of metal bioaccumulation, so the aquatic biota is best used as an indicator of metal pollution in aquatic environments. The results of the content analysis results of sea water in coastal estuaries Angke, Kaliadem and Panimbang detected heavy metals cadmium, mercury, lead, but did not find zinc metal. Based on the results of protein electrophoresis methallotionein found heavy metals in the tissues hepatopancreas, gills and muscles, and also the mRNA expression of has detected.

Keywords: gills, heavy metal, hepatopancreas, metallothionein, muscle

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4416 Market Index Trend Prediction using Deep Learning and Risk Analysis

Authors: Shervin Alaei, Reza Moradi

Abstract:

Trading in financial markets is subject to risks due to their high volatilities. Here, using an LSTM neural network, and by doing some risk-based feature engineering tasks, we developed a method that can accurately predict trends of the Tehran stock exchange market index from a few days ago. Our test results have shown that the proposed method with an average prediction accuracy of more than 94% is superior to the other common machine learning algorithms. To the best of our knowledge, this is the first work incorporating deep learning and risk factors to accurately predict market trends.

Keywords: deep learning, LSTM, trend prediction, risk management, artificial neural networks

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4415 Absorption Kinetic and Tensile Mechanical Properties of Swollen Elastomer/Carbon Black Nanocomposites using Typical Solvents

Authors: F. Elhaouzi, H. Lahlali, M. Zaghrioui, I. El Aboudi A. BelfKira, A. Mdarhri

Abstract:

The effect of physico chemical properties of solvents on the transport process and mechanical properties in elastomeric nano composite materials is reported. The investigated samples are formed by a semi-crystalline ethylene-co-butyl acrylate polymer filled with hard spherical carbon black (CB) nano particles. The swelling behavior was studied by immersion the dried samples in selected solvents at room temperature during 2 days. For this purpose, two chemical compounds methyl derivatives of aromatic hydrocarbons of benzene, i.e. toluene and xylene, are used to search for the mass and molar volume dependence on the absorption kinetics. Mass gain relative to the mass of dry material at specific times was recorded to probe the absorption kinetics. The transport of solvent molecules in these filled elastomeric composites is following a Fickian diffusion mechanism. Additionally, the swelling ratio and diffusivity coefficient deduced from the Fickian law are found to decrease with the CB concentration. These results indicate that the CB nano particles increase the effective path length for diffusion and consequently limit the absorption of the solvent by occupation free volumes in the material. According to physico chemical properties of the two used solvents, it is found that the diffusion is more important for the toluene molecules solvent due to their low values of the molecular weight and volume molar compared to those for the xylene. Differential Scanning Calorimetry (DSC) and X-ray photo electron (XPS) were also used to probe the eventual change in the chemical composition for the swollen samples. Mechanically speaking, the stress-strain curves of uniaxial tensile tests pre- and post- swelling highlight a remarkably decrease of the strength and elongation at break of the swollen samples. This behavior can be attributed to the decrease of the load transfer density between the matrix and the CB in the presence of the solvent. We believe that the results reported in this experimental investigation can be useful for some demanding applications e.g. tires, sealing rubber.

Keywords: nanocomposite, absorption kinetics, mechanical behavior, diffusion, modelling, XPS, DSC

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4414 Negative Pressures of Ca. -20 MPA for Water Enclosed into a Metal Berthelot Tube under a Vacuum Condition

Authors: K. Hiro, Y. Imai, M. Tanji, H. Deguchi, K. Hatari

Abstract:

Negative pressures of liquids have been expected to contribute many kinds of technology. Nevertheless, experiments for subjecting liquids which have not too small volumes to negative pressures are difficult even now. The reason of the difficulties is because the liquids tend to generate cavities easily. In order to remove cavitation nuclei, an apparatus for enclosing water into a metal Berthelot tube under vacuum conditions was developed. By using the apparatus, negative pressures for water rose to ca. -20 MPa. This is the highest value for water in metal Berthelot tubes. Results were explained by a traditional crevice model. Keywords

Keywords: Berthelot method, negative pressure, cavitation nuclei, water

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4413 Deep Learning to Enhance Mathematics Education for Secondary Students in Sri Lanka

Authors: Selvavinayagan Babiharan

Abstract:

This research aims to develop a deep learning platform to enhance mathematics education for secondary students in Sri Lanka. The platform will be designed to incorporate interactive and user-friendly features to engage students in active learning and promote their mathematical skills. The proposed platform will be developed using TensorFlow and Keras, two widely used deep learning frameworks. The system will be trained on a large dataset of math problems, which will be collected from Sri Lankan school curricula. The results of this research will contribute to the improvement of mathematics education in Sri Lanka and provide a valuable tool for teachers to enhance the learning experience of their students.

