Dow Chemical (Netherlands)

Lower olefins are key building blocks for the manufacture of plastics, cosmetics, and drugs. Traditionally, olefins with two to four carbons are produced by steam cracking of crude oil-derived naphtha, but there is a pressing need for alternative feedstocks and processes in view of supply limitations and of environmental issues. Although the Fischer-Tropsch synthesis has long offered a means to convert coal, biomass, and natural gas into hydrocarbon derivatives through the intermediacy of synthesis gas (a mixture of molecular hydrogen and carbon monoxide), selectivity toward lower olefins tends to be low. We report on the conversion of synthesis gas to C(2) through C(4) olefins with selectivity up to 60 weight percent, using catalysts that constitute iron nanoparticles (promoted by sulfur plus sodium) homogeneously dispersed on weakly interactive α-alumina or carbon nanofiber supports.

Iron copper zeolite (Fe-Cu-ZSM-5) with aqueous hydrogen peroxide is active for the selective oxidation of methane to methanol. Iron is involved in the activation of the carbon–hydrogen bond, while copper allows methanol to form as the major product. The catalyst is stable, re-usable and activates methane giving >90 % methanol selectivity and 10 % conversion in a closed catalytic cycle (see scheme).

The Fischer-Tropsch synthesis of lower olefins (FTO) is an alternative process for the production of key chemical building blocks from non-petroleum-based sources such as natural gas, coal, or biomass. The influence of the iron carbide particle size of promoted and unpromoted carbon nanofiber supported catalysts on the conversion of synthesis gas has been investigated at 340-350 °C, H(2)/CO = 1, and pressures of 1 and 20 bar. The surface-specific activity (apparent TOF) based on the initial activity of unpromoted catalysts at 1 bar increased 6-8-fold when the average iron carbide size decreased from 7 to 2 nm, while methane and lower olefins selectivity were not affected. The same decrease in particle size for catalysts promoted by Na plus S resulted at 20 bar in a 2-fold increase of the apparent TOF based on initial activity which was mainly caused by a higher yield of methane for the smallest particles. Presumably, methane formation takes place at highly active low coordination sites residing at corners and edges, which are more abundant on small iron carbide particles. Lower olefins are produced at promoted (stepped) terrace sites that are available and active, quite independent of size. These results demonstrate that the iron carbide particle size plays a crucial role in the design of active and selective FTO catalysts.

Depletion of crude oil resources and environmental concerns have driven a worldwide research on alternative processes for the production of commodity chemicals. Fischer-Tropsch synthesis is a process for flexible production of key chemicals from synthesis gas originating from non-petroleum-based sources. Although the use of iron-based catalysts would be preferred over the widely used cobalt, manufacturing methods that prevent their fast deactivation because of sintering, carbon deposition and phase changes have proven challenging. Here we present a strategy to produce highly dispersed iron carbides embedded in a matrix of porous carbon. Very high iron loadings (>40 wt %) are achieved while maintaining an optimal dispersion of the active iron carbide phase when a metal organic framework is used as catalyst precursor. The unique iron spatial confinement and the absence of large iron particles in the obtained solids minimize catalyst deactivation, resulting in high active and stable operation.

This paper presents a novel approach to generate data-driven regression models that not only give reliable prediction of the observed data but also have smoother response surfaces and extra generalization capabilities with respect to extrapolation. These models are obtained as solutions of a genetic programming (GP) process, where selection is guided by a tradeoff between two competing objectives - numerical accuracy and the order of nonlinearity. The latter is a novel complexity measure that adopts the notion of the minimal degree of the best-fit polynomial, approximating an analytical function with a certain precision. Using nine regression problems, this paper presents and illustrates two different strategies for the use of the order of nonlinearity in symbolic regression via GP. The combination of optimization of the order of nonlinearity together with the numerical accuracy strongly outperforms ldquoconventionalrdquo optimization of a size-related expressional complexity and the accuracy with respect to extrapolative capabilities of solutions on all nine test problems. In addition to exploiting the new complexity measure, this paper also introduces a novel heuristic of alternating several optimization objectives in a 2-D optimization framework. Alternating the objectives at each generation in such a way allows us to exploit the effectiveness of 2-D optimization when more than two objectives are of interest (in this paper, these are accuracy, expressional complexity, and the order of nonlinearity). Results of the experiments on all test problems suggest that alternating the order of nonlinearity of GP individuals with their structural complexity produces solutions that are both compact and have smoother response surfaces, and, hence, contributes to better interpretability and understanding.

