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When the COVID-19 coronavirus hit, the context-aware application users were willing to relax their context privacy preferences during the lockdown to cope their lives while staying home. Such disturbance in the privacy behavior affected the performance of Machine Learning (ML) algorithm that is trained on normal behavior. In this paper, we present the impact of the pandemic on the efficiency of the learning algorithm implementation of a privacy protection system. The system is composed of three modules, in this work we focus on Privacy Preferences Manager (PPM) module which is implemented using hybrid methodology based on a Statistical Model (SM) and Logistic Regression (LR) learning algorithm. The efficiency of the hybrid methodology is assessed using two real-world datasets collected prior and during the COVID-19 pandemic. The results show that the pandemic significantly impacted the efficiency of the hybrid methodology by 13.05% and 15.22% for the accuracy and F1 score respectively.

Capacitive deionization (CDI) shows promising potential for water desalination due to its high performance, energy efficiency, and environmental friendliness. Because of their excellent conductivit...

Microbial fuel cell (MFC) is a promising technology for simultaneous wastewater treatment and energy harvesting. The properties of the anode material play a critical role in the performance of the MFC. In this study, graphene oxide was prepared by a modified hummer's method. A thin layer of graphene oxide was incorporated on the carbon brush using an electrophoretic technique. The deoxygenated graphene oxide formed on the surface of the carbon brush (RGO-CB) was investigated as a bio-anode in MFC operated with real wastewater. The performance of the MFC using the RGO-CB was compared with that using plain carbon brush anode (PCB). Results showed that electrophoretic deposition of graphene oxide on the surface of carbon brush significantly enhanced the performance of the MFC, where the power density increased more than 10 times (from 33 mWm−2 to 381 mWm−2). Although the COD removal was nearly similar for the two MFCs, i.e., with PCB and RGO-CB; the columbic efficiency significantly increased in the case of RGO-CB anode. The improved performance in the case of the modified electrode was related to the role of the graphene in improving the electron transfer from the microorganism to the anode surface, as confirmed from the electrochemical impedance spectroscopy measurements.

In this work, Cu2O nanoparticles were successfully prepared onto the surface of two-dimensional graphitic carbon nitride (g-C3N4) by using a simple solution chemistry approach. An environment-friendly reducing agent, glucose, was used for the synthesis of Cu2O NPs onto the surface of g-C3N4 without using any surfactant or additives. The surface composition, crystalline structure, morphology, as well as other properties have been investigated using XPS, XRD, SEM, FTIR, FESEM, EDS, etc. The electrochemical measurements of the prepared materials demonstrated that Cu2O exhibited a weak oxidation activity towards urea, while g-C3N4 has no activity towards urea oxidation. The Cu2O supported on the surface of g-C3N4 (Cu2O-g-C3N4) demonstrated a significant activity towards urea oxidation that reached two times that of the unsupported one. The significant increase in the performance was related to the synergetic effect between the Cu2O and g-C3N4 support. The prepared composite materials demonstrated high stability towards urea oxidation as confirmed from the stable current discharge for around 3 h without any noticeable degradation performance.

A g-C3N4/VC composite material comprising of graphitic carbon nitride (g-C3N4) and Vulcan carbon (VC) with different ratios, i.e., 2:1, 1:1, and 1:2 were prepared through hydrothermal method without using any additives. These composite materials were further utilized as a support for Ni(OH)2 nanoparticles. These materials formed new type of Ni/(g-C3N4/VC) composite materials. The SEM images show the sheet-like structure of the graphitic carbon nitride. Although Ni nanoparticles' electrochemical activity over the surface for graphitic carbon nitride was slightly more compared to Ni supported on the Vulcan carbon, the Ni supported on the different composite supports demonstrated an outstanding activity compared with that over the single supports. Among the different composite ratios of the graphitic carbon nitride to the Vulcan carbon, the one with high Vulcan carbon, i.e., 2:1, exhibited the best performance that is nine-times the current density in comparison to that of Ni over Vulcan carbon at 0.5 V using 2 M urea in 1 M potassium hydroxide. The stability for the prepared Ni over the composite support was high, where the degradation in the current density for more than 2 hours was negligible.

In this work, standalone cobalt dendrites are prepared then doped with graphene flakes by a simple electroplating technique. Microstructural examination using SEM with EDX, as well as Raman spectroscopy measurements, verified the successful formation of graphene. The prepared material exhibit a favorably high electrochemical methanol oxidation activity with an onset oxidation potential of 0.07 V vs. Ag/AgCl, which is significantly lower than that of the Ni (0.35 V vs. Ag/AgCl). The doping process causes a decrease in the ohmic resistance of the material from 3.2 Ohm cm−2 to 2 Ohm cm−2, which consequently resulted in a significant increase in the current density from 35 mA cm−2 to 62 mA cm−2 using 1 M methanol at 0.5 V vs. Ag/AgCl. After two hours of current discharge at 0.5 V vs. Ag/AgCl, the catalyst doped with graphene showed a current density of 62 mA cm−2. This is an eight-times higher than that obtained in the case of the Ni nano-powder. An electrode prepared by depositing the catalyst on the surface of a highly conductive porous Ni foam was successfully used as the anode of a passive air cathode direct methanol fuel cell, demonstrating an open circuit voltage of 0.75 V using 0.25 M methanol in 1 M KOH.

A simple electrodeposition technique has been used to synthesize Co nanoparticles with a 3D leaf-like morphology at room temperature. The prepared Co material has a layered sheet structure of a few nanometers thickness. The surface area of the Co leaf-like structure is three times higher than that of the Co nanoparticles. The prepared nanoparticles exhibit high activity towards ethanol oxidation in alkaline media with an onset potential of 0 V vs Ag/AgCl, which is one of the lowest reported potentials for a non-precious catalyst. The current density is observed to increase with increasing ethanol concentration from 0.1 M to 2 M, after which it plateaus. Mixing the Co catalyst with Vulcan carbon (20 wt%) resulted in a 50% increase in current discharge at different ethanol concentrations due to the improvement in mass and charge transfer rates as confirmed by EIS measurements. Also, Co deposited in situ on the surface of nickel foam (NF) exhibited a high activity towards ethanol oxidation as a standalone electrode that is 10 times that of bare NF.