Keywords: information technology, education, machine learning, mathematics

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4412 Layer by Layer Coating of Zinc Oxide/Metal Organic Framework Nanocomposite on Ceramic Support for Solvent/Solvent Separation Using Pervaporation Method

Authors: S. A. A. Nabeela Nasreen, S. Sundarrajan, S. A. Syed Nizar, Seeram Ramakrishna

Abstract:

Metal-organic frameworks (MOFs) have attracted considerable interest due to its diverse pore size tunability, fascinating topologies and extensive uses in fields such as catalysis, membrane separation, chemical sensing, etc. Zeolitic imidazolate frameworks (ZIFs) are a class of MOF with porous crystals containing extended three-dimensional structures of tetrahedral metal ions (e.g., Zn) bridged by Imidazolate (Im). Selected ZIFs are used to separate solvent/solvent mixtures. A layer by layer formation of the nanocomposite of Zinc oxide (ZnO) and ZIF on a ceramic support using a solvothermal method was engaged and tested for target solvent/solvent separation. Metal oxide layer was characterized by XRD, SEM, and TEM to confirm the smooth and continuous coating for the separation process. The chemical composition of ZIF films was studied by using X-Ray absorption near-edge structure (XANES) spectroscopy. The obtained ceramic tube with metal oxide and ZIF layer coating were tested for its packing density, thickness, distribution of seed layers and variation of permeation rate of solvent mixture (isopropyl alcohol (IPA)/methyl isobutyl ketone (MIBK). Pervaporation technique was used for the separation to achieve a high permeation rate with separation ratio of > 99.5% of the solvent mixture.

Keywords: metal oxide, membrane, pervaporation, solvothermal, ZIF

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4411 Corrosion Characterization of Al6061 Hybrid Metal Matrix Composites in Acid Medium

Authors: P. V. Krupakara

Abstract:

This paper deals with the high corrosion resistance developed by the hybrid metal matrix composites when compared with that of matrix alloy. Matrix selected is Al6061. Reinforcements selected are graphite and red mud particulates. The composites are prepared using liquid melt metallurgy technique using vortex method. Metal matrix composites containing 2 percent graphite and 2 percent red mud, 2 percent graphite and 4 percent red mud, 2 percent graphite and 6 percent of red mud are prepared. Bar castings are cut into cylindrical discs of 20mm diameter and 20mm thickness. Corrosion tests were conducted at room temperature (230 °C) using conventional weight loss method according to ASTM G69-80. The corrodents used for the test were hydrochloric acid solution of different concentrations. Specimens were tested for every 24 hours interval up to 96 hours. Four specimens for each condition and time were immersed in corrodent. In each case the corrosion rate decreases with increase in exposure time for matrix and metal matrix composites whatever may be the concentration of hydrochloric acid. This may be due to aluminium, which may induce passivation due to development of non-porous layer. As red mud content increases the composites become corrosion resistant due to insulating nature of ceramic material red mud and less exposure of matrix alloy in those metal matrix composites.

Keywords: Al6061, graphite, passivation, red mud, vortex

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4410 Advanced Lithium Recovery from Brine: 2D-Based Ion Selectivity Membranes

Authors: Nour S. Abdelrahman, Seunghyun Hong, Hassan A. Arafat, Daniel Choi, Faisal Al Marzooqi

Abstract:

Abstract—The advancement of lithium extraction methods from water sources, particularly saltwater brine, is gaining prominence in the lithium recovery industry due to its cost-effectiveness. Traditional techniques like recrystallization, chemical precipitation, and solvent extraction for metal recovery from seawater or brine are energy-intensive and exhibit low efficiency. Moreover, the extensive use of organic solvents poses environmental concerns. As a result, there's a growing demand for environmentally friendly lithium recovery methods. Membrane-based separation technology has emerged as a promising alternative, offering high energy efficiency and ease of continuous operation. In our study, we explored the potential of lithium-selective sieve channels constructed from layers of 2D graphene oxide and MXene (transition metal carbides and nitrides), integrated with surface – SO₃₋ groups. The arrangement of these 2D sheets creates interplanar spacing ranging from 0.3 to 0.8 nm, which forms a barrier against multivalent ions while facilitating lithium-ion movement through nano capillaries. The introduction of the sulfonate group provides an effective pathway for Li⁺ ions, with a calculated binding energy of Li⁺ – SO³⁻ at – 0.77 eV, the lowest among monovalent species. These modified membranes demonstrated remarkably rapid transport of Li⁺ ions, efficiently distinguishing them from other monovalent and divalent species. This selectivity is achieved through a combination of size exclusion and varying binding affinities. The graphene oxide channels in these membranes showed exceptional inter-cation selectivity, with a Li⁺/Mg²⁺ selectivity ratio exceeding 104, surpassing commercial membranes. Additionally, these membranes achieved over 94% rejection of MgCl₂.

Keywords: ion permeation, lithium extraction, membrane-based separation, nanotechnology

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4409 Ultrastrong Coupling of CdZnS/ZnS Quantum Dots and Breathing Plasmons in Aluminum Metal-Insulator-Metal Nanocavities in Near-Ultraviolet Spectrum

Authors: Li Li, Lei Wang, Chenglin Du, Mengxin Ren, Xinzheng Zhang, Wei Cai, Jingjun Xu

Abstract:

Strong coupling between excitons of quantum dots and plasmons in nanocavites can be realized at room temperature due to the strong confinement of the plasmon fields, which offers building blocks for quantum information systems or ultralow-power switches and lasers. In this work, by using cathodoluminescence, ultrastrong coupling with Rabi splitting above 1 eV between breathing plasmons in Aluminum metal-insulator-metal (MIM) cavity and excited state of CdZnS/ZnS quantum dots was reported in near-UV spectrum. Analytic analysis and full-wave electromagnetic simulations provide the evidence for the strong coupling and confirm the hybridization of the QDs exciton and LSP breathing mode. This study opens the way for new emerging applications based on strongly coupled light-matter states all over the visible region down to ultra-violet frequencies.

Keywords: breathing mode, plasmonics, quantum dot, strong coupling, ultraviolet

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4408 Face Tracking and Recognition Using Deep Learning Approach

Authors: Degale Desta, Cheng Jian

Abstract:

The most important factor in identifying a person is their face. Even identical twins have their own distinct faces. As a result, identification and face recognition are needed to tell one person from another. A face recognition system is a verification tool used to establish a person's identity using biometrics. Nowadays, face recognition is a common technique used in a variety of applications, including home security systems, criminal identification, and phone unlock systems. This system is more secure because it only requires a facial image instead of other dependencies like a key or card. Face detection and face identification are the two phases that typically make up a human recognition system.The idea behind designing and creating a face recognition system using deep learning with Azure ML Python's OpenCV is explained in this paper. Face recognition is a task that can be accomplished using deep learning, and given the accuracy of this method, it appears to be a suitable approach. To show how accurate the suggested face recognition system is, experimental results are given in 98.46% accuracy using Fast-RCNN Performance of algorithms under different training conditions.

Keywords: deep learning, face recognition, identification, fast-RCNN

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4407 Post-Processing Method for Performance Improvement of Aerial Image Parcel Segmentation

Authors: Donghee Noh, Seonhyeong Kim, Junhwan Choi, Heegon Kim, Sooho Jung, Keunho Park

Abstract:

In this paper, we describe an image post-processing method to enhance the performance of the parcel segmentation method using deep learning-based aerial images conducted in previous studies. The study results were evaluated using a confusion matrix, IoU, Precision, Recall, and F1-Score. In the case of the confusion matrix, it was observed that the false positive value, which is the result of misclassification, was greatly reduced as a result of image post-processing. The average IoU was 0.9688 in the image post-processing, which is higher than the deep learning result of 0.8362, and the F1-Score was also 0.9822 in the image post-processing, which was higher than the deep learning result of 0.8850. As a result of the experiment, it was found that the proposed technique positively complements the deep learning results in segmenting the parcel of interest.

