Preparation and evaluation of Ni/γ-Al2O3 catalysts promoted by alkaline earth metals in glycerol reforming with carbon dioxide

Glycerol is the main by-product in the biodiesel process and can be considered as a promising and renewable source for hydrogen generation through the reforming process. In this work, catalysts with 15 wt% Ni supported on 3 wt% M ? Al₂O₃ (M = MgO, CaO, SrO, and BaO) were prepared and employed in the glycerol dry reforming (GDR) reaction to produce hydrogen and carbon monoxide. The textural characteristics of the fresh and spent catalysts were determined using the ICP, BET, TPR, TPO, and SEM analyses. Based on the obtained results, the catalyst promoted by SrO had the highest catalytic activity. The results indicated that adding various alkaline-earth oxides into the catalyst support decreased the Ni crystalline size from 17.2 nm to 7.4–10.9 nm. Moreover, all promoted catalysts showed better catalytic performance and the promoted sample with 3 wt% SrO possessed higher stability than unpromoted catalyst during 20 h on stream.     

Environmental-friendly mortar produced with treated and untreated coal wastes as cement replacement materials

Clean Technologies and Environmental Policy - This study aims to examine the influence of untreated coal waste (UCW) and treated coal waste (TCW) as supplementary cementitious materials (SCMs) on...     

A simple,low cost,and template-free method for synthesis of boron nitride using different precursors

In this research, hexagonal boron nitride (h-BN) was synthesized using a simple, low cost, and template-free method with urea-boric acid (UB), melamine-boric acid (MB), and melamine-urea and boric acid (MUB) precursors, followed by the pyrolysis and heat treatment in a nitrogen atmosphere at 1050 °C. Samples were characterized by X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), X-ray photoelectron spectroscopy (XPS), Raman Spectroscopy, Fourier transform IR (FT-IR), and Brunauer–Emmett–Teller (BET) techniques. The specific surface areas obtained for h-BN synthesized by UB, MB, and MUB precursors were 87.43, 573.07, and 1005.7 m²/g, respectively. The average diameters of the pores using the Barrett, Joyner, and Halenda (BJH) model were 37.78, 3.68, and 2.13 nm, respectively. A thermogravimetric analysis showed a wider range of decomposition temperatures after using three precursors for synthesizing h-BN. Crumpled, whisker, and flower-like morphologies for UB, MB, and MUB precursors were respectively found using FESEM investigations. The formation of h-BN within the MUB sample was confirmed using the XPS analysis with measured peaks of 398.5 and 190.6 eV belonging to N 1s and B 1s, respectively. Raman spectroscopy revealed a high-intensity peak in 1366 cm^?1 related to the E_2g mode for h-BN synthesized with MUB. Therefore, the results demonstrate that the employed method can increase the potential of using the h-BN porous powder with a high specific surface area as a lubricant, thermal insulation filler, anti-corrosion filler in paint coatings, adsorption of various gas and hydrocarbon molecules as well as its application in drug-delivery nanocarriers.     

Experimental and theoretical studies of methanol oxidation in the presence of Co-Pd @ polyaniline/N-doped reduced graphene oxide electrocatalyst

Journal of Applied Electrochemistry - Nanocomposites of polyaniline (PANI) with nitrogen-doped reduced graphene oxide (NRGO) were synthesized through a chemical polymerization method. The...     

PEGylated hollow pH‐responsive polymeric nanocapsules for controlled drug delivery

Novel pH‐responsive PEGylated hollow nanocapsules (HNCaps) were fabricated through a combination of distillation–precipitation copolymerization and surface thiol–ene ‘click’ grafting reaction. For this purpose, SiO₂ nanoparticles were synthesized using the Stöber approach, and then modified using 3‐(trimethoxysilyl)propyl methacrylate (MPS). Afterward, a mixture of triethyleneglycol dimethacrylate (as crosslinker), acrylic acid (AA; as pH‐responsive monomer) and MPS‐modified SiO₂ nanoparticles (as sacrificial template) was copolymerized using the distillation–precipitation approach to afford SiO₂@PAA core–shell nanoparticles. The SiO₂ core was etched from SiO₂@PAA using HF solution, and the obtained PAA HNCaps were grafted with a thiol‐end‐capped poly(ethylene glycol) (PEG) through a thiol–ene ‘click’ reaction to produce PAA‐g‐PEG HNCaps. The fabricated HNCaps were loaded with doxorubicin hydrochloride (DOX) as a model anticancer drug, and their drug loading and encapsulation efficiencies as well as pH‐dependent drug release behavior were investigated. The anticancer activity of the drug‐loaded HNCaps was extensively evaluated using MTT assay against human breast cancer cells (MCF7). The cytotoxicity assay results as well as superior physicochemical and biological features of the fabricated HNCaps mean that the developed DOX‐loaded HNCaps have excellent potential for cancer chemotherapy. © 2020 Society of Chemical Industry     

