Greener Alternatives to Selected Organic Oxidation Reactions

The study of green chemistry is dedicated to eliminating or reducing toxic waste. One route to accomplish this goal is to explore alternative reaction conditions and parameters resulting in the development of more benign synthetic routes and reagents. The primary focus of this research is to find optimal reaction conditions for the oxidation of a primary alcohol to an aldehyde. As a case study, the oxidation of benzyl alcohol to benzaldehyde, a common industrial process, was examined. Traditionally carried out using the Jones Reagent, commonly referred to as chromium (IV) oxide or chromium trioxide (CrO3) in sulphuric acid, a great deal of research went into utilizing less toxic reagents, such as MnO2 or KMnO4 supported on a clay base. This research has led to an improvement on these alternatives, using a lithium chloride (LiCl) catalyst in a montmorillonite K10 clay solid phase, together with the oxidizing agent hydrogen peroxide, as even greener alternatives to these traditional oxidizing agents. Experiments were carried out to determine the lifetime of this LiCl/clay system as compared to MnO2 and KMnO4, to investigate its ability to catalyze the oxidation of other aromatic alcohols (such as 4-methoxybenzyl alcohol and diphenylmethanol), and to further improve the system’s adherence to green chemistry principles. Green solvent alternatives were examined by replacing the toluene solvent with dimethylcarbonate (DMC), and reaction conditions were optimized to improve product yield. It was determined that the LiCl/H2O2 system was, in most cases, equally as effective at catalyzing the oxidation of benzyl alcohol to benzaldehyde. Although the catalyst and oxidizing agent eliminated the toxic waste generated from chromium reagents, it offered significant challenges in product isolation, because of an aqueous-organic phase separation.

Remoção de ibuprofeno de águas por oxidação catalítica

A ocorrência e destino de fármacos no ambiente aquático tem vindo a ser reconhecido como um problema emergente em química ambiental. Alguns compostos são resistentes à degradação nas estações de tratamento de águas residuais, ETARs, enquanto que outros, ainda que sofram degradação parcial, continuam a ser lançados nos meios aquáticos em quantidades apreciáveis. O Ibuprofeno, IB, um dos anti­ inflamatórios mais consumidos por todo o mundo, é um dos fármacos mais detectados no meio hídrico. Apesar dos sistemas de tratamento convencionais utilizados nas ETARs removerem até 90% do IB das águas residuais, é frequente o efluente descarregado conter ainda quantidades significativas deste poluente. A presença destes compostos no ambiente deve ser avaliada dado que possuem actividade biológica, mesmo a baixas concentrações. Os processos avançados de oxidação com peróxido de hidrogénio, na presença de catalisadores heterogéneos, permitem melhorar significativamente a remoção deste tipo de compostos em águas. Assim, foi objectivo deste trabalho o estudo da utilização de peróxido de hidrogénio como agente oxidante na remoção de IB em soluções aquosas, na presença de complexo de acetilacetonato de Ni (II) disperso em PDMS ou encapsulado em zeólitos NaY. Para o doseamento do fármaco em solução foi necessário desenvolver um método analítico consistindo de separação cromatográfica por HPLC e detecção e quantificação por UV-Vis. Não houve necessidade de recorrer a um passo de pré­ concentração de amostras por extracção em fase sólida (SPE) devido ao facto das concentrações de IB medidas ao longo do trabalho se terem sempre encontrado acima do LOQ (811 g L-1) do método analítico por injecção directa. Deste estudo pode concluir-se que o catalisador que apresentou melhor actividade catalítica e consequentemente maior remoção do IB em solução, foi o complexo de acetilacetonato de Ni (II), disperso em PDMS. Foi avaliada a influência, na conversão do IB, de diferentes parâmetros como a concentração inicial de peróxido de hidrogénio adicionada, quantidade de catalisador utilizada na mistura reaccional e temperatura. Os resultados permitiram concluir que os aumentos destes parâmetros conduzem a um aumento da actividade catalítica da reacção. A estabilidade catalítica do acetilacetonato de Ni (II)/PDMS, foi avaliada em ensaios consecutivos com a mesma amostra e nas mesmas condições, tendo-se observado que, após 8 utilizações, o catalisador perde ligeiramente a actividade (cerca de 11% do seu valor inicial). ABSTRACT: The presence and fate of pharmaceuticals in the aquatic environment is an emergent issue in environmental chemistry. Some compounds are poorly removed in wastewater treatment plants (WWTPs) while others, in spite of being partially removed, are still present in the WWTPs effluents and discharged in the receiving water bodies. Ibuprofen, IB, a non-steroid anti-inflammatory drug, is one of the most used and also one of the most frequently detected pharmaceutical contaminants in aquifers worldwide. Its removal by conventional wastewater treatment processes used in most WWTPs is usually high (up to 90% of incoming IB may be removed), but duet the high loads present in the influents, still significant amounts of IB usually leave the WWTPs in the treated effluents. The presence of these compounds in the environment must be evaluated considering that they may have some biological activity even at low concentrations. Advanced oxidation processes using hydrogen peroxide, in the presence of heterogeneous catalysts, provide a significantly improved removal of this type of substances from waters. Therefore, it was the aim of this work to study the use of hydrogen peroxide as an oxidizing agent in the removal of IB from aqueous solutions, in the presence of the catalyst nickel (II) acetylacetonate dispersed in PDMS or encapsulated in the NaY zeolite. For the quantification of the pharmaceutical in aqueous solution it was necessary to develop an analytical methodology based in chromatographic separation by HPLC and with UV-Vis detection and quantification. There was no need for a pre­concentration step of the samples by solid phase extraction (SPE) as the IB concentrations measured were always above the limit of quantification (811 bL1 of) the analytical method. The results from this study have shown that the catalyst which presented the best catalytic activity and the highest IB removal in solution was nickel (II) acetylacetonate dispersed in PDMS.

