Designing heterogeneous catalysts for biodiesel synthesis

Concerns over dwindling oil reserves, carbon dioxide emissions from fossil fuel sources and associated climate change is driving the urgent need for clean, renewable energy supplies. The conversion of triglycerides to biodiesel via catalytic transesterification remains an energetically efficient and attractive means to generate transportation fuel1. However, current biodiesel manufacturing routes employing soluble alkali based catalysts are very energy inefficient producing copious amounts of contaminated water waste during fuel purification. Technical advances in catalyst and reactor design and introduction of non-food based feedstocks are thus required to ensure that biodiesel remains a key player in the renewable energy sector for the 21st century. This presentation will give an overview of some recent developments in the design of solid acid and base catalysts for biodiesel synthesis. A particular focus will be on the benefits of designing materials with interconnected hierarchical macro-mesoporous networks to enhance mass-transport of viscous plant oils during reaction.

Heterogeneous catalysts for biodiesel production

The combination of dwindling oil reserves and growing concerns over carbon dioxide emissions and associated climate change is driving the urgent development of clean, sustainable energy supplies. Biodiesel is non-toxic and biodegradable, with the potential for closed CO2 cycles and thus vastly reduced carbon footprints compared with petroleum fuels. However, current manufacturing routes employing soluble catalysts are very energy inefficient and produce copious amounts of contaminated water waste. This review highlights the significant progress made in recent years towards developing solid acid and base catalysts for biodiesel synthesis. Issues to be addressed in the future are also discussed including the introduction of non-edible oil feedstocks, as well as technical advances in catalyst and reactor design to ensure that biodiesel remains a key player in the renewable energy sector for the 21st century.

In situ aberration corrected-transmission electron microscopy of magnesium oxide nanocatalysts for biodiesels

Biofuels are promising renewable energy sources and can be derived from vegetable oil feedstocks. Although solid catalysts show great promise in plant oil triglyceride transesterification to biodiesel, the identification of active sites and operating surface nanostructures created during their processing is essential for the development of efficient heterogeneous catalysts. Systematic, direct observations of dynamic MgO nanocatalysts from a magnesium hydroxide-methoxide precursor were performed under controlled calcination conditions using novel in situ aberration corrected-transmission electron microscopy at the 0.1 nm level and quantified with catalytic reactivity and physico-chemical studies. Surface structural modifications and the evolution of extended atomic scale glide defects implicate coplanar anion vacancies in active sites in the transesterification of triglycerides to biodiesel. The linear correlation between surface defect density (and therefore polarisability) and activity affords a simple means to fine tune new, energy efficient nanocatalysts for biofuel synthesis. © 2009 Springer Science+Business Media, LLC.

A polyoxometallate-tethered Ru complex as a catalyst in solventless phenyl acetylene oligomerisation

A novel compound comprising a Ru–tethered polyoxometallate Keggin anion of formula [HNEt3]+[(Ru{η5-C5H5}{PPh3}2)2(PW12O40)]− has been synthesised that shows high activity and selectivity in alkyne oligomerisation. In situ IR binding studies using CO confirmed the accessibility of the Ru centre for catalysis. Phenyl acetylene was successfully dimerised under a heterogeneous catalytic regime. Selectivity towards the (E)-enyne, not found in the homogeneous Ru(η5-C5H5)(PPh3)2Cl analogue, was achieved while retaining high a turnover frequency of 225 h−1.

Simulation process of biodiesel production over heterogeneous catalysts

Biodiesel production is a very promising area due to the relevance that it is an environmental-friendly diesel fuel alternative to fossil fuel derived diesel fuels. Nowadays, most industrial applications of biodiesel production are performed by the transesterification of renewable biological sources based on homogeneous acid catalysts, which requires downstream neutralization and separation leading to a series of technical and environmental problems. However, heterogeneous catalyst can solve these issues, and be used as a better alternative for biodiesel production. Thus, a heuristic diffusion-reaction kinetic model has been established to simulate the transesterification of alkyl ester with methanol over a series of heterogeneous Cs-doped heteropolyacid catalysts. The novelty of this framework lies in detailed modeling of surface reacting kinetic phenomena and integrating that with particle-level transport phenomena all the way through to process design and optimisation, which has been done for biodiesel production process for the first time. This multi-disciplinary research combining chemistry, chemical engineering and process integration offers better insights into catalyst design and process intensification for the industrial application of Cs-doped heteropolyacid catalysts for biodiesel production. A case study of the transesterification of tributyrin with methanol has been demonstrated to establish the effectiveness of this methodology.

