David Linke

Application of microstructured reactor technology for the photochemical chlorination of alkylaromatics

The advantageous application of a falling-film microreactor for a photochemical gas/liquid reaction was demonstrated by the selective photochlorination of toluene-2,4-diisocyanate (TDI) In the microstructured reactor the selectivity to the side-chain chlorinated product 1 -chloromethyl-2,4-diisocyanatobenzene (1CI-TDI) achieved a value of 80% at 55% TDI conversion, whereas the side product toluene-5-chloro-2,4-diisocyanate (5CI-TDI) was formed with only 5% selectivity. The yield of 1CI-TDI was enhanced by increasing the residence time from 24% after 5 s to 54% after 14 s. At the same time the formation of consecutive products increased and the selectivity to 1CI-TDI decreased to 67% after 14 s residence time. The influence of the reactor material was shown. In presence of a Lewis acid such as FeCl 3 , formed by chlorination using a reaction plate made of iron, consecutive products were formed and the selectivity to 1CI-TDI was lowered. The microstructured reactor led to remarkably higher selectivities than the conventional batch reactor, where the selectivity to 1CI-TDI was only 45% at 65% TDI conversion and the side product 5CI-TDI was formed with 50% selectivity. The space-time yield of 1CI-TDI achieved in the microstructured reactor (400 mol I - 1 h - 1 ) clearly exceeded the performance of the batch reactor (space-time yield 1.3 mol I - 1 h - 1 ). Based on the microreactor data, a kinetic model for the TDI chlorination including by-product formation was suggested and used to predict product selectivity at full TDI conversion.

ZrO2-Based Alternatives to Conventional Propane Dehydrogenation Catalysts: Active Sites, Design, and Performance

Non-oxidative dehydrogenation of propane to propene is an established large-scale process that, however, faces challenges, particularly in catalyst development; these are the toxicity of chromium compounds, high cost of platinum, and catalyst durability. Herein, we describe the design of unconventional catalysts based on bulk materials with a certain defect structure, for example, ZrO2 promoted with other metal oxides. Comprehensive characterization supports the hypothesis that coordinatively unsaturated Zr cations are the active sites for propane dehydrogenation. Their concentration can be adjusted by varying the kind of ZrO2 promoter and/or supporting tiny amounts of hydrogenation-active metal. Accordingly designed Cu(0.05 wt %)/ZrO2 -La2 O3 showed industrially relevant activity and durability over ca. 240 h on stream in a series of 60 dehydrogenation and oxidative regeneration cycles between 550 and 625 °C.

Effect of support on selectivity and on-stream stability of surface VOx species in non-oxidative propane dehydrogenation

Al2O3, SiO2(MCM-41), and Al2O3–SiO2 (Siral®) with a SiO2 content varying from 1 to 70 wt.% were used to prepare supported catalysts with a V loading below one monolayer. Their activity, selectivity and on-stream stability were tested in non-oxidative propane dehydrogenation (DH) at 550 °C. The highest space–time yield of propene was only 25% lower than that over industrially relevant Pt–Sn/Al2O3 under the same reaction conditions. All catalysts deactivated with time on stream, but restored their initial performance after oxidative regeneration as proven in a sequence of 10 DH/regeneration cycles lasting in total over 60 h. The deactivation was related to propene-derived carbon deposits covering active VOx sites. However, depending on the catalyst, such deposits formed on bare support sites can also participate in propane dehydrogenation. Their DH activity is, however, significantly lower compared to VOx species. Acidic properties of the support were found to be crucial for the generation of such catalytically active carbon species.

Optimization of Catalysts Using Specific, Description-Based Genetic Algorithms

This paper deals with the key optimization task that has to be solved when improving the performance of many chemical processes--optimization of the catalysts used in the reaction via the optimization of its composition and preparation. A novel approach is presented that allows for the preservation of the advantages of genetic algorithms developed specifically for the optimization of catalytic materials but avoids the disadvantageous necessity to reimplement the algorithm when the scope of the optimized materials changes. Its main idea is to automatically generate problem-tailored implementations from requirements concerning the materials with a program generator. For the specification of such requirements, a formal description language, called catalyst description language, has been developed.

The Enhancing Effect of Brønsted Acidity of Supported MoOx Species on their Activity and Selectivity in Ethylene/trans-2-Butene Metathesis

Supported catalysts with a nominal Mo surface density of 0.15 and 1.5 Mo atoms nm−2 were synthesized by impregnation of alumina, silica, and alumina–silica supports with silica content between 1 and 70 wt %. They were tested for their activity and selectivity in the metathesis of ethylene and trans‐2‐butene to propene between 343 and 603 K at 125 kPa. The catalysts were characterized by UV/Vis, Raman, and IR spectroscopy, XRD and H2 temperature‐programmed reduction for elucidating the distribution, degree of polymerization, reducibility, and acidity of MoOx species. We established that Brønsted acidity of highly dispersed tetrahedral and polymerized octahedral MoOx species is required to ensure high metathesis activity. The acidic character of these species is influenced by their structure and support. Tetrahedral MoOx species with Brønsted acidic character are only formed on supports possessing such acidity, whereas Brønsted acidic octahedral MoOx is also created on supports without such acidic sites.