Lyprinol : is it a useful anti-inflammatory agent?

The New Zealand green lipped mussel preparation Lyprinol is available without a prescription from a supermarket, pharmacy or Web. The Food and Drug Administration have recently warned Lyprinol USA about their extravagant anti-inflammatory claims for Lyprinol appearing on the web. These claims are put to thorough review. Lyprinol does have anti-inflammatory mechanisms, and has anti-inflammatory effects in some animal models of inflammation. Lyprinol may have benefits in dogs with arthritis. There are design problems with the clinical trials of Lyprinol in humans as an anti-inflammatory agent in osteoarthritis and rheumatoid arthritis, making it difficult to give a definite answer to how effective Lyprinol is in these conditions, but any benefit is small. Lyprinol also has a small benefit in atopic allergy. As anti-inflammatory agents, there is little to choose between Lyprinol and fish oil. No adverse effects have been reported with Lyprinol. Thus, although it is difficult to conclude whether Lyprinol does much good, it can be concluded that Lyprinol probably does no major harm.

Load–frequency control : a GA-based multi-agent reinforcement learning

The load–frequency control (LFC) problem has been one of the major subjects in a power system. In practice, LFC systems use proportional–integral (PI) controllers. However since these controllers are designed using a linear model, the non-linearities of the system are not accounted for and they are incapable of gaining good dynamical performance for a wide range of operating conditions in a multi-area power system. A strategy for solving this problem because of the distributed nature of a multi-area power system is presented by using a multi-agent reinforcement learning (MARL) approach. It consists of two agents in each power area; the estimator agent provides the area control error (ACE) signal based on the frequency bias estimation and the controller agent uses reinforcement learning to control the power system in which genetic algorithm optimisation is used to tune its parameters. This method does not depend on any knowledge of the system and it admits considerable flexibility in defining the control objective. Also, by finding the ACE signal based on the frequency bias estimation the LFC performance is improved and by using the MARL parallel, computation is realised, leading to a high degree of scalability. Here, to illustrate the accuracy of the proposed approach, a three-area power system example is given with two scenarios.