Multi-walled carbon nanotube supported aminomethylphosphine-Ru(II) complexes: Optical behavior and catalytic properties in transfer hydrogenation of acetophenone derivatives

The novel multi-walled carbon nanotube (MWCNT) supported bis(diphenylphosphinomethyl)amine [MWCNT@CHO-NHArN(CH₂PPh₂)₂ type] ligands and their Ru(II) complexes have been synthesized and characterized with Fourier Transform Infrared Spectrometry (FT-IR), Scanning Electron Microscopy (SEM), Energy Dispersive X-Ray (EDX), Transmission Electron Microscopy (TEM), Ultraviolet-Visible Spectrometry, X-Ray Diffraction Spectrometry (XRD), and Thermal analysis (TG/DTA) techniques. In addition, MWCNT@CHO-NHArN(CH₂PPh₂)₂Ru(p-cymene)Cl₂ type complexes were tried as catalysts in the catalytic transfer hydrogenation reactions of acetophenone derivatives. The crystallite size and lattice strain of the MWCNT-based compounds were calculated by the Scherrer's equation. The optical parameters of the MWCNT-based structures were analyzed and the band gap enhanced from 4.42 eV to 4.98 eV. It was confirmed that the reduction of bromo and chloro acetophenone derivatives using all the catalysts, the conversions were high. The results showed that MWCNT-supported Ru(II) complexes were efficient catalysts in the reduction of bromo and chloro acetophenone derivatives with 99% efficiency in K₂CO₃ media at 80 ^°C.     

Bayesian Belief Network Used in the Chemical and Process Industry: A Review and Application

With the increasing growth of the chemical and process industries, it is necessary to ensure the safe operation of their complex and often hazardous installations, given their proximity to residential areas. Several techniques, such as fault tree analysis (FTA), bow-tie analysis (BTA), and Bayesian belief networks (BBNs), have been developed for adequate probabilistic risk assessment and management. The current work is aimed at performing a brief statistical review of the use of Bayesian networks in the chemical and process industry within the last decade. The review reveals that Bayesian networks have been used extensively in various forms of safety and risk assessment. This trend is attributable to the complexity of the installations found in this industry and the ability of BBN to intuitively represent these complexities, handle uncertainties, and update event probabilities. The paper is concluded with an illustrative example of the use of BBN to investigate the effectiveness of the safety barriers of a gas facility.

     

Adsorption kinetics and surface modeling of aqueous methylene blue onto activated carbonaceous wood sawdust

In this work, Sawdust was used to develop a new low-cost adsorbent and study its application to remove methylene blue dye from aqueous solution. Sawdust was calcined under air atmosphere at three different temperatures (300°C, 400°C, and 500°C) using phosphoric acid (H₃PO₄) as an activating agent. The structure, morphology, surface functions and the chemical composition of adsorbent were characterized by Fourier Transform Infrared spectra (FTIR), X-ray fluorescence (XRF), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), specific surface area (BET) and Boehm method. Different operational parameters such as pH, adsorbent loading, contact time and were investigated to evaluate experimental data. The adsorption of MB on SD-300, SD-400, and SD-500 show that the pseudo-second-order and Langmuir models fitted better the experimental results of MB adsorption onto all adsorbents. The maximum capacities based on the Langmuir model were 416.7 mg.g^?1 for SD-300, 526.3 mg.g^?1 for SD-400, and 819.7 mg.g^?1 for SD-500. The positive values of ΔG, ΔH, and ΔS implied that the adsorption process was non-spontaneous and endothermic nature. Finally, Regeneration of the SD-500 was investigated and optimization was performed using CCD combined with RSM.     

Recent Techniques for Harvesting Energy from the Human Body

The human body contains a near-infinite supply of energy in chemical, thermal, and mechanical forms. However, the majority of implantable and wearable devices are still operated by batteries, whose insufficient capacity and large size limit their lifespan and increase the risk of hazardous material leakage. Such energy can be used to exceed the battery power limits of implantable and wearable devices. Moreover, novel materials and fabrication methods can be used to create various medical therapies and life-enhancing technologies. This review paper focuses on energy-harvesting technologies used in medical and health applications, primarily power collectors from the human body. Current approaches to energy harvesting from the bodies of living subjects for self-powered electronics are summarized. Using the human body as an energy source encompasses numerous topics: thermoelectric generators, power harvesting by kinetic energy, cardiovascular energy harvesting, and blood pressure. The review considers various perspectives on future research, which can provide a new forum for advancing new technologies for the diagnosis, treatment, and prevention of diseases by integrating different energy harvesters with advanced electronics.     

A New variant of the McEliece cryptosystem based on the Smith form of convolutional codes

In this article, the authors propose a new version of the McEliece cryptosystem based on the Smith form of convolutional codes. They use the Smith form to hide a part of the code in the public matrix, and they leave the other part secret. The secret part will then be used for decryption. They hide this part by multiplying it on the left by a random matrix, and they add a random matrix which has a few conditions. Their scheme has a small public key size compared to the original McEliece scheme and resists the unique decoding attack against convolutional structure presented at the conference PQCrypto 2013 by Landais and Tillich. Further, the exhaustive search attack is infeasible on their system.     

