Search results for: hybrid insulator metal insulator

Authors: Hamsasew Hankebo Lemago, Dóra Hessz, Zoltán Erdélyi, Imre Miklós Szilágyi

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Metal oxide inverse opals are a unique class of photocatalysts with a hierarchical structure that mimics the natural opal gemstone. They are composed of a network of interconnected pores, which provides a large surface area and efficient pathways for the transport of light and reactants. Atomic layer deposition (ALD) is a versatile technique for the synthesis of high-precision metal oxide thin films, including inverse opals. ALD allows for precise control over the thickness, composition, and morphology of the synthesized films, making it an ideal technique for the fabrication of photocatalysts with tailored properties. In this study, we report the synthesis of TiO2, ZnO, and Al2O3 inverse opal photocatalysts using thermal or plasma-enhanced ALD. The synthesized photocatalysts were characterized using a variety of techniques, including scanning electron microscopy (SEM)-energy dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD), Raman spectroscopy, photoluminescence (PL), ellipsometry, and UV-visible spectroscopy. The results showed that the ALD-synthesized metal oxide inverse opals had a highly ordered structure and a tunable pore size. The PL spectroscopy results showed low recombination rates of photogenerated electron-hole pairs, while the ellipsometry and UV-visible spectroscopy results showed tunable optical properties and band gap energies. The photocatalytic activity of the samples was evaluated by the degradation of methylene blue under visible light irradiation. The results showed that the ALD-synthesized metal oxide inverse opals exhibited high photocatalytic activity, even under visible light irradiation. The composites photocatalysts showed even higher activity than the individual metal oxide inverse opals. The enhanced photocatalytic activity of the composites can be attributed to the synergistic effect between the different metal oxides. For example, Al2O3 can act as a charge carrier scavenger, which can reduce the recombination of photogenerated electron-hole pairs. The ALD-synthesized metal oxide inverse opals and their composites are promising photocatalysts for a variety of applications, such as wastewater treatment, air purification, and energy production. For example, they can be used to remove organic pollutants from wastewater, decompose harmful gases in the air, and produce hydrogen fuel from water.

Keywords: ALD, metal oxide inverse opals, composites, photocatalysis

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Authors: Weixiang Liu, Yukun Qin, Song Liu, Pengcheng Li

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Plant diseases can cause the death of crops with great economic losses. Particularly, those diseases are usually caused by pathogenic fungi. Metal fungicides are a type of pesticide that has advantages of a low-cost, broad antimicrobial spectrum and strong sterilization effect. However, the frequent and wide application of traditional metal fungicides has caused serious problems such as environmental pollution, the outbreak of mites and phytotoxicity. Therefore, it is critically necessary to discover new organic metal fungicides alternatives that have a low metal content, low toxicity, and little influence on mites. Chitosan, the second most abundant natural polysaccharide next to cellulose, was proved to have broad-spectrum antifungal activity against a variety of fungi. However, the use of chitosan was limited due to its poor solubility and weaker antifungal activity compared with commercial fungicide. Therefore, in order to improve the water solubility and antifungal activity, many researchers grafted the active groups onto chitosan. The present work was to combine free metal ions with chitosan, to prepare more potent antifungal chitosan derivatives, thus, based on condensation reaction, chitosan derivative bearing amino pyridine group was prepared and subsequently followed by coordination with cupric ions, zinc ions and nickel ions to synthesize chitosan metal complexes. The calculations by density functional theory (DFT) show that the copper ions and nickel ions underwent dsp2 hybridization, the zinc ions underwent sp3 hybridization, and all of them are coordinated by the carbon atom in the p-π conjugate group and the oxygen atoms in the acetate ion. The antifungal properties of chitosan metal complexes against Phytophthora capsici (P. capsici), Gibberella zeae (G. zeae), Fusarium oxysporum (F. oxysporum) and Botrytis cinerea (B. cinerea) were also assayed. In addition, a plant toxicity experiment was carried out. The experiments indicated that the derivatives have significantly enhanced antifungal activity after metal ions complexation compared with the original chitosan. It was shown that 0.20 mg/mL of O-CSPX-Cu can 100% inhibit the growth of P. capsici and 0.20 mg/mL of O-CSPX-Ni can 87.5% inhibit the growth of B. cinerea. In general, their activities are better than the positive control oligosaccharides. The combination of the pyridine formyl groups seems to favor biological activity. Additionally, the ligand fashion was precisely analyzed, and the results revealed that the copper ions and nickel ions underwent dsp2 hybridization, the zinc ions underwent sp3 hybridization, and the carbon atoms of the p-π conjugate group and the oxygen atoms of acetate ion are involved in the coordination of metal ions. The phytotoxicity assay of O-CSPX-M was also conducted, unlike the traditional metal fungicides, the metal complexes were not significantly toxic to the leaves of wheat. O-CSPX-Zn can even increase chlorophyll content in wheat leaves at 0.40 mg/mL. This is mainly because chitosan itself promotes plant growth and counteracts the phytotoxicity of metal ions. The chitosan derivative described here may lend themselves to future applicative studies in crop protection.

Keywords: coordination, chitosan, metal complex, antifungal properties

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Authors: Meena Marafi, Mohan S. Rana

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Catalysts play an important role in producing valuable fuel products in petroleum refining; but, due to feedstock’s impurities catalyst gets deactivated with carbon and metal deposition. The disposal of spent catalyst falls under the category of hazardous industrial waste that requires strict agreement with environmental regulations. The spent hydroprocessing catalyst contains Mo, V and Ni at high concentrations that have been found to be economically significant for recovery. Metal recovery process includes deoiling, decoking, grinding, dissolving and treatment with complexing leaching agent such as ethylene diamine tetra acetic acid (EDTA). The process conditions have been optimized as a function of time, temperature and EDTA concentration in presence of ultrasonic agitation. The results indicated that optimum condition established through this approach could recover 97%, 94% and 95% of the extracted Mo, V and Ni, respectively, while 95% EDTA was recovered after acid treatment.