The introduction of autonomous vehicles (AVs) has led to a shift in liability from driver to AV. This paper is a systematic review of the literature on liability with AVs. Articles were selected from EBSCO, SCOPUS and PROQUEST and then sorted based on inclusion and exclusion criteria. The findings reveal that most such articles have been published in law journals and transport journals. The articles mainly discuss the steps being taken by developed countries, such as the US, the UK and Germany; the modification of existing laws; and the formulation of new laws. The articles also address the shift in liability from humans to AVs and affirm that there is no general rule on liability for AVs. Researchers conclude that liability would depend on the particular details of a situation, the role of the driver, the level of autonomy exercised by the vehicle, and the environmental factors among other considerations. Earlier papers have also suggested that ethical considerations should be studied when dealing with liability. Further research needs to be done on how users perceive liability and how liability evolves with the considerable changes in the law.

We report a density functional theory study of ZnO cluster doped with Eu and Mg along with native point defects using the generalized gradient approximation including the Hubbard parameter. The Zn atomic positions are found to be energetically more favorable doping sites than O. The Eu has a lower formation energy than Zn and O vacancies, helps in lowering the formation energy of point defects and induces spin polarization. Mg is less favorable dopant energetically and is not inducing any magnetism in the cluster. Presence of Eu and point defects along with Mg can help in sustaining spin polarization, implying that transition metal and rare earth dopant is a favorable combination to invoke desirable properties in ZnO based materials. Eu–Eu doping pair prefers ferromagnetic orientation and a spin flip is induced by Eu in the Eu–Mg configuration. Further, Eu doping increases the value of static refractive index and optical absorption in the UV region compared to the undoped ZnO cluster.

The quest for high performance supercapacitors from the energy-power point of view is commonly addressed from the constituting electrode materials and/or the electrolyte. Carbon-based double-layer capacitors are known for their high power density, whereas pseudocapacitors which use transition metal oxides/nitrides/sulfides or conductive polymers are known for their high energy density. In this work we show that one can modulate the energy storage capability of supercapacitors by mixing at preset ratios two types of carbon materials having two different energy storage capabilities. The time-domain and frequency-domain electrochemical characterization of five symmetric devices, in which electrodes made of carbon nanofibers (CNF) are mixed with cobalt-modified CNF (Co-CNF) at different mass proportions, show that as the Co-CNF content is increased, the effective capacitance, and hence the restored energy, is increased without affecting the power performance of the device. This opens up new opportunities for the modular design of supercapacitor electrodes using a small set of electric double-layer capacitive materials.

A series of BiOF/BiOI heterojunction composites photocatalysts has been prepared via a simple coprecipitation method and characterized by using UV–vis (UV–vis) diffuse reflectance spectroscopy (DRS), powder X-ray diffraction (PXRD), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), Brunauer-Emmett-Teller for determination of the specific surface area and porosity (BET), high resolution transmission electron microscopy (HRTEM) and photoluminescence (PL). The enhanced photocatalytic activity for removal of the pharmaceutical compound Diclofenac Potassium commercially available as Voltfast sachets under visible light irradiation was demonstrated by comparing heterojunction prepared composites photocatalysts with that of pure BiOF and BiOI photocatalysts prepared under the same conditions. Based on the experimental conditions, the highest activity was achieved for the composite contains 40% BiOF and 60% BiOI showing comparable activities to that of pure BiOI. To the best of our knowledge, this study is the first to report the preparation of BiOF/BiOI composites photocatalysts and their use in the photocatalytic removal of Diclofenac Potassium from aqueous solution.

Direct urea fuel cell (DUFC) is an attractive and inexpensive method for the simultaneous wastewater treatment (urine and urea-contaminated water) and electricity generation. Many efforts have been made to increase the catalytic activity of Ni-based DUFC anodic catalyst toward urea oxidation, which is considered to be the best non-precious catalyst in alkaline media so far. Alloying Ni with other metals and/or non-metals, and increasing its surface area demonstrated a power of up to 26.9 mW cm−2 at room temperature, which is comparable to that obtained in direct alcoholic fuel cells using high loading of precious catalyst. However, this is still viewed as low-performance. This review presents a comprehensive picture of the mechanism of urea oxidation on Ni-based catalysts, the poisoning effect of catalysts and its possible remedies, as well as the different approaches in preparing highly active catalysts. We also analyze the performance and associated issues of DUFC using newly applied strategies to increase its open-circuit voltage and power output via alternative oxidants and re-designed chemical conditions in the cell.

Selecting prospective programs in higher education can be a problematic and inefficient task for applicants. In particular, one of the most significant challenges entails locating a specific subset of programs likely to be a good fit. In this paper, clustering techniques are employed in evaluating a specifically created data set of AACSB-accredited doctoral programs in accounting so as to aggregate them by type. In so doing, one is then better positioned to identify which schools best align with his/her relevant characteristics and objectives, thus gaining insight concerning the most appropriate subset of schools to initially consider for application purposes. This approach provides meaningful differentiation between the various program types, offers a means for improving productivity relative to the university application process, and demonstrates promise as an initial foundation for eventual construction of a program recommendation system for use in ostensibly any program application initiative within the higher education domain.

Current demands for flexible services based on context-aware applications are mounting. The efficiency of such services mainly depends on acquiring, organizing, accessing, processing and sharing the user’s context. This context usage yield to more concerns and even more worries about the user’s data privacy. Hence, in this work we propose a privacy-aware method to address users privacy protection concerns in context-aware environments through automated decision-making processes by monitoring their privacy behavior and personal data usage.