Technologies to recover exhaust heat from internal combustion engines

The focus of this study is to review the latest developments and technologies on waste heat recovery of exhaust gas from internal combustion engines (ICE). These include thermoelectric generators (TEG), organic Rankine cycle (ORC), six-stroke cycle IC engine and new developments on turbocharger technology. Furthermore, the study looked into the potential energy savings and performances of those technologies. The current worldwide trend of increasing energy demand in transportation sector are one of the many segments that is responsible for the growing share of fossil fuel usage and indirectly contribute to the release of harmful greenhouse gas (GHG) emissions. It is hoped that with the latest findings on exhaust heat recovery to increase the efficiency of ICEs, world energy demand on the depleting fossil fuel reserves would be reduced and hence the impact of global warming due to the GHG emissions would fade away.     

Structural investigation and simulation of acoustic properties of some tellurite glasses using artificial intelligence technique

The developments in the field of industry raise the need for simulating the acoustic properties of glass materials before melting raw material oxides. In this paper, we are trying to simulate the acoustic properties of some tellurite glasses using one of the artificial intelligence techniques (artificial neural network). The artificial neural network (ANN) technique is introduced in the current study to simulate and predict important parameters such as density, longitudinal and shear ultrasonic velocities and elastic moduli (longitudinal and shear moduli). The ANN results were found to be in successful good agreement with those experimentally measured parameters. Then the presented ANN model is used to predict the acoustic properties of some new tellurite glasses. For this purpose, four glass systems xNb₂O₅-(1 − x)TeO₂, 0.1PbO-xNb₂O₅-(0.9 − x)TeO₂, 0.2PbO-xNb₂O₅-(0.8 − x)TeO₂ and 0.05Bi₂O₃-xNb₂O₅-(0.95 − x)TeO₂ were prepared using melt quenching technique. The results of ultrasonic velocities and elastic moduli showed that the addition of Nb₂O₅ as a network modifier provides oxygen ions to change [TeO₄] tbps into [TeO₃] tps.     

A new method for grafting functional groups onto mesoporous silica: an electrochemical approach

A novel method for the modification of mesoporous silica, MCM-41, using an electrochemical approach has been developed, and the process was monitored by cyclic voltammetery and spectrometric methods. The method was applied to the modification of mesoporous silica with new functional groups which are not accessible by conventional methods. Malononitrile-functionalized MCM-41 mesoporous silica was characterized by low-angle X-ray diffraction, Fourier transform infrared spectroscopy, mass spectrometry, thermal analysis, elemental analysis, high resolution transmission electron microscopy, and surface area measurement (S _BET). In addition, the application of malononitrile-functionalized MCM-41 as a sorbent for gold ions was demonstrated.     

In quest of new document relations: evaluating co-opinion relations between co-citations and its impact on Information retrieval effectiveness

Document relational network has been effective in retrieving and evaluating papers. Despite their effectiveness, relational measures, including co-citation, are far from ideal and need improvements. The assumption underlying the co-citation relation is the content relevance and opinion relatedness of cited and citing papers. This may imply existence of some kind of co-opinionatedness between co-cited papers which may be effective in improving the measure. Therefore, the present study tries to test the existence of this phenomenon and its role in improving information retrieval. To do so, based on CITREC, a medical test collection was developed consisting of 30 queries (seed documents) and 4823 of their co-cited papers. Using NLP techniques, the co-citances of the queries and their co-cited papers were analyzed and their similarities were computed by 4 g similarity measure. Opinion scores were extracted from co-citances using SentiWordnet. Also, nDCG values were calculated and then compared in terms of the citation proximity index (CPI) and co-citedness measures before and after being normalized by the co-opinionatedness measure. The reliability of the test collection was measured by generalizability theory. The findings suggested that a majority of the co-citations exhibited a high level of co-opinionatedness in that they were mostly similar either in their opinion strengths or in their polarities. Although anti-polar co-citations were not trivial in their number, a significantly higher number of the co-citations were co-polar, with a majority being positive. The evaluation of the normalization of the CPI and co-citedness by the co-opinionatedness indicated a generally significant improvement in retrieval effectiveness. While anti-polar similarity reduced the effectiveness of the measure, the co-polar similarity proved to be effective in improving the co-citedness. Consequently, the co-opinionatedness can be presented as a new document relation and used as a normalization factor to improve retrieval performance and research evaluation.