Liquid coordination complexes: a new class of Lewis acids as safer alternatives to BF3 in synthesis of polyalphaolefins

Liquid coordination complexes (LCCs) are a new class of liquid Lewis acids, prepared by combining an excess of a metal halide (e.g. GaCl3) with a basic donor molecule (e.g. amides, amines or phosphines). LCCs were used to catalyse oligomerisation of 1-decene to polyalphaolefins (PAOs). Molecular weight distribution and physical properties of the produced oils were compliant with those required for low viscosity synthetic (Group IV) lubricant base oils. Kinematic viscosities at 100 °C of ca. 4 or 6 cSt were obtained, along with viscosity indexes above 120 and pour points below −57 °C. In industry, to achieve similar properties, BF3 gas is used as a catalyst. LCCs are proposed as a safer and economically attractive alternative to BF3 gas for the production of polyalphaolefins.

Artificial Neural Network for Compositional Ionic Liquid Viscosity Prediction

Being a new generation of green solvents and high-tech reaction media of the future, ionic liquids have increasingly attracted much attention. Of particular interest in this context are room temperature ionic liquids (in short as ILs in this paper). Due to the relatively high viscosity, ILs is expected to be used in the form of solvent diluted mixture with reduced viscosity in industrial application, where predicting the viscosity of IL mixture has been an important research issue. Different IL mixture and many modelling approaches have been investigated. The objective of this study is to provide an alternative model approach using soft computing technique, i.e., artificial neural network (ANN) model, to predict the compositional viscosity of binary mixtures of ILs [C _n-mim][NTf ₂] with n=4, 6, 8, 10 in methanol and ethanol over the entire range of molar fraction at a broad range of temperatures from T=293.0-328.0K. The results show that the proposed ANN model provides alternative way to predict compositional viscosity successfully with highly improved accuracy and also show its potential to be extensively utilized to predict compositional viscosity taking account of IL alkyl chain length, as well as temperature and compositions simultaneously, i.e., more complex intermolecular interactions between components in which it would be hard or impossible to establish the analytical model. This illustrates the potential application of ANN in the case that the physical and thermodynamic properties are highly non-linear or too complex. © 2012 Copyright the authors.

Techno-Economic and Life Cycle Assessment on Lignocellulosic Biomass Thermochemical Conversion Technologies: A Review

Bioenergy derived from biomass provides a promising energy alternative and can reduce the greenhouse gas (GHG) emissions generated from fossil fuels. Biomass-based thermochemical conversion technologies have been acknowledged as apt options to convert bioresources into bioenergy; this bioenergy includes electricity, heat, and fuels/chemicals in solid, liquid, and gaseous phases. In this review, the techno-economic and life cycle assessment of these technologies (combustion, gasification, pyrolysis, liquefaction, carbonization, and co-firing) are summarized. Specific indicators (production costs in a techno-economic analysis, functional units and environmental impacts in a life cycle analysis) for different technologies were compared. Finally, gaps in research and future trends in biomass thermochemical conversion were identified. This review could be used to guide future research related to economic and environmental benefits of bioenergy.