Kernels are used in support vector machines to map the learning data (nonlinearly) into a higher dimensional feature space where the computational power of the linear learning machine is increased. Every kernel has its advantages and disadvantages. A desirable characteristic for learning may not be a desirable characteristic for generalization. Preferably the 'good' characteristics of two or more kernels should be combined. It is shown that using mixtures of kernels can result in having both good interpolation and extrapolation abilities. The performance of this method is illustrated with an artificial as well as an industrial data set.

Abstract A new technique to analyze the short‐chain branching distribution (SCBD) in linear lowdensity polyethylene has been developed. The technique referred as crystallization analysis fractionation is based on a stepwise precipitation approach. By monitoring the polymer solution concentration during crystallization, the cumulative and differential SCBD can be obtained without the need of physical separation of fractions. The new technique has been shown to provide similar results to temperature rising elution fractionation but in a shorter time and with a simplified apparatus. It allows the simultaneous analysis of various samples and could also be used for analysis of polypropylene and other semicrystalline polymers that can be fractionated on the basis of crystallizability. © 1994 John Wiley & Sons, Inc.

We present a predictive scheme connecting the topological structure of highly branched entangled polymers, with industrial-level complexity, to the emergent viscoelasticity of the polymer melt. The scheme is able to calculate the linear and nonlinear viscoelasticity of a stochastically branched "high-pressure free radical" polymer melt as a function of the chemical kinetics of its formation. The method combines numerical simulation of polymerization with the tube/entanglement physics of polymer dynamics extended to fully nonlinear response. We compare calculations for a series of low-density polyethylenes with experiments on structural and viscoelastic properties. The method provides a window onto the molecular processes responsible for the optimized rheology of these melts, connecting fundamental science to process in complex flow, and opens up the in silico design of new materials.

Abstract A comprehensive 13 C‐NMR method for the analysis of composition in the most common commercial polyethylene copolymers has been established. The method covers ethene copolymers with propene, butene‐1, hexene‐1, octene‐1, and 4‐methyl pentene‐1 in the composition range of 1–10 mol %. The chemical shift assignments and T 1 values of the resonances of the copolymers are presented. Results of precision studies and interlaboratory analyses showed that the molar composition could be determined with a relative precision at 2δ of about 6%. This method is being proposed to ASTM as Method X70‐8605‐2.

The development of a catalytic, one-step route for the oxidation of methane to methanol remains one of the greatest challenges within catalysis. Of particular importance is the need to develop an efficient route that proceeds under mild reaction conditions so as to avoid deeper oxidation and the economic limitations of the currently practiced syngas route. Recently, it was demonstrated that a copper- and iron-containing zeolite is an efficient catalyst for such a one-step process. The catalyst in question (Cu–Fe–ZSM-5) is capable of selectively transforming methane to methanol in an aqueous medium with hydrogen peroxide as the terminal oxidant. Nevertheless, despite its high activity and unparalleled methanol selectivity, the origin of its activity and the precise nature of its active species are not yet fully understood. Through a combination of catalytic and spectroscopic studies, we hereby demonstrate that extraframework Fe species are the active component of the catalyst for methane oxidation, although the speciation of these sites from synthesis to catalysis significantly alters the observed activity and selectivity. The analogies and differences between this system and other iron-containing zeolite-catalyzed processes, such as N2O-mediated benzene hydroxylation, are also considered.