Keywords: aerial image, image process, machine vision, open field smart farm, segmentation

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4406 Analysis of Contact Width and Contact Stress of Three-Layer Corrugated Metal Gasket

Authors: I. Made Gatot Karohika, Shigeyuki Haruyama, Ken Kaminishi, Oke Oktavianty, Didik Nurhadiyanto

Abstract:

Contact width and contact stress are important parameters related to the leakage behavior of corrugated metal gasket. In this study, contact width and contact stress of three-layer corrugated metal gasket are investigated due to the modulus of elasticity and thickness of surface layer for 2 type gasket (0-MPa and 400-MPa mode). A finite element method was employed to develop simulation solution to analysis the effect of each parameter. The result indicated that lowering the modulus of elasticity ratio of surface layer will result in better contact width but the average contact stresses are smaller. When the modulus of elasticity ratio is held constant with thickness ratio increase, its contact width has an increscent trend otherwise the average contact stress has decreased trend.

Keywords: contact width, contact stress, layer, metal gasket, corrugated, simulation

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4405 Capture of Co₂ From Natural Gas Using Modified Imidazolium Ionic Liquids

Authors: Alaa A. Ghanem, S. E. M. Desouky

Abstract:

Natural gas (NG) is considered one of the most essential global energy sources. NG fields are often far away from the market, and a long-distance transporting pipeline usually is required. Production of NG with high content of CO₂ leads to severe problems such as equipment corrosion along with the production line until refinery.in addition to a high level of toxicity and decreasing in calorific value of the NG. So it is recommended to remove or decrease the CO₂ percent to meet transport specifications. This can be reached using different removal techniques such as physical and chemical absorption, pressure swing adsorption, membrane separation, or low-temperature separation. Many solvents and chemicals are being used to capture carbon dioxide on a large scale; among them, Ionic liquids have great potential due to their tunable properties; low vapour pressure, low melting point, and sensible thermal stability. In this research, three modifiedimidazolium ionic liquids will be synthesized and characterized using different tools of analysis such as FT-IR, 1H NMR. Thermal stability and surface activity will be studied. The synthesized compounds will be evaluated as selective solvents for CO₂ removal from natural gas using PVT cell.

Keywords: natural gas, CO₂ capture, imidazolium ionic liquid, PVT cell

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4404 Symmetry-Protected Dirac Semi-Metallic Phases in Transition Metal Dichalcogenides

Authors: Mohammad Saeed Bahramy

Abstract:

Transition metal dichalcogenides have experienced a resurgence of interest in the past few years owing to their rich properties, ranging from metals and superconductors to strongly spin-orbit-coupled semiconductors and charge-density-wave systems. In all these cases, the transition metal d-electrons mainly determine the ground state properties. This presentation focuses on the chalcogen-derived states. Combining density-functional theory calculations with spin- and angle-resolved photoemission, it is shown that these states generically host a coexistence of type I and type II three-dimensional bulk Dirac fermions as well as ladders of topological surface states and surface resonances. It will be discussed how these naturally arise within a single p-orbital manifold as a general consequence of a trigonal crystal field, and as such can be expected across many compounds. Our finding opens a new route to design topological materials with advanced functionalities.

Keywords: topology, electronic structure, Dirac semimetals, transition metal dichalcogenides

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4403 The Batch Method Approach for Adsorption Mechanism Processes of Some Selected Heavy Metal Ions and Methylene Blue by Using Chemically Modified Luffa Cylindrica

Authors: Akanimo Emene, Mark D. Ogden, Robert Edyvean

Abstract:

Adsorption is a low cost, efficient and economically viable wastewater treatment process. Utilization of this treatment process has not been fully applied due to the complex and not fully understood nature of the adsorption system. To optimize its process is to choose a sufficient adsorbent and to study further the experimental parameters that influence the adsorption design system. Chemically modified adsorbent, Luffa cylindrica, was used to adsorb heavy metal ions and an organic pollutant, methylene blue, from aqueous environmental solution at varying experimental conditions. Experimental factors, adsorption time, initial metal ion or organic pollutant concentration, ionic strength, and pH of solution were studied. The experimental data were analyzed with kinetic and isotherm models. The antagonistic effect of the methylene and some heavy metal ions were recorded. An understanding of the use of this treated Luffa cylindrica for the removal of these toxic substances will establish and improve the commercial application of the adsorption process in treatment of contaminated waters.