International audience; Severe acute respiratory syndrome SARS-CoV-2 virus led to notable challenges amongst researchers in view of development of new and fast detecting techniques. In this regard, surface-enhanced Raman spectroscopy (SERS) technique, providing a fingerprint characteristic for each material, would be an interesting approach. The current study encompasses the fabrication of a SERS sensor to study the SARS-CoV-2 S1 (RBD) spike protein of the SARS-CoV-2 virus family. The SERS sensor consists of a silicon nanowires (SiNWs) substrate decorated with plasmonic silver nanoparticles (AgNPs). Both SiNWs fabrication and AgNPs decoration were achieved by a relatively simple wet chemical processing method. The study deliberately projects the factors that influence the growth of silicon nanowires, uniform decoration of AgNPs onto the SiNWs matrix along with detection of Rhodamine-6G (R6G) to optimize the best conditions for enhanced sensing of the spike protein. Increasing the time period of etching process resulted in enhanced SiNWs’ length from 0.55 to 7.34 µm. Furthermore, the variation of the immersion time in the decoration process of AgNPs onto SiNWs ensued the optimum time period for the enhancement in the sensitivity of detection. Tremendous increase in sensitivity of R6G detection was perceived on SiNWs etched for 2 min (length=0.90 µm), followed by 30s of immersion time for their optimal decoration by AgNPs. These SiNWs/AgNPs SERS-based sensors were able to detect the spike protein at a concentration down to 9.3 × 10−12 M. Strong and dominant peaks at 1280, 1404, 1495, 1541 and 1609 cm−1 were spotted at a fraction of a minute. Moreover, direct, ultra-fast, facile, and affordable optoelectronic SiNWs/AgNPs sensors tuned to function as a biosensor for detecting the spike protein even at a trace level (pico molar concentration). The current findings hold great promise for the utilization of SERS as an innovative approach in the diagnosis domain of infections at very early stages.

Background The web-based EatWellQ8 food frequency questionnaire (FFQ) was developed as a dietary assessment tool for healthy adults in Kuwait. Validation against reliable instruments and assessment of its reproducibility are required to ensure the accuracy of the EatWellQ8 FFQ in computing nutrient intake. Objective This study aims to assess the reproducibility and relative validity of the EatWellQ8 146-item FFQ, which included images of food portion sizes based on The Composition of Foods by McCance and Widdowson and food composition tables from Kuwait and the Kingdom of Bahrain, against a paper-based FFQ (PFFQ) and a 4-day weighed food record (WFR). Methods Reproducibility of the EatWellQ8 FFQ was assessed using a test-retest methodology. Participants were required to complete the FFQ at 2 time points, 4 weeks apart. To assess the relative validity of the EatWellQ8 FFQ, a subset of the participants were asked to complete a PFFQ or a 4-day WFR 1 week after the administration of the EatWellQ8 FFQ. The level of agreement between nutrient and food group intakes was estimated by repeated EatWellQ8 FFQ administration. The EatWellQ8 FFQ, PFFQ, and 4-day WFR were also evaluated using the Bland-Altman methodology and classified into quartiles of daily intake. Crude unadjusted correlation coefficients were also calculated for nutrients and food groups. Results A total of 99 Kuwaiti participants (64/99, 65% female and 35/99, 35% male) completed the study—53 participated in the reproducibility study and the 4-day WFR validity study (mean age 37.1 years, SD 9.9) and 46 participated in the PFFQ validity study (mean age 36.2 years, SD 8.3). Crude unadjusted correlations for repeated EatWellQ8 FFQs ranged from 0.37 to 0.93 (mean r=0.67, SD 0.14; 95% CI 0.11-0.95) for nutrients and food groups (P=.01). Mean cross-classification into exact agreement plus adjacent was 88% for nutrient intakes and 86% for food groups, and Bland-Altman plots showed good agreement for energy-adjusted macronutrient intakes. The association between the EatWellQ8 FFQ and PFFQ varied, with crude unadjusted correlations ranging from 0.42 to 0.73 (mean r=0.46, SD 0.12; 95% CI −0.02 to 0.84; P=.046). Mean cross-classification into exact agreement plus adjacent was 84% for nutrient intake and 74% for food groups. Bland-Altman plots showed moderate agreement for both energy and energy-controlled nutrient intakes. Crude unadjusted correlations for the EatWellQ8 FFQ and the 4-day WFR ranged from 0.40 to 0.88 (mean r=0.58, SD 0.13; 95% CI 0.01-0.58; P=.01). Mean cross-classification into exact agreement plus adjacent was 85% for nutrient intake and 83% for food groups. Bland-Altman plots showed moderate agreement for energy-adjusted macronutrient intakes. Conclusions The results indicate that the web-based EatWellQ8 FFQ is reproducible for assessing nutrient and food group intake and has moderate agreement compared with a PFFQ and a 4-day WFR for measuring energy and nutrient intakes.

Capacitive deionization (CDI) is one of the emerging desalination technologies that attracted much attention in the last years as a low-cost, energy-efficient, and environmentally-friendly alternative to other desalination technologies, such as multi-stage flash desalination (MSF) and multiple effect distillation (MED). The implementation of faradaic electrode materials is a promising method for enhancing CDI systems' performance by achieving higher salt removal characteristics, lower energy consumption, and better ion selectivity. Therefore, a novel CDI technology named Faradaic CDI (FCDI) that implements faradaic electrode materials arose as a high-performance CDI cell design. In this work, the application of FCDI cells in desalination and wastewater treatment systems is reviewed. First, the progress done on using various FCDI systems for saline water desalination is summarized and discussed. Next, the application of FCDI in wastewater treatment applications and selective ion removal is presented. A thorough comparison between FCDI and conventional carbon-based CDI is carried out in terms of working principle, electrode material's cost, salt removal performance, energy consumption, advantages, and disadvantages. Finally, future research consideration regarding FCDI technology is included to drive this technology closer towards practical application.

Generating true random bits of high quality at high data rates is usually viewed as a challenging task. To do so, physical sources of entropy with wide bandwidth are required which are able to provide truly random bits and not pseudorandom bits, as it is the case with deterministic algorithms and chaotic systems. In this work we demonstrate a reliable high-speed true random bit generator (TRBG) device based on the unpredictable electrical current time series of atmospheric pressure air microplasma (APAMP). After binarization of the sampled current time series, no further post-processing was needed in order for the bitstreams to pass all 15 tests of the NIST SP 800-22 statistical test suite. Several configurations of the system have been successfully tested at different sampling rates up to 100 MS/s, and with different inter-electrode distances giving visible/non-visible optical emissions. The cost-effectiveness, simplicity and ease of implementation of the proposed APAMP system compared to others makes it a very promising solution for portable TRBGs.