Keywords: atmospheric residue desulfurization (ARDS), deactivation, hydrotreating, spent catalyst

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Authors: Monireh Azimi, Mohammad Reza Toroghinejad, Leo A. I. Kestens

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The role of different metallic and intermetallic reinforcements on the microstructure and the associated mechanical response of a composite is of crucial importance. To investigate this issue, a multiphase metal-intermetallic composite was in-situ fabricated through reactive annealing and accumulative roll bonding (ARB) processes. EBSD results indicated that the lamellar grain structure of the Al matrix after the first cycle has evolved with increasing strain to a mixed structure consisting of equiaxed and lamellar grains, whereby the steady-state did not occur after the 3rd (last) cycle—applying a strain of 6.1 in the Al phase, the length and thickness of the grains reduced by 92.2% and 97.3%, respectively, compared to the annealed state. Intermetallic phases together with the metallic reinforcement of Ni influence grain fragmentation of the Al matrix and give rise to a specific texture evolution by creating heterogeneity in the strain and flow patterns. Mechanical properties of the multiphase composite demonstrated the yield and ultimate tensile strengths of 217.9 MPa and 340.1 MPa, respectively, compared to 48.7 MPa and 55.4 MPa in the metal-intermetallic laminated (MIL) sandwich before applying the ARB process, which corresponds to an increase of 347% and 514% of yield and tensile strength, respectively.

Keywords: accumulative roll bonding, mechanical properties, metal-intermetallic composite, severe plastic deformation, texture

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Authors: John Kabuba, Hilary Rutto

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Ion exchange is one of the methods used to remove heavy metal such as copper and cobalt from wastewaters. Parameters affecting the ion-exchange of copper and cobalt aqueous solutions using clinoptilolite are the objectives of this study. Synthetic solutions were prepared with the concentration of 0.02M, 0.06M and 0.1M. The cobalt solution was maintained to 0.02M while varying the copper solution to the above stated concentrations. The clinoptilolite was activated with HCl and H2SO4 for removal efficiency. The pHs of the solutions were found to be acidic hence enhancing the copper and cobalt removal. The natural clinoptilolite performance was also found to be lower compared to the HCl and H2SO4 activated one for the copper removal ranging from 68% to 78% of Cu2+ uptake with the natural clinoptilolite to 66% to 51% with HCl and H2SO4 respectively. It was found that the activated clinoptilolite removed more copper and cobalt than the natural one and found that the electronegativity of the metal plays a role in the metal removal and the clinoptilolite selectivity.

Keywords: clinoptilolite, cobalt and copper, ion-exchange, mass dosage, pH

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Authors: Shalini Arora, Sri Sivakumar

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The deep removal of high molecular weight sulphur compounds (e.g., 4,6, dimethyl dibenzothiophene) is challenging due to their steric hindrance. Hydrogenation desulfurization (HYD) pathway is the main pathway to remove these sulfur compounds, and it is mainly governed by the number of type 2 sites. The formation of type 2 sites can be enhanced by modulating the pore structure and the interaction between the active metal and support. To this end, we report the enhanced HDS catalytic activity of ultrasmall NiMo supported on amorphous alumina (A-Al₂O₃) catalysts by one pot colloidal synthesis method followed by calcination and sulfidation. The amorphous alumina (A-Al₂O₃) was chosen as the support due to its lower surface energy, better physicochemical properties, and enhanced acidic sites (due to the dominance of tetra and penta coordinated [Al] sites) than crystalline alumina phase. At 20% metal oxide composition, NiMo supported on A-Al₂O₃ catalyst showed 1.4 and 1.2 times more reaction rate constant and turn over frequency (TOF) respectively than the conventional catalyst (wet impregnated NiMo catalysts) for HDS reaction of dibenzothiophene reactant molecule. A-Al₂O₃ supported catalysts represented enhanced type 2 sites formation (because this catalystpossesses higher sulfidation degree (80%) and NiMoS sites (19.3 x 10¹⁷ sites/mg) with desired optimum stacking degree (2.5) than wet impregnated catalyst at same metal oxide composition 20%) along with higher active metal dispersion, Mo edge site fraction. The experimental observations were also supported by DFT simulations. Lower heat of adsorption (< 4.2 ev for MoS2 interaction and < 3.15 ev for Ni doped MoS2 interaction) values for A-Al₂O₃ confirmed the presence of weaker metal-support interaction in A-Al₂O₃ in contrast to crystalline ℽ-Al₂O3. The weak metal-support interaction for prepared catalysts clearly suggests the higher formation of type 2 sites which leads to higher catalytic activity for HDS reaction.

Keywords: amorphous alumina, colloidal, desulfurization, metal-support interaction

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Authors: Ahmadur Rahman, Showkat Ahmad Lone, Ariful Islam

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In this article, we have estimated the parameters for the failure times of units based on the sampling technique adaptive type-I progressive hybrid censoring under the step-stress partially accelerated life tests for competing risk. The failure times of the units are assumed to follow an exponential distribution. Maximum likelihood estimation technique is used to estimate the unknown parameters of the distribution and tampered coefficient. Confidence interval also obtained for the parameters. A simulation study is performed by using Monte Carlo Simulation method to check the authenticity of the model and its assumptions.

