Combinatorial Chemistry & High Throughput Screening - Volume 15, Issue 2, 2012

As populations increase and economic growth, industrialization, and modernization spread throughout the world, Green Chemistry is emerging as a subject of utmost importance. Some of its most significant and diverse applications include the development of chemical processes that are more energy efficient and environmentally sound, save valuable raw materials, control emissions, and produce less hazardous byproducts. World energy demand is rapidly growing and is expected to increase nearly 50% by 2035, driven mostly by growth in emerging markets such as China and India as well as Russia and Brazil. The world's population has more than doubled since 1950 and it is projected to increase another 40% by 2050. The industrial sector, which uses more energy globally than any other end-use sector, is currently consuming about 50% of the world's total delivered energy, and it is expected that this number will grow dramatically in the future. Worldwide, projected industrial energy consumption will grow from 184 quadrillion Btu in 2007 to 262 quadrillion Btu in 2035 (EIA). The daily consumption of crude oil could reach 105 million barrels per day in 2030. This ever growing energy demand has the potential to have a severe negative impact on global society if it is not addressed. As an example, the EIA forecasts energyrelated emissions of carbon dioxide will jump by 43%, from 29.7 billion tons in 2007 to 42.4 billion tons in 2035. Most industrial chemical processes operate at high temperatures and/or pressures. Therefore, their energy consumption is very high when compared, for example, to biological systems. To illustrate, the worldwide fertilizer demand from the Haber-Bosch process corresponded to 110 million tons of ammonia in 2002 and utilized approximately 1% of the global energy production in that year. Catalysts render chemical processes more selective and energy-efficient and are employed in the production of more than 90% of all chemical products. Hence catalysts add significant value to the productivity and efficiency of chemical processes. It is estimated that about 20 to 50% of the energy consumption by the chemical industry can be saved for current processes by the improvement of commercial catalysts as well as through the development of novel catalytic systems. This will be a critical contributor to reduce global energy demand to a minimum. Green catalysis comprises homogeneous, heterogeneous, and biological catalysis. In this Hot Topic issue we focus on heterogeneous chemical catalysis which is the most widely used and longest established catalyst type in the chemical industry. Simultaneously, we focus on high-throughput synthesis and screening methodologies for catalyst research and development, which have proven to be very useful to accelerate applications of new and optimized materials in chemical catalysis. They have also resulted in an increase in the probability of technical success due to the larger experimental space that can be scanned more rapidly and efficiently. The design of an integrated workflow consisting of synthesis, characterization, screening and data management is the key factor here. Diverse aspects of fundamental as well as applied high throughput techniques are covered in this issue including hardware/equipment, catalyst library synthesis and characterization, reaction screening, and data mining by neural networks. Articles from both academia and industry make this Hot Topic issue well balanced, with applications ranging from optimization of established industrial catalysts to the discovery of new materials and the development of innovative reactor concepts (advanced Temkin reactor, small scale parallel film reactor). Included are detailed contributions covering commodity chemicals produced by continuous flow gas phase reactions (phthalic anhydride, vinyl acetate monomer), and fine chemicals usually synthesized in liquid phase batch processes. The potential of novel catalytic materials (Ionic Liquids, Metal Organic Framework materials applied to CO2 adsorption, transition-metal-free epoxidation catalysts) are also presented. The analysis of multiparameter space is shown to represent a new way of probing reaction networks.....

Effects of different catalyst components on the catalytic performance in steam reforming of ethanol have been investigated by means of Artificial Neural Networks (ANNs) and Partial Least Square regression (PLSR). The data base consisted of ca. 400 items (catalysts with varied composition), which were obtained from a former catalyst optimization procedure. Marten's uncertainty (jackknife) test showed that simultaneous addition of Ni and Co has crucial effect on the hydrogen production. The catalyst containing both Ni and Co provided remarkable hydrogen production at 450°C. The addition of Ceas modifier to the bimetallic NiCo catalyst has high importance at lower temperatures: the hydrogen concentration is doubled at 350°C. Addition of Pt had only little effect on the product distribution. The outliers in the data set have been investigated by means of Hotelling T2 control chart. Compositions containing high amount of Cu or Ce have been identified as outliers, which points to the nonlinear effect of Cu and Ce on the catalytic performance. ANNs were used for analysis of the non-linear effects: an optimum was found with increasing amount of Cu and Ce in the catalyst composition. Hydrogen production can be improved by Ce only in the absence of Zn. Additionally, negative cross-effect was evidenced between Ni and Cu. The above relationships have been visualized in Holographic Maps, too. Although predictive ability of PLSR is somewhat worse than that of ANN, PLSR provided indirect evidence that ANNs were trained adequately.