/CO = 1). Upon addition of sodium and sulfur promoters to iron nanoparticles supported on carbon nanofibers, initial catalytic activities were high, but substantial deactivation was observed over a period of 100 h. In situ Mössbauer spectroscopy revealed that after 20 h time-on-stream, promoted catalysts attained 100% carbidization, whereas for unpromoted catalysts, this was around 25%. In situ carbon deposition studies were carried out using a tapered element oscillating microbalance (TEOM). No carbon laydown was detected for the unpromoted catalysts, whereas for promoted catalysts, carbon deposition occurred mainly over the first 4 h and thus did not play a pivotal role in deactivation over 100 h. Instead, the loss of catalytic activity coincided with the increase in Fe particle size to 20-50 nm, thereby supporting the proposal that the loss of active Fe surface area was the main cause of deactivation.

The aim of any diffraction experiment is to obtain reproducible data of high accuracy and precision so that the data can be correctly interpreted and analyzed. Various methods of sample preparation have been devised so that reproducibility, precision and accuracy can be obtained. The success of a diffraction experiment will often depend on the correct choice of preparation method for the sample being analyzed and for the instrument being used in the analysis. A diffraction pattern contains three types of useful information: the positions of the diffraction maxima, the peak intensities, and the intensity distribution as a function of diffraction angle. This information can be used to identify and quantify the contents of the sample, as well as to calculate the material's crystallite size and distribution, crystallinity, and stress and strain. The ideal preparation for a given experiment depends largely on information desired.

Plastic foams have found a number of applications in the energy absorption, thermal, and acoustic markets. Here advances that have been made with extruded polystyrene, polyolefin, and polyurethane foams, and their uses, particularly in the automotive industry, are highlighted. The Figure shows a 65 % compressed foam.

Fe- and Cu-containing zeolites have recently been shown to be efficient catalysts for the one-step selective transformation of methane into methanol in an aqueous medium at only 50 °C, using H2O2 as green oxidant. Previously, we have observed that Fe species alone are capable of catalyzing this highly selective transformation. However, further catalytic testing and spectroscopic investigations demonstrate that although these extra-framework Fe species are the active component of the catalyst, significant promotion is observed upon the incorporation of other trivalent cations, e.g., Al3+ or Ga3+, into the MFI-framework. While these additional framework species do not constitute active catalytic centers, promotion is observed upon their incorporation as they (1) facilitate the extraction of Fe from the zeolite framework and hence increase the formation of the active Fe species and (2) provide an associated negatively charged framework, which is capable of stabilizing and maintaining the dispersion of the cationic extra-framework Fe species responsible for catalytic activity. By understanding these phenomena and subsequently controlling the overall composition of the catalyst (Fe and Al), we have subsequently been able to prepare a catalyst of equal intrinsic activity (i.e., TOF) but five-times higher productivity (i.e., space-time-yield) compared with the best catalysts reported for this reaction to date.

The partial oxidation of methane to methanol presents one of the most challenging targets in catalysis. Although this is the focus of much research, until recently, approaches had proceeded at low catalytic rates (<10 h(-1)), not resulted in a closed catalytic cycle, or were unable to produce methanol with a reasonable selectivity. Recent research has demonstrated, however, that a system composed of an iron- and copper-containing zeolite is able to catalytically convert methane to methanol with turnover frequencies (TOFs) of over 14,000 h(-1) by using H(2)O(2) as terminal oxidant. However, the precise roles of the catalyst and the full mechanistic cycle remain unclear. We hereby report a systematic study of the kinetic parameters and mechanistic features of the process, and present a reaction network consisting of the activation of methane, the formation of an activated hydroperoxy species, and the by-production of hydroxyl radicals. The catalytic system in question results in a low-energy methane activation route, and allows selective C(1)-oxidation to proceed under intrinsically mild reaction conditions.