Simulation process of biodiesel production over heterogeneous catalysts

Biodiesel production is a very promising area due to the relevance that it is an environmental-friendly diesel fuel alternative to fossil fuel derived diesel fuels. Nowadays, most industrial applications of biodiesel production are performed by the transesterification of renewable biological sources based on homogeneous acid catalysts, which requires downstream neutralization and separation leading to a series of technical and environmental problems. However, heterogeneous catalyst can solve these issues, and be used as a better alternative for biodiesel production. Thus, a heuristic diffusion-reaction kinetic model has been established to simulate the transesterification of alkyl ester with methanol over a series of heterogeneous Cs-doped heteropolyacid catalysts. The novelty of this framework lies in detailed modeling of surface reacting kinetic phenomena and integrating that with particle-level transport phenomena all the way through to process design and optimisation, which has been done for biodiesel production process for the first time. This multi-disciplinary research combining chemistry, chemical engineering and process integration offers better insights into catalyst design and process intensification for the industrial application of Cs-doped heteropolyacid catalysts for biodiesel production. A case study of the transesterification of tributyrin with methanol has been demonstrated to establish the effectiveness of this methodology.

R. A. Sheldon, I. Arends and U. Hanefeld. Green chemistry and catalysis. Wiley-VCH, 2007, 448 pp; ISBN 978-3-527-30715-9 (Hardcover)

Book review

On the active site in heterogeneous palladium selox catalysts

The nature of the active site in the Pd-catalysed aerobic selective oxidation of cinnamyl and crotyl alcohols has been directly probed by bulk and surface X-ray techniques. The importance of high metal dispersions and the crucial role of surface palladium oxide have been identified. © The Royal Society of Chemistry 2006.

Asymmetric epoxidation of alkenes by a chiral manganese(III) salen complex anchored onto a functionalised hexagonal mesoporous silica

A Jacobsen-type catalyst was anchored onto an amine functionalised hexagonal mesoporous silica (HMS) through the diimine bridge fragment of the complex. The new heterogeneous catalyst, as well as the precedent materials, were characterised by elemental analyses, FTIR-DRIFT, UV-vis, porosimetry and XPS which showed that the complex was successfully anchored. This material was active in the epoxidation of styrene and α-methylstyrene in dichloromethane at 0°C using, respectively, m-CPBA/NMO and NaOCl. With the former substrate no asymmetric induction was found in the epoxide, whereas with the latter substrate higher %ee was found than in homogeneous phase. Using the latter experimental conditions, catalyst reuse led to no significant loss of catalytic activity and enantioselectivity. © 2005 Elsevier B.V. All rights reserved.

Visualisation of heterogeneous data with the generalised generative topographic mapping

Heterogeneous and incomplete datasets are common in many real-world visualisation applications. The probabilistic nature of the Generative Topographic Mapping (GTM), which was originally developed for complete continuous data, can be extended to model heterogeneous (i.e. containing both continuous and discrete values) and missing data. This paper describes and assesses the resulting model on both synthetic and real-world heterogeneous data with missing values.

Improving scheduling techniques in heterogeneous systems with dynamic, on-line optimisations

Computational performance increasingly depends on parallelism, and many systems rely on heterogeneous resources such as GPUs and FPGAs to accelerate computationally intensive applications. However, implementations for such heterogeneous systems are often hand-crafted and optimised to one computation scenario, and it can be challenging to maintain high performance when application parameters change. In this paper, we demonstrate that machine learning can help to dynamically choose parameters for task scheduling and load-balancing based on changing characteristics of the incoming workload. We use a financial option pricing application as a case study. We propose a simulation of processing financial tasks on a heterogeneous system with GPUs and FPGAs, and show how dynamic, on-line optimisations could improve such a system. We compare on-line and batch processing algorithms, and we also consider cases with no dynamic optimisations.

Evolutionary market agents and heterogeneous service providers:achieving desired resource allocations

In future massively distributed service-based computational systems, resources will span many locations, organisations and platforms. In such systems, the ability to allocate resources in a desired configuration, in a scalable and robust manner, will be essential.We build upon a previous evolutionary market-based approach to achieving resource allocation in decentralised systems, by considering heterogeneous providers. In such scenarios, providers may be said to value their resources differently. We demonstrate how, given such valuations, the outcome allocation may be predicted. Furthermore, we describe how the approach may be used to achieve a stable, uneven load-balance of our choosing. We analyse the system's expected behaviour, and validate our predictions in simulation. Our approach is fully decentralised; no part of the system is weaker than any other. No cooperation between nodes is assumed; only self-interest is relied upon. A particular desired allocation is achieved transparently to users, as no modification to the buyers is required.

Application of the Heterogeneous System Prediction Method to Pattern Recognition Problem

* This work was financially supported by RFBR-04-01-00858.

Extreme Situations Prediction by MultidimenSional Heterogeneous Time Series Using Logical Decision Functions

* The work is supported by RFBR, grant 04-01-00858-a

Multidimensional Heterogeneous Variable Prediction Based on Experts’ Statements

* The work was supported by the RFBR under Grant N07-01-00331a.