Pincer Type Ditertiary Aminomethylphosphine–Pd(II) Complexes Supported on Multi-Walled Carbon Nanotube: Catalytic Properties in Heck C–C Coupling Reactions

Pincer type aminomethylphosphine–Pd(II) complexes supported on multi-walled carbon nanotube (MWCNT) have been synthesized and characterized using X-Ray diffraction spectrometry, scanning electron microscopy, thermal analysis, energy dispersive X-Ray, Fourier transform infrared spectrometry, transmission electron microscopy (TEM) and ultraviolet–visible spectrometry techniques. The novel complexes were tried as catalysts in Heck C–C coupling reactions. The crystallite size and lattice strain of the MWCNT based compounds were calculated by the Scherrer’s equation. The optical parameters of the MWCNT based structures were analyzed and the band gap enhanced from 4.42 to 4.98 eV. Different solvents (toluene, 1,4-diooxane, DMF and NMP) and bases (Et₃N, Na₂CO₃, NaOAc and K₂CO₃) were tried at different temperatures (80, 100 and 110 °C) in the cross-coupling of bromobenzene with styrene. The optimum yield was found in the presence of K₂CO₃, 110 °C in 1,4-dioxane solvent system.     

INTRODUCTION OF DYNAMICS TO AN APPROACH FOR BATCH PROCESS MONITORING USING INDEPENDENT COMPONENT ANALYSIS

Use of independent component analysis (ICA) in developing statistical monitoring charts for batch processes has been reported previously. This article extends the previous work by introducing time lag shifts to include process dynamics in the ICA model. Comparison of the dynamic ICA-based method with other batch process monitoring approaches based on static ICA, static principal component analysis (PCA), and dynamic PCA is made for an industrial batch polymerization reactor and a simulated fed-batch penicillin fermentation process. For both case studies, it was found that the dynamic ICA approach detected faults earlier than other approaches, with less ambiguity, and was the only approach that detected all the faults.     

Enhanced catalytic activity of monodispersed AgPd alloy nanoparticles assembled on mesoporous graphitic carbon nitride for the hydrolytic dehydrogenation of ammonia borane under sunlight

We address the composition-controlled synthesis of monodispersed AgPd alloy nanoparticles (NPs),their assembly for the first time on mesoporous graphitic carbon nitride (mpg-C3N4),and the unprecedented catalysis of mpg-C3N4@AgPd in the hydrolytic dehydrogenation of ammonia borane (AB) at room temperature.Monodispersed AgPd alloy NPs were synthesized using a high-temperature organic-phase surfactant-assisted protocol comprising the co-reduction of silver(Ⅰ) acetate and palladium(Ⅱ) acetylacetonate in the presence of oleylamine,oleic acid,and 1-octadecene.This protocol allowed the synthesis of four different compositions of AgPd alloy NPs.The AgPd alloy NPs were then assembled on mpg-C3N4,reduced graphene oxide,and Ketjenblack using a liquid-phase self-assembly method.Among the three supports tested,the mpg-C3N4@AgPd catalysts provided the best activity because of the Mott-Schottky effect,which was driven by the favorable work function difference between mpg-C3N4 and the metal NPs.Moreover,the activity of the mpg-C3N4@AgPd catalyst was further enhanced by an acetic acid treatment (AAt),and a record initial turnover frequency of 94.1 mol(hydrogen)·mol(catalyst)-1·min-1 was obtained.Furthermore,the mpg-C3N4@Ag42Pd58-AAt catalyst also showed moderate durability for the hydrolysis of AB.This study also includes a wealth of kinetic data for the mpg-C3N4@AgPd-catalyzed hydrolysis of AB.     

Economic incentives to use fertilizer on maize under differing agro-ecological conditions in Burkina Faso

Increasing agricultural productivity while protecting natural resources depends on proper understanding of farmers’ incentives to use intensification strategies, including fertilizer. Using a large-scale household dataset collected in rural Burkina Faso, we examined how the response of maize yield to fertilizer, and thus the economic incentives for its use, varied according to agro-ecological conditions. We employed a Control Function Approach with Correlated Random Effects in order to test and control for endogeneity of fertilizer use, measuring agro-ecological conditions at several scales. We investigated the profitability of fertilizer use with value-cost ratios. We found that productivity and marginal effects of fertilizer differ significantly according to agro-ecological conditions. Micro-variation appeared to be more critical than the definition of agro-ecological zone. Burkinabe soils are severely degraded and would benefit from greater application of fertilizer. However, at full market prices, fertilizer use was unprofitable. Though it was profitable with subsidized prices, transaction costs diminish the benefits of the subsidy. Profitability of fertilizer use with maize varied across agro-ecological conditions, even for field plots located in the same agro-ecological zone. Our results confirm that policy makers need to be cautious when generalizing across regions or drawing policy recommendations from a single agro-ecological zone because crop responses and economic incentives vary widely.