Keywords: adaptive type-I hybrid progressive censoring, competing risks, exponential distribution, simulation, step-stress partially accelerated life tests

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Authors: Masoud Ghermezi

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Studying the sheet metals is one of the most important research areas in the field of metal forming due to their extensive applications in the aerospace industries. A useful method for determining the forming limit of these materials and consequently preventing the rupture of sheet metals during the forming process is the use of the forming limit curve (FLC). In addition to specifying the forming limit, this curve also delineates a boundary for the allowed values of strain in sheet metal forming; these characteristics of the FLC along with its accuracy of computation and wide range of applications have made this curve the basis of research in the present paper. This study presents a new model that not only agrees with the results obtained from the above mentioned theory, but also eliminates its shortcomings. In this theory, like in the M-K theory, a thin sheet with an inhomogeneity as a gradient thickness reduction with a sinusoidal function has been chosen and subjected to two-dimensional stress. Through analytical evaluation, ultimately, a governing differential equation has been obtained. The numerical solution of this equation for the range of positive strains (stretched region) yields the results that agree with the results obtained from M-K theory. Also the solution of this equation for the range of negative strains (tension region) completes the FLC curve. The findings obtained by applying this equation on two alloys with the hardening exponents of 0.4 and 0.24 indicate the validity of the presented equation.

Keywords: sheet metal, metal forming, forming limit curve (FLC), M-K theory

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Authors: C. Joseph Abou-Fayssal, K. Philippot, R. Poli, E. Manoury, A. Riisager

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The use of soluble polymer-supported metal nanoparticles (MNPs) has received significant attention for the ease of catalyst recovery and recycling. Of particular interest are MNPs that are supported on polymers that are either soluble or form stable colloidal dispersion in water, as this allows to combine of the advantages of the aqueous biphasic protocol with the catalytical performances of MNPs. The objective is to achieve good confinement of the catalyst in the nanoreactor cores and, thus, a better catalyst recovery in order to overcome the previously witnessed MNP extraction. Inspired by previous results, we are interested in the design of polymeric nanoreactors functionalized with ligands able to solidly anchor metallic nanoparticles in order to control the activity and selectivity of the developed nanocatalysts. The nanoreactors are core-crosslinked micelles (CCM) synthesized by reversible addition-fragmentation chain transfer (RAFT) polymerization. Varying the nature of the core-linked functionalities allows us to get differently stabilized metal nanoparticles and thus compare their performance in the catalyzed aqueous biphasic hydrogenation of model substrates. Particular attention is given to catalyst recyclability.

Keywords: biphasic catalysis, metal nanoparticles, polymeric nanoreactors, catalyst recovery, RAFT polymerization

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Authors: M. S. Jimah, A. C. Achuenu, M. Momodu

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Group communications over public infrastructure are prone to a lot of security issues. Existing network protocols like Protocol Independent Multicast Sparse Mode (PIM SM) and Protocol Independent Multicast Dense Mode (PIM DM) do not have inbuilt security features. Therefore, any user or node can easily access the group communication as long as the user can send join message to the source nodes, the source node then adds the user to the network group. In this research, a hybrid method of salting and hashing to encrypt information in the source and stub node was designed, and when stub nodes need to connect, they must have the appropriate key to join the group network. Object oriented analysis design (OOAD) was the methodology used, and the result shows that no extra controlled bandwidth overhead cost was added by encrypting and the hybrid model was more securing than the existing PIM SM, PIM DM and Zhang secure PIM SM.

Keywords: group communications, multicast, PIM SM, PIM DM, encryption

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Authors: Claudio Clemente, Valentina Gargiulo, Alessio Occhicone, Giovanni Piero Pepe, Giovanni Ausanio, Michela Alfè

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Volatile organic compound (VOC) emissions represent a serious risk to human health and the integrity of the ecosystems, especially at high concentrations. For this reason, it is very important to continuously monitor environmental quality and develop fast and reliable portable sensors to allow analysis on site. Chemiresistors have become promising candidates for VOC sensing as their ease of fabrication, variety of suitable sensitive materials, and simple sensing data. A chemoresistive gas sensor is a transducer that allows to measure the concentration of an analyte in the gas phase because the changes in resistance are proportional to the amount of the analyte present. The selection of the sensitive material, which interacts with the target analyte, is very important for the sensor performance. The most used VOC detection materials are metal oxides (MOx) for their rapid recovery, high sensitivity to various gas molecules, easy fabrication. Their sensing performance can be improved in terms of operating temperature, selectivity, and detection limit. Metal-organic frameworks (MOFs) have attracted a lot of attention also in the field of gas sensing due to their high porosity, high surface area, tunable morphologies, structural variety. MOFs are generated by the self-assembly of multidentate organic ligands connecting with adjacent multivalent metal nodes via strong coordination interactions, producing stable and highly ordered crystalline porous materials with well-designed structures. However, most MOFs intrinsically exhibit low electrical conductivity. To improve this property, MOFs can be combined with organic and inorganic materials in a hybrid fashion to produce composite materials or can be transformed into more stable structures. MOFs, indeed, can be employed as the precursors of metal oxides with well-designed architectures via the calcination method. The MOF-derived MOx partially preserved the original structure with high surface area and intrinsic open pores, which act as trapping centers for gas molecules, and showed a higher electrical conductivity. Core-shell heterostructures, in which the surface of a metal oxide core is completely coated by a MOF shell, forming a junction at the core-shell heterointerface, can also be synthesized. Also, nanocomposite in which MOF structures are intercalated with graphene related materials can also be produced, and the conductivity increases thanks to the high mobility of electrons of carbon materials. As MOF structures, zinc-based MOFs belonging to the ZIF family were selected in this work. Several Zn-based materials based and/or derived from MOFs were produced, structurally characterized, and arranged in a chemo resistive architecture, also exploring the potentiality of different approaches of sensing layer deposition based on PLD (pulsed laser deposition) and, in case of thermally labile materials, MAPLE (Matrix Assisted Pulsed Laser Evaporation) to enhance the adhesion to the support. The sensors were tested in a controlled humidity chamber, allowing for the possibility of varying the concentration of ethanol, a typical analyte chosen among the VOCs for a first survey. The effect of heating the chemiresistor to improve sensing performances was also explored. Future research will focus on exploring new manufacturing processes for MOF-based gas sensors with the aim to improve sensitivity, selectivity and reduce operating temperatures.