As context-aware applications are becoming increasingly popular, there are also mounting demands for privacy protection systems. In our work, we propose a context-aware privacy protection system that consists of three modules and aims to recognize the user privacy behavior, classify the context-aware applications and recommend a set of protection action scenarios for the user privacy profile settings. Each module is a challenging problem that needs to be addressed using supervised and unsupervised Machine Learning (ML) algorithms. Part 1 of our work, this paper, consists of deploying hybrid techniques to handle the privacy controller module tasks. Logistic Regression (LR) learning algorithm is integrated with Statistical Method (SM) to recognize user privacy complex activities. The potential of the proposed system is demonstrated using a large-scale real-world dataset provided by institutes from Kuwait, the United States and Belgium. The system demonstration shows promising results with an accuracy of 97.9%.

Petrophysical Groups (PG) from cores and log facies (electrofacies) are two of the main outputs generated in the petrophysical domain. Those are particularly contributors to the highest degree of uncertainty during the reservoir modeling, with the subsequent high-impact in field development decisions. Detailed core analysis is the preferred main source of information to condition the PG, however, since there are generally more un-cored than cored wells, logs are the most frequently applied source of information to extrapolate petrophysical groups by the use of log facies. The approach of this investigation is to apply machine learning to move from the core domain to the log domain and to determine relationships to generate properties for the three-dimensional reservoir model. All wells have a full set of logs (Gamma Ray, Resistivity, Density, PEF and Neutron) and few have routine core analysis (Permeability, Porosity and MICP). On a first pass, logs from selected wells are classified into Self Organizing Maps (SOM) without analytical supervision. The idea of this step is to observe the capability of the log data to self-classify according to the log response. In a second stage, core data is used to define petrophysical groups (PG) by clustering the data in into similar pore throats from the MICP and permeability vs. porosity relationships, also thin section were used to introduce geological meaning to the to the PG. The PG are linked to the NMR pore-size distribution (Invasion correction were applied in order to observe only the pore geometry content on the T2 distribution) by correlating into a pre-determined standard NMR pore geometry distribution, the result is that each PG group has a particular T2 range and proportion. In the next step a pseudo NMR curve is create by the use of a Neural Network constrained by the range and proportions obtained and observed in cored wells. This pseudo NMR can be generated in all wells (even the ones Un-cored or without NMR) and generate PG groups at log scale hence the PG logs are controlled by the relationship between core (Pore throat, permeability, porosity and Geological Facies) and pore-size distribution coming from the NMR Log. The result is a robust model capable to capture the core relationships and able to predict properties preserving the geological features of the reservoir. The application of this method makes possible to determine the minimum and most relevant source of data to address the issues caused by the heterogeneity of the rock. The applied workflows also show how to break the autocorrelation of variables and maximize the usage of logs. This work demonstrates that the introduced data-driven methods are useful for rock typing determination and address several of the challenges related to core to log properties derivation.

Burnishing is an advanced finishing process that produces higher-quality surfaces with better hardness and roughness than conventional finishing processes. Herein, a flexible magnetic burnishing brush comprising stainless steel pins under permanent magnet poles was used to investigate the influence of multiple passes and directions on the produced surface of soft and rough ground prepared brass. In total, five different samples were burnished on each of the two brass samples prepared. Four samples were processed in the same direction for up to four passes and the fifth sample was processed with two passes in the opposite direction. Results indicate that there was approximately a 30% increase in hardness and an 83% increase in microroughness for rougher-surface brass samples. For smoothly prepared surfaces, there was approximately a 14% increase in hardness and a 35% increase in microroughness. In the same direction of multi-pass burnishing, increasing the number of passes negatively affected surface roughness, for rougher surfaces, the surface hardness reduced and process uniformity increased owing to surface over-hardening and flaking mechanisms, and for smoother surfaces, the hardness, roughness, and process non-uniformity increased with the number of passes owing to repeated surface deformation at some locations and high flaking at other locations. Compared to single-pass burnishing, wherein the surface roughness and microhardness showed almost no change with high process uniformity, in burnishing with two opposite-direction passes, the produced surface exhibited better surface roughness, process uniformity, and microhardness improvements owing to a reverse strain mechanism. Hence, opposite burnishing passes are recommended.

Microbial fuel cell (MFC) is an emerging method for extracting energy from wastewater. The power generated from such systems is low due to the sluggish electron transfer from the inside of the biocatalyst to the anode surface. One strategy for enhancing the electron transfer rate is anode modification. In this study, iron nanostructure was synthesized on a carbon cloth (CC) via a simple electroplating technique, and later investigated as a bio-anode in an MFC operated with real wastewater. The performance of an MFC with a nano-layer of iron was compared to that using bare CC. The results demonstrated that the open-circuit voltage increased from 600 mV in the case of bare CC to 800 mV in the case of the iron modified CC, showing a 33% increase in OCV. This increase in OCV can be credited to the decrease in the anode potential from 0.16 V vs. Ag/AgCl in the case of bare CC, to &minus, 0.01 V vs. Ag/AgCl in the case of the modified CC. The power output in the case of the modified electrode was 80 mW/m2&mdash, two times that of the MFC using the bare CC. Furthermore, the steady-state current in the case of the iron modified carbon cloth was two times that of the bare CC electrode. The improved performance was correlated to the enhanced electron transfer between the microorganisms and the iron-plated surface, along with the increase of the anode surface- as confirmed from the electrochemical impedance spectroscopy and the surface morphology, respectively.

Remote areas and poor communities are occasionally deprived of access to freshwater. It is, therefore, critical to providing a cheap and efficient desalination system that encourages the development of those communities and benefiting society at large. Solar stills are an affordable, direct method of water desalination, but its productivity is the critical challenge hindering its application. To ease this, research has focused on the role of nanofluids to improve heat transfer. Other works have focused on improving the design in consort with utilizing the nanofluids. This review reports and discusses the substantial role of nanofluids to enhance the productivity and energy utilization efficiency of the solar stills. Specifically, the mechanism of energy transfer between the nanoparticles and the base fluid. This includes both plasmonic and thermal effects. It is evident that nanofluid utilization in small fraction enhanced the thermal conductivity compared to base fluid alone. Alumina was found to be the most suitable nanoparticle used as nanofluid inside the solar stills due to its availability and lower cost. Still, other competitors such as carbon nanostructures need to be investigated as it provides higher enhancement of thermal conductivity. Also, several aspects of energy utilization enhancement have been discussed, including innovative application techniques. The challenges of such integrated systems are addressed as well.