The Temkin reactor concept was successfully extended to the high throughput operation mode and it could be considerably improved as compared to the original design with respect to an optimized gas flow pattern over the full size beads. This improved parallel reactor design was successfully used for the high throughput optimization of an innovative new class of physically coated VAM shell catalysts. Exploiting this novel, improved Temkin reactor concept allowed Sud-Chemie not only to optimize the multiparameter compositional space of noble metal and promoter loadings on the support spheres but for the first time to combine this “chemical optimization” with the high throughput improvement of catalytically decisive parameters as the active shell thickness, the metal distribution cross the shell, the pore diameters, and the pore volumes. This new class of physically impregnated VA catalysts, called VAM2ax, impress by its exceptionally high VA selectivity of above 94% at 50% oxygen conversion and the very high space time yields of > 1000 g VAM/l*h which easily can be reached over these shell catalysts with optimized mass and heat transport properties.

Renewable feedstocks have been in the spotlight of intensive research activities over the past 10 years. Glycerol is one of the feedstock molecules which has been the target of numerous research efforts, for a number of reasons. First of all glycerol is currently readily available due to the fact that it is a couple product of the first generation biodiesel production. Secondly glycerol can be taken as a representative model substrate to explore the options of selective conversion of sugar alcohols to products of value. In our paper we discuss potential routes for the valorisation of glycerol which lead to intermediates already established within the petrochemical value chain and illustrate what impact high throughput experimentation may have as a success factor on research and development for this field. As illustrative examples we have chosen the oxidative transformation of glycerol to acrolein and acrylic acid and the carbonylation of glycerol to C4-acids

The oxidation of o-xylene and/or naphthalene to phthalic anhydride is one of the important industrial processes based on catalytic selective oxidation reactions. Vanadia - titania catalysts have been used in the industrial phthalic anyhdride process for the last 50 years. The operation parameters like the temperature range of operation, reactor inlet pressures, contact times, o-xylene loadings, etc. were constantly improved during this period of continuous process optimization so as to optimize catalyst performance and increase its life time. However, a fundamental understanding of the mutual interaction of the rather complex reaction network and the catalyst formulation is still missing. Recently, a detailed study of by-product formation as function of process conditions allowed us to develop a novel, improved reaction scheme for the catalytic oxidation of o-xylene [1]. Based on this understanding, a detailed investigation was conducted for the first time of the by-product formation under varying operation conditions and as a function of the active mass variation exploiting high-throughput, as well as bench scales reactors. This high-throughput testing allowed us to relate reaction kinetics to novel catalyst formulations.

Transition-metal-free oxides were studied as heterogeneous catalysts for the sustainable epoxidation of alkenes with aqueous H2O2 by means of high throughput experimentation (HTE) techniques. A full-factorial HTE approach was applied in the various stages of the development of the catalysts: the synthesis of the materials, their screening as heterogeneous catalysts in liquid-phase epoxidation and the optimisation of the reaction conditions. Initially, the chemical composition of transition-metal-free oxides was screened, leading to the discovery of gallium oxide as a novel, active and selective epoxidation catalyst. On the basis of these results, the research line was continued with the study of structured porous aluminosilicates, gallosilicates and silica-gallia composites. In general, the gallium-based materials showed the best catalytic performances. This family of materials represents a promising class of heterogeneous catalysts for the sustainable epoxidation of alkenes and offers a valid alternative to the transition-metal heterogeneous catalysts commonly used in epoxidation. High throughput experimentation played an important role in promoting the development of these catalytic systems.