Keywords: chemiresistors, gas sensors, graphene related materials, laser deposition, MAPLE, metal-organic frameworks, metal oxides, nanocomposites, sensing performance, transduction mechanism, volatile organic compounds

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Authors: Dejan Tanikić, Jelena Đoković, Saša Kalinović, Miodrag Manić, Saša Ranđelović

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This paper deals with measuring and modelling of the quality of the machined surface of the metal machining process. The average surface roughness (R_a) which represents the quality of the machined part was measured during the dry turning of the AISI 4140 steel. A large number of factors with the unknown relations among them influences this parameter, and that is why mathematical modelling is extremely complicated. Different values of cutting speed, feed rate, depth of cut (cutting regime) and workpiece hardness causes different surface roughness values. Modelling with soft computing techniques may be very useful in such cases. This paper presents the usage of the fuzzy logic-based system for determining metal machining process parameter in order to find the proper values of cutting regimes.

Keywords: fuzzy logic, metal machining, process modeling, surface roughness

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Authors: Dominik Szczesniak, Sabre Kais

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In the present communication, we analyze selected local aspects of the metal-induced gap states (MIGSs) that may be responsible for the magnetic flux noise in some of the superconducting qubit modalities at low-dimension. The presented theoretical analysis stems from the earlier bulk considerations and is aimed at further explanation of the decoherence effect by recognizing its universal character. Specifically, the analysis is carried out by using the complex band structure method for arbitrary low-dimensional junctions. This allows us to provide the most fundamental and general observations for the systems of interest. In particular, herein, we investigate in detail the MIGSs behavior in the momentum space as a function of the potential fluctuations and the electron-electron interaction magnitude at the interface. In what follows, this study is meant to provide a direct relationship between the MIGSs behavior, the discussed decoherence effect, and the intrinsic properties of the low-dimensional Josephson junctions.

Keywords: superconducting qubits, metal-induced gap states, decoherence, low-dimension

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Authors: Muhammad Umair Mushtaq, Ameena Iqbal, Muhammad Aqib Hassan Ali Khan, Ismat Nawaz, Sohail Yousaf, Mazhar Iqbal

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Heavy metals are one of the priority pollutants as they pose serious health and environmental threats. They can be removed by various physiochemical methods but are costly and responsible for additional environmental problems. Bioremediation that exploits plants and their associated microbes have been referred as cost effective and environmental friendly technique. In this study, a pot experiment was conducted in a greenhouse to evaluate the potential of Celosia cristata and effects of bacteria, Pseudomonas japonica, and organic amendment moss/compost on tolerating/accumulating heavy metals. Two weeks old seedlings were transferred to soil in pots, and after four weeks they were inoculated with bacterial strain, while after growth of six weeks they were watered with a metal containing synthetic wastewater and were harvested after a growth period of nine weeks. After harvesting, morphological and physiological parameters and metal content of plants were measured. The results showed highest plant growth and biomass production in case of organic amendments while highest metal uptake has been found in non-amended pots. Positive controls have shown highest Pb uptake of 2900 mg/kg DW, while P. japonica amended pots have shown highest Cd, Cr, Ni and Cu uptake of 963.53, 1481.17, 1022.01 and 602.17 mg/kg DW, respectively. In conclusion organic amendments have strong impacts on growth enhancement while P. japonica enhances metal translocation and accumulation to aerial parts with little significant involvement in plant growth.

Keywords: ornamental plants, plant microbe interaction, amendments, bacteria

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Authors: Rosalie Menon, Angela Reid

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Building integrated photovoltaic systems with air collectors (hybrid PV-T) have proved successful however there are few examples of their application in the UK. The opportunity to pull heat from behind the PV system to contribute to a building’s heating system is an efficient use of waste energy and its potential to improve the performance of the PV array is well documented. As part of Glasgow School of Art’s estate expansion, the purchase and redevelopment of an existing 1950’s college building was used as a testing vehicle for the hybrid PV-T system as an integrated element of the upper floor and roof. The primary objective of the feasibility study was to determine if hybrid PV-T was technically and financially suitable for the refurbished building. The key consideration was whether the heat recovered from the PV panels (to increase the electrical efficiency) can be usefully deployed as a heat source within the building. Dynamic thermal modelling (IES) and RetScreen Software were used to carry out the feasibility study not only to simulate overshadowing and optimise the PV-T locations but also to predict the atrium temperature profile; predict the air load for the proposed new 4 No. roof mounted air handling units and to predict the dynamic electrical efficiency of the PV element. The feasibility study demonstrates that there is an energy reduction and carbon saving to be achieved with each hybrid PV-T option however the systems are subject to lengthy payback periods and highlights the need for enhanced government subsidy schemes to reward innovation with this technology in the UK.