Oxygen-free copper was processed by equal-channel angular pressing (ECAP) at room temperature for 1, 4 and 8 passes and then the ECAP specimens were further deformed by dynamic testing at 298 K using a strain rate of 10 s−1. Experiments were conducted to investigate the influence of the initial microstructures induced by ECAP on the subsequent grain refinement and mechanical properties after dynamic testing. The results show the strength of copper increased with increasing numbers of ECAP passes and a significant additional grain refinement was produced in the ECAP specimens through the dynamic testing. Thus, the initial grain sizes after ECAP for 1, 4 and 8 passes were ~16, ~4.4 and ~2.9 μm, respectively, and these values were reduced to ~400, ~330 and ~300 nm by dynamic testing, The grains were refined by conventional dislocation processes in the 1-pass specimen but there was evidence for dynamic recrystallization in the specimen processed by 8 passes.

We report the synthesis of aryldiazonium tetrachloroaurate(III) salts [X-4-C6H4N≡N]AuCl4 (X = F, Cl, Br, I, CN, NO2) and their mild reduction to covalently functionalized nanoparticles. The synthesis of the salts was carried out by the oxidation of anilines, dissolved in HCl, using sodium nitrite followed by the exchange of the counter anion with [AuCl4]- in water. In another procedure, the anilines were protonated with H[AuCl4] in acetonitrile followed by one-electron oxidation using nitrosonium salt [NO]X (X = BF4−, PF6−). Raman and ATR-FTIR spectroscopy displayed the diazonium νN≡N and Raman showed the tetrachloroaurate νAu-Cl stretching frequencies. X-ray crystal structure of [NO2-4-C6H4N≡N]AuCl4 salt showed N≡N bond distance typical of a triple bond. Gold-aryl nanoparticles were constructed by the mild chemical reduction of the diazonium gold(III) salts using 9-borabicyclo[3.3.1]nonane (9-BBN). Nanoparticles hydrodynamic diameter, elemental composition, dynamics information, and stability data were determined. Transmission electron microscopy (TEM) measurements showed limited aggregation due to the small suppressing organic shell. However, dynamic light scattering (DLS) measurements showed considerable aggregation in acetonitrile. X-ray photoelectron spectrometry (XPS) showed the gold core in zero oxidation state and manifested the gold-organic shell connectivity. The –N=N-aryl interfacial formation on the gold surface can be ruled out since the N1s peak assigned to the diazonium moiety showed no sign in the XPS nitrogen area in addition to its absence in the ATR-FTIR spectra. Raman spectroscopy measurements showed a peak assigned to gold-carbon bonding supported by density functional calculations (DFT) on Au20-C6H4-CN model.

There is a tremendous interest in the fabrication of novel hemocompatible nanoparticles for applications in theranostics. In this context, bovine serum albumin (BSA) conjugates with the water-soluble and super robust gold-aryl nanoparticles truncated with carboxylic functionals were synthesized. The gold-aryl nanoparticles were fabricated by the mild reduction of the diazonium gold(III) salt [HOOC-4-C6H4N≡N]AuCl4. The gold core size and the presence of BSA sheath encapsulating Au−COOH nanoparticles were concluded from transmission electron microscopy (TEM). Clear spectral changes supported by quantitative X-ray photoelectron spectrometry (XPS) surface analysis are visible: the C1s/Au4d intensity ratio increased sharply and the gold features were very well attenuated after BSA attachment, which brings more nitrogen essentially due to NH-C = O peptide links. The conjugation of BSA with Au−COOH nanoparticles resulted in the isoelectric point (pI) change from 4.7 to a range of 4.1-5.0. The robustness of the bioconjugates can be concluded based on the high ζ-potential values and the resistance to drastic pH conditions. The high encapsulation efficiency percentage (EE%) calculated using Bradford protein assay was in a range of 90.0–94.6% under physiological pH values. Taken together, overall studies imply the presence of interaction between the Au−COOH nanoparticles and BSA. In this study we investigated the interaction of gold nanoparticles and their BSA conjugates with human red blood cells (RBCs), which might cause cell deformity and hemolysis. To elaborate on the uniqueness of the bioconjugates, they showed negligible hemolysis or morphology deformation to cells membrane visualized using light and phase contrast microscopes. Quantitative measurements of hemoglobin leached out of the cell membrane using UV–vis showed negligible hemolysis. The high physiological stability of the conjugates fosters their applications in intravenous drug delivery supported by the long blood circulation half-life.

This work presents the simple synthesis and simultaneous deposition of graphene nanoplatelets onto pure copper substrates for use as capacitive deionization electrodes. Copper is cheap and abundant material that can easily be fabricated into electrodes but suffers from high reactivity in solution with unpredictable consequences. The deposition of turbostratic graphene layer using the proposed high energy centrifugal milling technique introduces a chemically inert, but electrically conductive surface layer that extends the operational lifetime of the copper working electrode many folds compared to the bare pure copper one. In the trials presented here the operation of the pure copper electrode degraded almost instantly as the electrochemical cell was activated, compared to a smooth 60-minute operation of its graphene-coated counterpart. The graphene electrode was successful in reducing the solution conductance by more than 12% for the test period, which renews the interest in copper as an effective counter electrode for capacitive deionization applications. The quality of graphene deposition is verified via Raman spectroscopy, while the characterization of the copper chloride is done via X-ray Diffraction. The deionization process resulted in the production of Cu2Cl(OH)3 deposits on the copper electrode, which is mentioned as a viable method of producing it, although it is an unexpected result of this work.

This study unravels the soft chemical synthesis of Bi2O3/ZnO (BZO) nanocomposites having nano-cones like morphology with tunable optical and luminescent properties. The prepared BZO samples with varying Bi2O3 concentrations have been characterized for structural, morphological, band gap energy, photoluminescence (PL) and antibacterial characteristics. Structural and morphological investigations revealed the separate single wurtzite phase of ZnO and monoclinic phase of Bi2O3 without any undesired phases with dominant nano-cones like morphology. Optical and PL analysis have depicted the band gap widening, enhanced ultra-violet (UV) emission and decreased defects densities of BZO nanocomposites as compared to pristine ZnO nano-cones. Interestingly, a good correlation between defects and antibacterial activity of ZnO nanostructures has been found.