Combinatorial screening using precipitation methods at room temperature can lead to a great diversity of carboxylate based Metal Organic Frameworks (MOFs) including already known or original porous solids. The investigation of the synthesis of MOFs in different solvent and solvent mixtures includes the use of solvents such as alcohols and tetrahydrofuran (THF) which would greatly facilitate large scale production. We also show the application of Principal Component Analysis (PCA) and clustering techniques on large libraries of XRD diffraction files in order to identify classes of similar phases and peculiar phases. The combinatorial screening of 105 samples in the La/btc system has led to the identification of two phases which are solvent depending. On the La(btc) compound, the CO2 adsorption measurements reveal a guest-host interactions as supported by XRD phase transformation upon thermal treatment. The mass transport can be assigned to a “single file diffusion” regime due to the one dimensional channel porous structure associated to small pore size.

Technically relevant partial oxidation reactions represent complex reaction networks. Establishing a kinetic model for a system of multiple consecutive and parallel reaction steps is a challenging goal. The synthesis of acrylic acid by oxidation of propane using MoVTeNb mixed oxide as catalyst is such a reaction network. In an on-going study, a 10- fold parallel reactor set-up is used to vary systematically reaction conditions in a broad range over a single, well-defined MoVTeNb oxide. Selectivity and product yield in a multidimensional parameter space can give insight into the reaction network. Apparent activation energies and reaction orders of propane are derived for several conditions. Optimum reaction conditions within the investigated parameter space are specified. The results presented within this contribution contain about 200 data points measured in steady states each corresponding to reaction conditions that differ in temperature, contact time, and propane feed concentration. The fact that this data was collected in less than two months shows clearly the advantage of parallel screening of reaction conditions for mechanistic studies.

Supported Ionic Liquid Phase (SILP) catalysts have been prepared by effective immobilization of [Cu(TMEDA)(OH)]Cl in a nano-metric film of an ionic liquid on various oxidic support materials. The catalysts were tested for the oxidative homocoupling of 1-alkynes to the corresponding diynes in in a combined high throughput and conventional batch reaction approach. Among the screened support materials silica based materials performed best. The results indicate that for the specific reaction the thickness of the ionic liquids layer and therefore the mobility of the homogeneous copper complex within the ionic liquid layer as deduced from solid state nmr measurements have major impact on the catalytic performance. The optimized catalysts could be recycled up to four times without any loss of activity.

High Throughput experimentation has been well established as a tool in early stage catalyst development and catalyst and process scale-up today. One of the more challenging areas of catalytic research is polymer catalysis. The main difference with most non-polymer catalytic conversions is the fact that the product is not a well defined molecule and the catalytic performance cannot be easily expressed only in terms of catalyst activity and selectivity. In polymerization reactions, polymer chains are formed that can have various lengths (resulting in a molecular weight distribution rather than a defined molecular weight), that can have different compositions (when random or block co-polymers are produced), that can have cross-linking (often significantly affecting physical properties), that can have different endgroups (often affecting subsequent processing steps) and several other variations. In addition, for polyolefins, mass and heat transfer, oxygen and moisture sensitivity, stereoregularity and many other intrinsic features make relevant high throughput screening in this field an incredible challenge. For polycondensation reactions performed in the melt often the viscosity becomes already high at modest molecular weights, which greatly influences mass transfer of the condensation product (often water or methanol). When reactions become mass transfer limited, catalyst performance comparison is often no longer relevant. This however does not mean that relevant experiments for these application areas cannot be performed on small scale. Relevant catalyst screening experiments for polycondensation reactions can be performed in very efficient small scale parallel equipment. Both transesterification and polycondensation as well as post condensation through solid-stating in parallel equipment have been developed. Next to polymer synthesis, polymer characterization also needs to be accelerated without making concessions to quality in order to draw relevant conclusions.

Successful implementation of High throughput Experimentation (EE) tools has resulted in their increased acceptance as essential tools in chemical, petrochemical and polymer R&D laboratories. This article provides a number of concrete examples of EE systems, which have been designed and successfully implemented in studies, which focus on deriving reaction kinetic data. The implementation of high throughput EE tools for performing kinetic studies of both catalytic and non-catalytic systems results in a significantly faster acquisition of high-quality kinetic modeling data, required to quantitatively predict the behavior of complex, multistep reactions.

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