Keywords: building integrated, photovoltatic thermal, pre-heat air, ventilation

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Authors: Abas Mohsenzadeh, Mina Arya, Kim Bolton

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Catalytic combustion of hydrocarbons is an important technology developed to produce energy with minimum pollutant formation. The catalyst plays a key role in this process which operates at lower temperatures compared to conventional flame combustion. The energetics of the direct combustion of hydrocarbons (CH → C + H) on a series of metal surfaces including Ag, Au, Al, Cu, Rh, Pt, Pd, Ni, Fe and Co were investigated using density functional theory (DFT). Brønsted-Evans-Polanyi (BEP) and transition state scaling (TSS) correlations were proposed based on DFT calculations on the Ag, Au, Al, Cu, Rh, Pt and Pd surfaces. These correlations were then used to estimate the energetics on Fe, Ni and Co surfaces. Results showed that the estimated reaction and activation energies by BEP and TSS correlations on Fe, Ni and Co surfaces are in an excellent agreement with those obtained by DFT calculations. Therefore these correlations can be efficiently used to predict energetics of similar reactions on these surfaces without doing computationally costly transition state calculations. It was found that the activation barrier for CH dissociation follows the order Ag ˃ Au ˃ Al ˃ Cu ˃ Pt ˃ Pd ˃ Ni > Co > Rh > Fe. Also, BEP (with R2 value of 0.96) and TSS correlations (with R2 value of 0.99) support the results.

Keywords: BEP, DFT, hydrocarbon combustion, metal surfaces, TSS

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Authors: Jing Lin, Zou Yiming, Goei Ronn, Li Yun, Amanda Ong Jiamin, Alfred Tok Iing Yoong

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High-entropy alloy (HEA) coatings comprise multiple (five or more) principal elements that give superior mechanical, electrical, and thermal properties. However, the current synthesis methods of HEA coating still face huge challenges in facile and controllable preparation, as well as conformal integration, which seriously restricts their potential applications. Herein, we report a controllable synthesis of conformal quinary HEA coating consisting of noble metals (Rh, Ru, Ir, Pt, and Pd) by using the atomic layer deposition (ALD) with a post-annealing approach. This approach realizes low temperature (below 200 °C), precise control (nanoscale), and conformal synthesis (over complex substrates) of HEA coating. Furthermore, the resulting quinary HEA coating shows promising potential as a platform for catalysis, exhibiting substantially enhanced electrocatalytic hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) performances as compared to other noble metal-based structures such as single metal coating or multi-layered metal composites.

Keywords: high-entropy alloy, thin-film, catalysis, water splitting, atomic layer deposition

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Authors: V. K. Srivastava

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The chemistry of compounds containing transition metals bound to sulfur containing ligands has been actively studied. Interest in these compounds arises from the identification of the biological importance of iron-sulfur containing proteins as well as the unusual behaviour of several types of synthetic metal-sulfur complexes. Metal complexes (C₆H₅)₄P)₂ Pt(Mos₄)₂, (C₆H₅)₄P)₂ Pd(MoS₄)₂, (C₆H₅)₄P)₂ Ni(MoS₄)₂ of bioinorganic relevance were investigated. The complexes [M(M'S₄)₂]²⁻ were prepared with high yield and purity as salts of the variety of organic cations. The diamagnetism and spectroscopic properties of these complexes confirmed that their structures are essentially equivalent with two bidentate M'S₄²⁻ ligands coordinated to the central d⁸ metal in a square planer geometry. The interaction of the complexes with CT-DNA was studied. Results showed that metal complexes increased DNA's relative viscosity and quench the fluorescence intensity of EB bound to DNA. In antimicrobial activities, all complexes showed good antimicrobial activity higher than ligand against gram positive, gram negative bacteria and fungi. The antitumor properties have been tested in vitro against two tumor human cell lines, Hela (derived from cervical cancer) and MCF-7 (derived from breast cancer) using metabolic activity tests. Result showed that the complexes are promising chemotherapeutic alternatives in the search of anticancer agents.

Keywords: anti cancer, biocidal, DNA binding, spectra

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Authors: Kevin W. Zobrist, Patricia A. Townsend, Nora M. Haider

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Advanced Hardwood Biofuels Northwest (AHB) is a consortium funded by the United States Department of Agriculture (USDA) to research the potential for a system to produce advanced biofuels (jet fuel, diesel, and gasoline) from hybrid poplar in the Pacific Northwest region of the U.S. An Extension team was established as part of the project to examine community readiness and willingness to adopt hybrid as a purpose-grown bioenergy crop. The Extension team surveyed key stakeholder groups, including growers, Extension professionals, policy makers, and environmental groups, to examine attitudes and concerns about growing hybrid poplar for biofuels. The surveys found broad skepticism about the viability of such a system. The top concern for most stakeholder groups was economic viability and the availability of predictable markets. Growers had additional concerns stemming from negative past experience with hybrid poplar as an unprofitable endeavor for pulp and paper production. Additional barriers identified included overall land availability and the availability of water and water rights for irrigation in dry areas of the region. Since the beginning of the project, oil and natural gas prices have plummeted due to rapid increases in domestic production. This has exacerbated the problem with economic viability by making biofuels even less competitive than fossil fuels. However, the AHB project has identified intermediate market opportunities to use poplar as a renewable source for other biochemicals produced by petroleum refineries, such as acetic acid, ethyl acetate, ethanol, and ethylene. These chemicals can be produced at a lower cost with higher yields and higher, more-stable prices. Despite these promising market opportunities, the survey results suggest that it will still be challenging to induce growers to adopt hybrid poplar. Early adopters will be needed to establish an initial feedstock supply for a budding industry. Through demonstration sites and outreach events to various stakeholder groups, the project attracted interest from wastewater treatment facilities, since these facilities are already growing hybrid poplar plantations for applying biosolids and treated wastewater for further purification, clarification, and nutrient control through hybrid poplar’s phytoremediation capabilities. Since these facilities are already using hybrid poplar, selling the wood as feedstock for a biorefinery would be an added bonus rather than something requiring a high rate of return to compete with other crops and land uses. By holding regional workshops and conferences with wastewater professionals, AHB Extension has found strong interest from wastewater treatment operators. In conclusion, there are several significant barriers to developing a successful system for producing biofuels from hybrid poplar, with the largest barrier being economic viability. However, there is potential for wastewater treatment facilities to serve as early adopters for hybrid poplar production for intermediate biochemicals and eventually biofuels.