This paper presents the results obtained for incorporating the Al65Cu24Fe11material with the conventional TiO2 as the electron injection layer in dye-sensitized solar cells. The icosahedral phase of the Al-Cu-Fe system has attractive physical and optical properties at the target composition, and is obtained by synthesizing the material via the facile high energy ball milling process to ensures the highest possible interdiffusion of elemental powders, followed by heat treatment. The evolution of the i-phase is confirmed via X-ray diffraction, scanning electron microscopy and energy dispersive x-ray spectroscopy. The optical absorption and electrical properties of the compound are investigated by spectrometry, four probe measurement and Mott-Schottky analysis, respectively. Different cells with different percentages (x value) of (TiO2)1-x/(Al65Cu24Fe11)xare constructed and tested to obtain the electrical characteristic curves, efficiency and fill factor to quantify the effect of the proposed material mixture.

Carbon-based nanofluids are viewed as promising thermal fluids for heat transfer applications. However, other properties, such as electrical conductivity and electrochemical behavior, are usually overlooked and rarely investigated despite their importance for the overall performance characterization of a given application. In this study, we synthesized PAN-based carbon nanofibers (CNF) by electrospinning, and characterized them using electron microscopy, X-ray diffraction, X-ray photoelectron spectroscopy, Raman spectroscopy, and thermogravimetric analysis. Thermoelectrical and electrochemical measurements were carried out on nanofluids. We found that, although CNF nanofluids exhibit good thermal and electrical properties with a negligible corrosive effect, the suspensions tend to sediment within a few days. However, acid treatment of CNF (F-CNF), which resulted in the shortening of the fibers and the appearance of surface-oxygenated species, made F-CNF-based nanofluids exhibit superior stability in water that extended for more than 90 days, with consistent and superior thermal and electrical properties.

One of the main challenges facing the development of urea fuel cells is the low catalytic activity of the anode. Ni decorated carbon nano-fiber is a promising anode catalyst in urea fuel cells. In this study, we have investigated the effect of Cd doping of Ni decorated carbon nano-fiber on catalytic activity for urea oxidation. The catalyst was prepared by heat treatment of electrospun nano-fibers containing different percentages of Ni and Cd acetates in poly(vinyl alcohol) under an inert atmosphere at 850 °C. The initial percentages of the Cd acetate to Ni acetate in the polymer solution was set at 5, 10, 30, 50 and 70 wt.%. The introduction of Cd significantly improved the electro-catalytic activity for urea oxidation. The sample that was prepared with initial 50 wt.% Cd acetate showed the best activity for urea oxidation activity using different urea concentrations, 0.33 M–3 M. The introduction of Cd improved both the quality and the number of active sites for the urea oxidation as seen from the shift of the anodic peak potential and anodic peak current density, respectively.

The link between energy and climate change is fundamental - energy accounting for two-thirds of global greenhouse gas emissions. Of all countries, those of the Arabian Peninsula are synonymous with energy and the supply and use of fossil fuels. However driven by commitments to international climate change agreements the Gulf Cooperation Council (GCC) countries have been developing alternative energy strategies with targets for renewables. This paper presents the outputs of biomass resource modelling analyses that identify bioenergy opportunities across the region. Municipal wastes are found to represent a leading opportunity for bioenergy with a combined 19.35 Mtpa of resource across the GCC currently being sent to landfill that could otherwise be used for energy. The research finds that up to 22.5% of GCC country electricity could be generated from bioenergy technologies fuelled by indigenous biomass resources. Interviews were undertaken with Director-level GCC individuals from industry and government and a survey was facilitated to gain an understanding of perceptions of bioenergy and the potential barriers to its greater deployment. There was majority support for renewable technologies and for bioenergy, however a majority of respondents were found to be ‘not willing’ or ‘unsure’ when asked if they would be willing to take any individual actions such as recycling to support bioenergy schemes. High availability of cheap fossil fuels, stimulated by fossil fuel subsidies is identified as the greatest barrier to renewables. The GCC's commitment to international climate and sustainability targets represents an opportunity to develop a strategy to phase out fossil fuels.

Mesoporous Co dendrites prepared by electroplating have a surface area of 145 m2g−1, which is three times that of Co nanoparticles. The Co dendrites demonstrate superior urea oxidation activity compared to Ni or Co nanoparticles prepared using chemical reduction. The onset potential with Co dendrites is around 0 V “vs. Ag/AgCl” using 2 M urea, that is remarkably lower than 0.35 V “vs. Ag/AgCl” for Ni catalyst at optimum urea concentration of 0.5 M. The current produced in case of the Co dendrites using 2 M urea at 0.5 V “vs. Ag/AgCl” was six times that obtained using Ni. The in-situ measurements using Co dendrites on the Ni foam as anode and Prussian blue as cathode catalyst demonstrated a 21 mWcm−2 at 20 °C. These are the first reported results for a complete Ni-free nonprecious anode and cathode catalysts under real fuel cell operation with high performance comparable to those obtained using precious catalyst under same conditions.

Oxygen-free copper of 99.95Â wt.% purity was severely deformed at room temperature by two modes of severe plastic deformation, equal-channel angular pressing (ECAP) and high-pressure torsion (HPT). ECAP was performed using 4, 16 and 24 passes, and HPT was performed using 1/2, 1 and 10 turns. The results show that while recovery occurs during both ECAP and HPT processing, copper shows a faster recovery rate with HPT processing than ECAP. The occurrence of recovery was observed at an equivalent strain exceeding â¼12 that led to an enhancement in the uniform plastic deformation. The influence of recovery behaviour on the mechanical properties was investigated using X-ray diffraction, microhardness and tensile testing. Keywords: Ductility, Equal-channel angular pressing, High-pressure torsion, Recovery, Strain rate sensitivity, Work hardening

Graphene nanosheets (GNS) reinforced Al2O3 nanocomposites were prepared by a rapid sintering route. The microhardness and fracture toughness values of the resulting nanocomposites simultaneously increased due to efficient graphene nanosheet incorporation and chemical interaction with the Al2O3 matrix grains. The properties enhancement is attributed to uniformly dispersed graphene nanosheet in the consolidated structure promoted by high surface roughness and ability of graphene nanosheet to decorate Al2O3 nanoparticles, strong GNS/Al2O3 chemical interaction during colloidal mixing and pullout/crack bridging toughening mechanisms during mechanical testing. The GNS/Al2O3 interaction during different processing stages was thoroughly examined by thermal and structural investigation of the interfacial area. We report formation of an intermediate aluminum oxycarbide phase via a confined carbothermal reduction reaction at the GNS/Al2O3 interface. The graphene nanosheet surface roughness improves GNS/Al2O3 mechanical attachment and chemical compatibility. The Al2O3/GNS interface phase facilitates efficient load transfer, thus delaying failure through impediment of crack propagation. The resulting nanocomposites, therefore, offer superior toughness.