Keywords: adsorption, heavy metal ions, Luffa cylindrica, wastewater treatment

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4402 Study of Self-Assembled Photocatalyst by Metal-Terpyridine Interactions in Polymer Network

Authors: Dong-Cheol Jeong, Jookyung Lee, Yu Hyeon Ro, Changsik Song

Abstract:

The design and synthesis of photo-active polymeric systems are important in regard to solar energy harvesting and utilization. In this study, we synthesized photo-active polymer, thin films, and polymer gel via iterative self-assembly using reversible metal-terpyridine (M-tpy) interactions. The photocurrent generated in the polymeric thin films with Zn(II) was much higher than those of other films. Apparent diffusion rate constant (kapp) was measured for the electron hopping process via potential-step chronoamperometry. As a result, the kapp for the polymeric thin films with Zn(II) was almost two times larger than those with other metal ions. We found that the anodic photocurrents increased with the inclusion of the multi-walled carbon nanotube (MWNT) layer. Inclusion of MWNTs can provide efficient electron transfer pathways. In addition, polymer gel based on interactions between terpyridine and metal ions was shown the photocatalytic activity. Interestingly, in the Mg-terpyridine gel, the reaction rate of benzylamine to imine photo-oxidative coupling was faster than Fe-terpyridine gel because the Mg-terpyridine gel has two steps electron transfer pathway but Fe-terpyridine gel has three steps electron transfer pathway.

Keywords: terpyridine, photocatalyst, self-assebly, metal-ligand

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4401 Fe3O4 Decorated ZnO Nanocomposite Particle System for Waste Water Remediation: An Absorptive-Photocatalytic Based Approach

Authors: Prateek Goyal, Archini Paruthi, Superb K. Misra

Abstract:

Contamination of water resources has been a major concern, which has drawn attention to the need to develop new material models for treatment of effluents. Existing conventional waste water treatment methods remain ineffective sometimes and uneconomical in terms of remediating contaminants like heavy metal ions (mercury, arsenic, lead, cadmium and chromium); organic matter (dyes, chlorinated solvents) and high salt concentration, which makes water unfit for consumption. We believe that nanotechnology based strategy, where we use nanoparticles as a tool to remediate a class of pollutants would prove to be effective due to its property of high surface area to volume ratio, higher selectivity, sensitivity and affinity. In recent years, scientific advancement has been made to study the application of photocatalytic (ZnO, TiO2 etc.) nanomaterials and magnetic nanomaterials in remediating contaminants (like heavy metals and organic dyes) from water/wastewater. Our study focuses on the synthesis and monitoring remediation efficiency of ZnO, Fe3O4 and Fe3O4 coated ZnO nanoparticulate system for the removal of heavy metals and dyes simultaneously. Multitude of ZnO nanostructures (spheres, rods and flowers) using multiple routes (microwave & hydrothermal approach) offers a wide range of light active photo catalytic property. The phase purity, morphology, size distribution, zeta potential, surface area and porosity in addition to the magnetic susceptibility of the particles were characterized by XRD, TEM, CPS, DLS, BET and VSM measurements respectively. Further on, the introduction of crystalline defects into ZnO nanostructures can also assist in light activation for improved dye degradation. Band gap of a material and its absorbance is a concrete indicator for photocatalytic activity of the material. Due to high surface area, high porosity and affinity towards metal ions and availability of active surface sites, iron oxide nanoparticles show promising application in adsorption of heavy metal ions. An additional advantage of having magnetic based nanocomposite is, it offers magnetic field responsive separation and recovery of the catalyst. Therefore, we believe that ZnO linked Fe3O4 nanosystem would be efficient and reusable. Improved photocatalytic efficiency in addition to adsorption for environmental remediation has been a long standing challenge, and the nano-composite system offers the best of features which the two individual metal oxides provide for nanoremediation.

Keywords: adsorption, nanocomposite, nanoremediation, photocatalysis

Procedia PDF Downloads 215