Keywords: hybrid poplar, biofuels, biochemicals, wastewater treatment

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Authors: Davyd Urbanas, Pranas Baltrenas

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It is well-known that, despite the constant increase of alternative energy sources usage, today combustible fuels are still widely used in power engineering. As a result of fuel combustion, significant amounts of nitrogen oxides (NOx) and carbon monoxide (CO is a product of incomplete combustion) are supplied to the atmosphere. Also, these pollutants are formed in industry (chemical production, refining, and metal production). In this work, the investigation of nitrogen oxides CO-selective catalytic reduction using new grain load-type catalysts was carried out. The catalysts containing the substrate and a thin active coating made of transition metal (Mn, Cu, and Nb) oxides were prepared with the use of electroless chemical deposition method. Chemical composition, chemical state, and morphology of the formed active coating were investigated using ICP-OES, EDX, SEM, and XPS techniques. The obtained results revealed that the prepared catalysts (Cu-Mn-oxide and Cu-Mn-Nb-oxide) have rough and developed surface and can be successfully used for the flue gas catalytic purification. The significant advantage of prepared catalysts is their suitability from technological application point of view, which differs this work from others dedicated to gas purification by SCR.

Keywords: flue gas, nitrogen oxides, selective catalytic reduction, transition metal oxides

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Authors: Haydar S. Al Shabbani, M. Marshall, R. Goodall

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Metal matrix composites (MMCs) have been explored for many applications for many decades. Recently, this includes investigations for thermal applications associated with electronics, such as in heat sinks. Here, to promote thermal conductivity, composites of a metal matrix with diamond particles are used. However, this class of composites has not yet been extensively examined for mechanical and tribological behavior, especially for applications that require extreme mechanical and tribological strength, such as the resistance to abrasive cutting. Therefore, this research seeks to develop a composite material with metal matrix and diamond particles which resist abrasive and cutting forces. The development progresses through a series of steps, exploring methods to process the material, understanding the mechanics of abrasive behavior and optimizing the composite structure to resist abrasive cutting. In processing, infiltration casting under gas pressure has been applied to molten aluminum to obtain a significant penetration of the metal into a preform of diamond particles. Different diamond particle sizes were used with different surface modifications (coated/uncoated), and to compare resulting composites with the same particle sizes. Al-1 wt.% Mg as a matrix alloy was utilised to investigate the possible effect of Mg on bonding phases during the infiltration process. The mechanical behavior and microstructure of the materials produced have been characterised. These tests showed that the surface modification of the diamond particles with a reactive material (Ti-coating) has an important role for enhancing the bonding between the aluminium matrix and diamond reinforcement as apparent under SEM observation. The effect of this improved bond is seen in the cutting resistance of the material.

Keywords: aluminium, composites, diamond, Ti-coated, tribology

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Authors: Gi-Beom Park, Hyong-Gi Park, Seong-Yong Lee, Jaeho Choi, Seok Hong Min, Tae Kwon Ha

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The Nb silicide-based alloy has the excellent high-temperature strength and relatively lower density than the Ni-based superalloy; therefore, it has been receiving a lot of attention for the next generation high-temperature material. To enhance the high temperature creep property and oxidation resistance, Si was added to the Nb-based alloy, resulting in a multi-phase microstructure with metal solid solution and silicide phase. Since the silicide phase has a low machinability due to its brittle nature, it is necessary to fabricate components using the powder metallurgy. However, powder manufacturing techniques for the alloys have not yet been developed. In this study, we tried to fabricate Nb-based alloy powder by the hydrogenation-dehydrogenation reaction. The Nb-based alloy ingot was prepared by vacuum arc melting and it was annealed in the hydrogen atmosphere for the hydrogenation. After annealing, the hydrogen concentration was increased from 0.004wt% to 1.22wt% and Nb metal phase was transformed to Nb hydride phase. The alloy after hydrogenation could be easily pulverized into powder by ball milling due to its brittleness. For dehydrogenation, the alloy powders were annealed in the vacuum atmosphere. After vacuum annealing, the hydrogen concentration was decreased to 0.003wt% and Nb hydride phase was transformed back to Nb metal phase.

Keywords: Nb alloy, Nb metal and silicide composite, powder, hydrogenation-dehydrogenation reaction

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Authors: Vishnu Goyal, Basant Agarwal

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Sentiment analysis research provides methods for identifying the people’s opinion written in blogs, reviews, social networking websites etc. Sentiment analysis is to understand what opinion people have about any given entity, object or thing. Sentiment analysis research can be broadly categorised into three types of approaches i.e. semantic orientation, machine learning and lexicon based approaches. Feature selection methods improve the performance of the machine learning algorithms by eliminating the irrelevant features. Information gain feature selection method has been considered best method for sentiment analysis; however, it has the drawback of selection of threshold. Therefore, in this paper, we propose a hybrid feature selection methods comprising of information gain and proposed feature selection method. Initially, features are selected using Information Gain (IG) and further more noisy features are eliminated using the proposed feature selection method. Experimental results show the efficiency of the proposed feature selection methods.