Bipolar electrochemistry is used as an economical, single-step, and scalable process for the oxidation of a wireless graphite substrate, and the subsequent electrophoretic deposition of graphene oxide thin film on a second wireless substrate. An all-solid-state symmetric double-layer capacitor (EDLC) using binderless reduced graphene oxide electrodes exhibited outstanding reversibility and capacitance retention over 18000 cycles, as well as superior capacitive behavior at far-from-dc frequencies (for example 45 and 47 μ F cm-2 ), effective capacitances at 75 and 189 Hz, respectively (computed using a series resonance network with ideal inductors), compared to 55 μ F cm-2 at close-to-dc (computed from cyclic voltammetry at 10 mV s-1 ). This makes the device well-suited for ac filtering applications. A one-hour thermal treatment of the electrodes at 900 °C under vacuum increased the capacitance 13-fold (719 μ F cm-2 ) at close-to-dc, which decreased to 185 and 150 μ F cm-2 as the frequency was increased to 37 and 106 Hz, respectively These properties make this device suitable for both reasonable dc energy storage and higher frequency applications.

Graphene is a 2-D carbon material showing considerable prominence in a wide range of optoelectronics, energy storage, thermal and mechanical applications. However, due to its unique features which are typically associated with difficulty in handling (ultra-thin thickness and hydrophobic surface, to name a few), synthesis and subsequent deposition processes are thus critical to the material properties of the prepared graphene films. While existing synthesis approaches such as chemical vapor deposition and epitaxial growth can grow graphene with high degree of order, the costly high temperature and/or high vacuum process prohibit the widespread usage, and the subsequent graphene transfer from the growth substrates for deposition proves to be challenging. Herein, a low-cost one-step synthesis and deposition approach for preparing few-layer graphene (FLG) on flexible copper substrates based on dry ball-free milling of graphite powder is proposed. Different from previous reports, copper substrates are inserted into the milling crucible, thus accomplishing simultaneous synthesis and deposition of FLG and eliminating further deposition step. Furthermore, while all previously reported high energy milling processes involve using balls of various sizes, we adopt a ball-free milling process relying only on centrifugal forces, which significantly reduces the surface damage of the deposition substrates. Sample characterization indicates that the process yields FLG deposited uniformly across all tested specimens. Consequently, this work takes graphene synthesis and deposition a step closer to full automation with simple and low-cost process.

This paper presents the results obtained for dye-sensitized solar cells with an Al65Cu24Fe11 mesoporous layer replacing the conventional TiO2 layer. The synthesis of the icosahedral quasicrystalline Al-Cu-Fe compound is done by high energy ball milling to ensure the highest possible diffusion of the starting powder elemental materials, and the evolution of the desired microstructure is monitored via X-ray diffraction, scanning electron microscopy and energy dispersive x-ray spectroscopy. The optical absorption and electrical properties of the compound was characterized by spectrometry, four probe measurement, as well as Mott-Schottky analysis, respectively, and compared with those of TiO2. Natural beetroot dye sensitizer was used in this, where its optical absorptivity property has been investigated. A natural organic dye extracted from beetroot is selected for the application as it has the widest absorption at the UV-Vis range. Two identical cells are constructed, one with the reference TiO2 material and the other with Al-Cu-Fe icosahedral compound as the mesoporous layer. The electrical characteristic curves, efficiency and fill factor were calculated for both. Power conversion efficiency enhancement from 0.4% to 0.827% was shown.

Nanoparticle (NP) synthesis by biological systems is more cost-effective, safe, and environmentally friendly when compared to currently used chemical and physical methods. Although many studies have utilized different plant extracts to synthesize NPs, few studies have incorporated living plants. In this study, silver nanoparticles (AgNPs) were synthesized exogenously by Tephrosia apollinea living plant system under the combined stresses of silver nitrate and different levels of drought stress simulated by Polyethylene glycol (PEG) (0, &minus, 0.1, &minus, 0.2, and &minus, 0.4 MPa for three and six days). Biomass, cell death, and H2O2 content were evaluated to determine the toxicological effect of the treatments on the plant. More severe effects were detected in day 6 plants compared to day 3 plants, and at higher drought levels. UV-visible spectrum, energy dispersive X-ray spectroscopy, X-ray diffraction, scanning electron microscope, and Fourier transform infrared spectroscopy were used to detect and characterize the T. apollinea synthesized NPs. The shapes of the NPs were spherical and cubic with different phytochemicals being the possible capping agents. Broth microdilution was used to determine the antimicrobial activity of the NPs against Escherichia coli and Staphylococcus aureus. In this case, antimicrobial activity increased at higher PEG concentrations. Bactericidal effects were observed against E. coli, while only bacteriostatic effects were detected against S. aureus.

Digital images have a serious influence over all the world, since, images have a very tangible importance, which impacts several people needs, this gave image retrieval researches this importance. So, Content-based image retrieval (CBIR) became one of the challenges in information retrieval and image processing fields, its services needs to apply for both business and science domains. In this paper we have proposed a CBIR approach that based on statistical methods feature selection via k-nearest neighbor (KNN) technique. Hence, supervised learning is employed for CBIR to train WANG database images, then the query image was the tested sample, and among predicted class we have filtered the final results. Number of randomly selected query images have been tested via this approach, with a variation of CBIR criteria, which have varied among image types, category query, and threshold distances. The average results have presented in three result groups, some RGB images results have showed good evaluation, in term of precisions measure, also grayscale and RGB images have varied values; on the evaluation of f-measures results, which have changed according some different CBIR factors. Proposed feature selection have made CBIR simpler and effective, this have been showed in high precision evaluation in final results.