Ein Eisen-Kupfer-Zeolith (Fe-Cu-ZSM-5) katalysiert die selektive Oxidation von Methan zu Methanol mit wässrigem Wasserstoffperoxid. Das Eisen aktiviert die Kohlenstoff-Wasserstoff-Bindung, während das Kupfer dafür sorgt, dass Methanol als Hauptprodukt gebildet wird. Der Katalysator ist stabil und wiederverwendbar und aktiviert Methan mit >90 % Selektivität und 10 % Umsatz in einem geschlossenen Katalysezyklus (siehe Schema). Detailed facts of importance to specialist readers are published as ”Supporting Information”. Such documents are peer-reviewed, but not copy-edited or typeset. They are made available as submitted by the authors. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

A qualitative review of the epidemiological literature on the herbicide 2,4-dichlorophenoxyacetic acid (2,4-D) and health after 2001 is presented. In order to compare the exposure of the general population, bystanders and occupational groups, their urinary levels were also reviewed. In the general population, 2,4-D exposure is at or near the level of detection (LOD). Among individuals with indirect exposure, i.e. bystanders, the urinary 2,4-D levels were also very low except in individuals with opportunity for direct contact with the herbicide. Occupational exposure, where exposure was highest, was positively correlated with behaviors related to the mixing, loading and applying process and use of personal protection. Information from biomonitoring studies increases our understanding of the validity of the exposure estimates used in epidemiology studies. The 2,4-D epidemiology literature after 2001 is broad and includes studies of cancer, reproductive toxicity, genotoxicity, and neurotoxicity. In general, a few publications have reported statistically significant associations. However, most lack precision and the results are not replicated in other independent studies. In the context of biomonitoring, the epidemiology data give no convincing or consistent evidence for any chronic adverse effect of 2,4-D in humans.

A wide variety of hydrocarbon processes, catalytic or noncatalytic, involve the formation of carbon deposits, either on catalysts or on reactor (or engine/exhaust) surfaces. Therefore, researchers have developed a large array of catalysts to aid the combustion of these deposits. Recently, the mechanism of catalytic carbon oxidation and/or gasification has been the focus of research in an attempt to design better catalysts for carbon removal. With this approach, understanding the mechanism of formation of different types of carbon deposits is desired. Efforts undertaken for studying oxidation or gasification of various forms of carbon deposits are discussed in this review, along with the techniques used to study the mechanism of oxidation/gasification. The kinetics of catalyzed and noncatalytic carbon oxidation are described in detail. The effect of reactive gases such as NOx, water vapor, CO2, and SO2 on the gasification behavior of carbon deposits is also discussed. Reaction rates of oxidation/gasification of carbon under different operating conditions have been calculated, allowing for a comprehensive overview of carbon removal reactivity.

Abstract The phase morphology of intensively melt mixed and injection moulded bisphenol‐A polycarbonate (PC)/styrene‐acrylonitrile copolymer (SAN) blends changes on annealing above the glass‐transition temperature ( T g ) of both components. For the selected PC and SAN resins, the phase morphology of the 60/40 PC/SAN blend changes from a fine dispersion of the PC phase in a SAN matrix to a coarse co‐continuous phase network, whereas a co‐continuous 70/30 PC/SAN blend changes to a dispersion of SAN domains in a PC matrix. The effect of the blend morphology on dynamic mechanical properties and ambient tensile stress‐strain properties have been studied thoroughly. An increase of the storage modulus between T g (SAN) and T g (PC) is observed with increasing coarsening of the phase structure until a continuous PC matrix is formed. The coarsening of the phase structure of the blends gives rise to a transition from ductile to brittle fracture. The loss in ductility is related to a decrease in relative amount of interface and a transition in the type of dispersion.

A closer look at catalysis: In situ hard X-ray nanotomography has been developed (see picture) as a method to investigate an individual iron-based Fischer–Tropsch-to-Olefins (FTO) catalyst particle at elevated temperatures and pressures. 3D and 2D maps of 30 nm resolution could be obtained and show heterogeneities in the pore structure and chemical composition of the catalyst particle of about 20 μm. Detailed facts of importance to specialist readers are published as ”Supporting Information”. Such documents are peer-reviewed, but not copy-edited or typeset. They are made available as submitted by the authors. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.