Keywords: feature selection, sentiment analysis, hybrid feature selection

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Authors: Leila Samiee, Amir Yadegari, Saeedeh Tasharrofi

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In the work presented here, nitrogen-doped graphene materials were synthesized and used as metal-free electrocatalysts for oxygen reduction reaction (ORR) under alkaline conditions. Paraphenylenediamine was used as N precursor. The N-doped graphene was synthesized under hydrothermal treatment at 200°C. All the materials have been characterized by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), Transmission electron microscopy (TEM) and X-ray photo-electron spectroscopy (XPS). Moreover, for electrochemical evaluation of samples, Rotating Disk electrode (RDE) and Cyclic Voltammetry techniques (CV) were employed. The resulting material exhibits an outstanding catalytic activity for the oxygen reduction reaction (ORR) as well as excellent resistance towards methanol crossover effects, indicating their promising potential as ORR electrocatalysts for alkaline fuel cells.

Keywords: alkaline fuel cell, graphene, metal-free catalyst, paraphenylen diamine

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Authors: C. Manjula, Lilly Florence

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Software technology is developing rapidly which leads to the growth of various industries. Now-a-days, software-based applications have been adopted widely for business purposes. For any software industry, development of reliable software is becoming a challenging task because a faulty software module may be harmful for the growth of industry and business. Hence there is a need to develop techniques which can be used for early prediction of software defects. Due to complexities in manual prediction, automated software defect prediction techniques have been introduced. These techniques are based on the pattern learning from the previous software versions and finding the defects in the current version. These techniques have attracted researchers due to their significant impact on industrial growth by identifying the bugs in software. Based on this, several researches have been carried out but achieving desirable defect prediction performance is still a challenging task. To address this issue, here we present a machine learning based hybrid technique for software defect prediction. First of all, Genetic Algorithm (GA) is presented where an improved fitness function is used for better optimization of features in data sets. Later, these features are processed through Decision Tree (DT) classification model. Finally, an experimental study is presented where results from the proposed GA-DT based hybrid approach is compared with those from the DT classification technique. The results show that the proposed hybrid approach achieves better classification accuracy.

Keywords: decision tree, genetic algorithm, machine learning, software defect prediction

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Authors: Obinna K. Ihesiulor, Krishna Shankar, Paul Smith, Alan Fien

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Excessive fretting wear at the taper-trunnion junction (trunnionosis) apparently contributes to the high failure rates of hip implants. Implant wear and corrosion lead to the release of metal particulate debris and subsequent release of metal ions at the taper-trunnion surface. This results in a type of metal poisoning referred to as metallosis. The consequences of metal poisoning include; osteolysis (bone loss), osteoarthritis (pain), aseptic loosening of the prosthesis and revision surgery. Follow up after revision surgery, metal debris particles are commonly found in numerous locations. Background: A stable connection between the femoral ball head (taper) and stem (trunnion) is necessary to prevent relative motions and corrosion at the taper junction. Hence, the importance of component assembly cannot be over-emphasized. Therefore, the aim of this study is to determine the influence of head-stem junction assembly by press fitting and the subsequent disengagement/disassembly on the connection strength between the taper ball head and stem. Methods: CoCr femoral heads were assembled with High stainless hydrogen steel stem (trunnion) by Push-in i.e. press fit; and disengaged by Pull-out test. The strength and stability of the two connections were evaluated by measuring the head pull-out forces according to ISO 7206-10 standards. Findings: The head-stem junction strength linearly increases with assembly forces.

Keywords: wear, modular hip prosthesis, taper head-stem, force assembly and disassembly

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Authors: Pierre Bauduin, Coralie Pasquier, Alban Jonchere, Luc Girard, Olivier Diat

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Ionic species, such as polyoxometalates (POMs) or (metal-) boron clusters, are at the frontier between ions and (charged-)colloids due to their nm size. We show here that the large size and low charge density of POMs, compared to classical ions, are responsible for a peculiar behavior called “super-chaotropy”. This property refers to the strong propensity of nano-ions to adsorb at neutral polar interfaces, via non-specific interactions. It has strong effects on phase transitions in soft matter and can, for example, stabilize colloidal systems such as surfactant foams. A simple way for evaluating and classifying nano-ions, such as POMs, according to their super-chaotropy is proposed here. The super-chaotropic behavior of nano-ions opens many opportunities in separation science, catalysis, and for the design of nanostructured hybrid materials.

Keywords: colloids, foams, surfactant, salt effect, colloidal stability, nano-ions

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Authors: Imran Ullah Imran

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Language contact is a familiar concept in the present global world. Across the globe, languages get mixed up at different levels. Borrowing, code-switching are some of the means through which languages interact. This study examines Pashto-English contact at word and syllable levels. By recording the speech of 30 Pashto native speakers, selected via 'social network' sampling, the study located a number of Pashto-English compound words, which is a unique contact of its kind. In data analysis, tokens were categorized on the basis of their pattern and morphological structure. The study shows that Pashto-English Bilingual Compound words (BCWs) are very prevalent in the Pashto language. The study also found that the BCWs in Pashto are completely productive and have their own meanings. It also shows that the dominant pattern of hybrid words in Pashto is the conjugation of an independent English root word followed by a Pashto inflectional morpheme, which contributes to the core semantic content of the construction. The BCWs construction shows that how both the languages are closer to each other. Pashto-English contact results into bilingual compound and hybrid words, which forms a considerable number of tokens in the present-day spoken Pashto. On the basis of these findings, the study assumes that the same phenomenon may increase with the passage of time that would, in turn, result in the formation of more bilingual compound or hybrid words.