A novel g-C3N4/VC composite was prepared by adopting simple hydrothermal treatment without using any additives from bulk g-C3N4 and Vulcan XC-72R (VC) in different ratios. Further, the resulting composite materials were used as a support for the synthesis of Cu2O NPs. The use of g-C3N4/VC not only acts as a support for the Cu2O NPs but also it forms a new type of novel composite materials, i.e., Cu2O-g-C3N4/VC. Various ratios (1:1, 1:2 and 2:1) of g-C3N4 and VC were used for the synthesis of three different types of the composite materials such as Cu2O-g-C3N4/VC(1:1), Cu2O-g-C3N4/VC(1:2), and Cu2O-g-C3N4/VC(2:1). The structures, surface properties, elemental compositions, and morphologies of synthesized materials were analyzed by various instrument methods such as FTIR, XRD, FESEM, Raman, EDS, BET, etc. Then the electrochemical activity of those resulting Cu2O-g-C3N4/VC composite materials were examined towards urea oxidation. The catalytic activity of Cu2O-g-C3N4/VC composite materials were found to be influenced by the variation of the g-C3N4 to VC ratio. The Cu2O-g-C3N4/VC(1:2) composite presented a higher current density (25.3 mAcm−2) as compared to that of Cu2O-g-C3N4/VC(1:1) (21.2 mAcm−2) and Cu2O-g-C3N4/VC(2:1) (13.5 mAcm−2) at 0.6 V using 2 M urea. The observed higher catalytic activity of this Cu2O-g-C3N4/VC (1:2) composite material compared to Cu2O-g-C3N4/VC (1:1) and Cu2O-g-C3N4/VC (2:1) is due to its higher surface area arising from different morphology compared to that of others. The Chronoamperometric measurements of the composite materials demonstrated their high stability upto 2 h without any degradation in the current density.

A biocompatible graphitic carbon nitride (g-C3N4) was prepared on the surface of carbon brush fiber (CB) via a facile one-step preparation method. The prepared g-C3N4 formed a composite with the carbon brush’s fibers (g-C3N4@CB), as shown from the XRD analysis. The g-C3N4@CB was used as an anode in a yeast-based microbial fuel cell (MFC), and demonstrated an outstanding performance compared to plain CB. An anode potential of −0.27 V “vs. Ag/AgCl” and an open-circuit voltage of 0.77 V was obtained in the case of the composite electrode, compared to −0.1 V vs. Ag/AgCl and 0.62 V, respectively, in the case of the CB. The cell using the composite electrode demonstrated a maximum power of 772 mWm−2, which is twelve times that obtained using the CB. The outstanding performance of the composite electrode can be credited to the biocompatibility of the composite anode and its roughness, which improved the yeast biofilm formation and decreased the ohmic resistance. This is the first report involving the application of g-C3N4 in a yeast-based MFC, and it demonstrated promising results which can be used for other types of MFCs.

Since centrifugal pumps consume a mammoth amount of energy in various industrial applications, their design and optimization are highly relevant to saving maximum energy and increasing the system’s efficiency. In the current investigation, a centrifugal pump has been designed and optimized. The study has been carried out for the specific application of transportation of slurry at a flow rate of 120 m3/hr to a head of 20 m. For the optimization process, a multi-objective genetic algorithm (MOGA) and response surface methodology (RSM) have been employed. The process is based on the mean line design of the pump. It utilizes six geometric parameters as design variables, i.e., number of vanes, inlet beta shroud, exit beta shroud, hub inlet blade draft, Rake angle, and the impeller’s rotational speed. The objective functions employed are pump power, hydraulic efficiency, volumetric efficiency, and pump efficiency. In this reference, five different software packages, i.e., ANSYS Vista, ANSYS DesignModeler, response surface optimization software, and ANSYS CFX, were coupled to achieve the optimized design of the pump geometry. Characteristic maps were generated using simulations conducted for 45 points. Additionally, erosion rate was predicted using 3-D numerical simulations under various conditions. Finally, the transient behavior of the pump, being the highlight of the study, was evaluated. Results suggest that the maximum fluctuation in the local pressure and stresses on the cases correspond to a phase angle of 0°–30° of the casing that in turn corresponds to the maximum erosion rates in the region.

The rising environmental problems due to fossil fuels’ consumption have pushed researchers and technologists to develop sustainable power systems. Due to properties such as abundance and nontoxicity of the working fluid, the supercritical carbon (sCO2) dioxide Brayton cycle is considered one of the most promising technologies among the various sustainable power systems. In the current study, a mathematical model has been developed and coded in Matlab for the recompression of the supercritical carbon dioxide Brayton cycle sCO2-BC. The real gas properties of supercritical carbon dioxide (sCO2) were incorporated into the program by pairing the NIST’s Refporp with Matlab© through a subroutine. The impacts of the various designs of the cycle’s individual components have been investigated on the performance of sCO2−BC. The impact of various sedative cycle parameters, i.e., compressor’s inlet temperature (T1), and pressure (P1), cycle pressure ratio (Pr), and split mass fraction (x), on the cycle’s performance (ηcyc) were studied and highlighted. Moreover, an optimization study using the genetic algorithm was carried out to find the abovementioned cycle’s optimized values that maximize the cycle’s per-formance under provided design constraints and boundaries.

The accumulation of dust pollution on the photovoltaic (PV) module can have a significant effect on the productivity and efficiency of PV systems in different locations in the world. Dust which accumulated over time on the PV module and is based on weather conditions led to the reduction in the effectiveness of solar cells. The aim of this research was to experimentally investigate the effect of the natural dust and the effects of environmental parameters on PV performance. The experiments were conducted to propose a model for the current, voltage, power and efficiency and to simulate the effect of environmental parameters on PV performance. The natural dust investigated consisted of different compounds: SiO2 (45.53 %), CaO (24.62 %), Al2O3 (10.83 %), Fe2O3 (10.46 %), MgO (6.33 %), K2O (0.87 %), TiO2 (0.45 %), SO3 (0.24 %), MnO2 (0.21), Cr2O3 (0.23 %), SrO (0.13 %) and NiO (0.09 %). It was found that the most accurate correlation is a polynomial from seventh degree for current, voltage, power and efficiency, fourth degree for solar radiation and temperature, cubic degree for humidity and wind velocity. The coefficients of general model are 0.6343, 0.0110, 0.0 and 0.0001 for PV module, respectively, with 0.0011 fitting factor. The proposed model has been validated using models in the literature.