Keywords: code-mixing, bilingual compound words, pashto-english contact, hybrid words, inflectional lexical morpheme

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Authors: Ahmadali Tahmasebimoradi, Chetra Mang, Xavier Lorang

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Thanks to the additive manufacturing process, lattice structures are replacing the traditional structures in aeronautical and automobile industries. In order to evaluate the mechanical response of the lattice structures, one has to resort to numerical techniques. Ansys is a globally well-known and trusted commercial software that allows us to model the lattice structures and analyze their mechanical responses using either solid or beam elements. In this software, a script may be used to systematically generate the lattice structures for any size. On the one hand, solid elements allow us to correctly model the contact between the substrates (the supports of the lattice structure) and the lattice structure, the local plasticity, and the junctions of the microbeams. However, their computational cost increases rapidly with the size of the lattice structure. On the other hand, although beam elements reduce the computational cost drastically, it doesn’t correctly model the contact between the lattice structures and the substrates nor the junctions of the microbeams. Also, the notion of local plasticity is not valid anymore. Moreover, the deformed shape of the lattice structure doesn’t correspond to the deformed shape of the lattice structure using 3D solid elements. In this work, motivated by the pros and cons of the 3D and beam models, a numerically hybrid model is presented for the lattice structures to reduce the computational cost of the simulations while avoiding the aforementioned drawbacks of the beam elements. This approach consists of the utilization of solid elements for the junctions and beam elements for the microbeams connecting the corresponding junctions to each other. When the global response of the structure is linear, the results from the hybrid models are in good agreement with the ones from the 3D models for body-centered cubic with z-struts (BCCZ) and body-centered cubic without z-struts (BCC) lattice structures. However, the hybrid models have difficulty to converge when the effect of large deformation and local plasticity are considerable in the BCCZ structures. Furthermore, the effect of the junction’s size of the hybrid models on the results is investigated. For BCCZ lattice structures, the results are not affected by the junction’s size. This is also valid for BCC lattice structures as long as the ratio of the junction’s size to the diameter of the microbeams is greater than 2. The hybrid model can take into account the geometric defects. As a demonstration, the point clouds of two lattice structures are parametrized in a platform called LATANA (LATtice ANAlysis) developed by IRT-SystemX. In this process, for each microbeam of the lattice structures, an ellipse is fitted to capture the effect of shape variation and roughness. Each ellipse is represented by three parameters; semi-major axis, semi-minor axis, and angle of rotation. Having the parameters of the ellipses, the lattice structures are constructed in Spaceclaim (ANSYS) using the geometrical hybrid approach. The results show a negligible discrepancy between the hybrid and 3D models, while the computational cost of the hybrid model is lower than the computational cost of the 3D model.

Keywords: additive manufacturing, Ansys, geometric defects, hybrid finite element model, lattice structure

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Authors: Golnush Masghati-Amoli, Paul Chin

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Over the past recent years, with the rapid increases in data availability and computing power, Machine Learning (ML) techniques have been called on in a range of different industries for their strong predictive capability. However, the use of Machine Learning in commercial banking has been limited due to a special challenge imposed by numerous regulations that require lenders to be able to explain their analytic models, not only to regulators but often to consumers. In other words, although Machine Leaning techniques enable better prediction with a higher level of accuracy, in comparison with other industries, they are adopted less frequently in commercial banking especially for scoring purposes. This is due to the fact that Machine Learning techniques are often considered as a black box and fail to provide information on why a certain risk score is given to a customer. In order to bridge this gap between the explain-ability and performance of Machine Learning techniques, a Hybrid Model is developed at Dun and Bradstreet that is focused on blending Machine Learning algorithms with traditional approaches such as scorecards. The Hybrid Model maximizes efficiency of traditional scorecards by merging its practical benefits, such as explain-ability and the ability to input domain knowledge, with the deep insights of Machine Learning techniques which can uncover patterns scorecard approaches cannot. First, through development of Machine Learning models, engineered features and latent variables and feature interactions that demonstrate high information value in the prediction of customer risk are identified. Then, these features are employed to introduce observed non-linear relationships between the explanatory and dependent variables into traditional scorecards. Moreover, instead of directly computing the Weight of Evidence (WoE) from good and bad data points, the Hybrid Model tries to match the score distribution generated by a Machine Learning algorithm, which ends up providing an estimate of the WoE for each bin. This capability helps to build powerful scorecards with sparse cases that cannot be achieved with traditional approaches. The proposed Hybrid Model is tested on different portfolios where a significant gap is observed between the performance of traditional scorecards and Machine Learning models. The result of analysis shows that Hybrid Model can improve the performance of traditional scorecards by introducing non-linear relationships between explanatory and target variables from Machine Learning models into traditional scorecards. Also, it is observed that in some scenarios the Hybrid Model can be almost as predictive as the Machine Learning techniques while being as transparent as traditional scorecards. Therefore, it is concluded that, with the use of Hybrid Model, Machine Learning algorithms can be used in the commercial banking industry without being concerned with difficulties in explaining the models for regulatory purposes.

Keywords: machine learning algorithms, scorecard, commercial banking, consumer risk, feature engineering

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