Effect of VOx Species and Support on Coke Formation and Catalyst Stability in Nonoxidative Propane Dehydrogenation

VOx/SiO2–Al2O3 catalysts were prepared by grafting vanadyl acetylacetonate onto the supports with a SiO2 content between 0 and 100 wt. %. The degree of polymerization of VOx species and acidity both of pristine supports and the catalysts were evaluated. To determine their on‐stream stability and carbon deposition activity in nonoxidative propane dehydrogenation, continuous‐flow tests and in situ thermogravimetric measurements were performed. The rate constants of catalyst deactivation and carbon deposition were derived from kinetic evaluation of these experiments. Gathered experimental evidence pointed out that VOx species were significantly more active for coke formation than acid sites of the supports. The rate constant of carbon formation was found to increase with the degree of polymerization of VOx species, whereas no correlation between catalyst acidity and the rate constants of coking or deactivation could be drawn.

Catalytic partial oxidation of ethane to acetic acid over Mo1V0.25Nb0.12Pd0.0005Ox: reactor operation

Abstract The operation of a fixed-bed and fluidized-bed reactor for the partial oxidation of ethane to acetic acid was simulated. For the fixed-bed reactor a two-dimensional homogenous model and for fluidized-bed reactor the bubble assemblage model was applied. A kinetic model was used for reactor simulation, which describes the primary oxidative dehydrogenation of ethane to ethylene, the formation of acetic acid via ethylene, as an intermediate as well as a direct formation of acetic acid from ethane. Carbon dioxide formation results from combustion of ethane, ethylene and acetic acid. Furthermore, the influence of water on the reaction pathway was taken into account in the kinetic model. For the fixed-bed reactor, the influence of inlet temperature was investigated in a temperature range from 500 to 525 K and at a total pressure of 16 bar . The range of temperature where the danger of run-away occurs depends on gas velocities and reactor diameters. Accordingly, for a reactor diameter of 0.025 m and a gas velocity of u STP =0.0045 m s −1 runaway must be expected above a temperature of the inlet feed of 520 K . In a fluidized-bed reactor, significant lower selectivities and space-time yields of acetic acid are achieved compared to the fixed-bed due to the slow mass transfer of oxygen between bubble and emulsion phase. However, yield and selectivity of acetic acid can be increased by applying small sized catalyst particles.

An Innovative Approach for Highly Selective Direct Conversion of CO2 into Propanol using C2H4 and H2

Multifunctional catalysts are developed for converting CO2 with C2H4 and H2 into propanol. Au nanoparticles (NP) supported on TiO2 are found to facilitate this reaction. The activity and selectivity strongly depend on NP size, which can be tuned by the method of Au deposition and by promoting with K. The promoter improves the selectivity to propanol. Under optimized reaction conditions (2 MPa, 473 K, and CO2/H2/C2H4=1:1:1), CO2 is continuously converted into propanol with a near-to-100% selectivity. Catalytic tests as well as mechanistic studies by in situ FTIR and temporal analysis of products with isotopic tracers allow the overall reaction scheme to be determined. Propanol is formed through a sequence of reactions starting with reverse water-gas shift to reduce CO2 to CO, which is further consumed in the hydroformylation of ethylene to propanal. The latter is finally hydrogenated to propanol, while propanol hydrogenation to propane is suppressed.

Neural networks as surrogate models for measurements in optimization algorithms

The paper deals with surrogate modelling, a modern approach to the optimization of objective functions evaluated via measurements. The approach leads to a substantial decrease of time and costs of evaluation of the objective function, a property that is particularly attractive in evolutionary optimization. The paper recalls common strategies for using surrogate models in evolutionary optimization, and proposes two extensions to those strategies - extension to boosted surrogate models and extension to using a set of models. These are currently being implemented, in connection with surrogate modelling based on feed-forward neural networks, in a software tool for problem-tailored evolutionary optimization of catalytic materials. The paper presents results of experimentally testing already implemented parts and comparing boosted surrogate models with models without boosting, which clearly confirms the usefulness of both proposed extensions.

Boosted Neural Networks in Evolutionary Computation

The paper deals with a neural-network-based version of surrogate modelling, a modern approach to the optimization of empirical objective functions. The approach leads to a substantial decrease of time and costs of evaluation of the objective function, a property that is particularly attractive in evolutionary optimization. In the paper, an extension of surrogate modelling with regression boosting is proposed, which increases the accuracy of surrogate models, thus also the agreement between results obtained with the model and those obtained with the original objective function. The extension is illustrated on a case study in materials science. Presented case study results clearly confirm the usefulness of boosting for neural-network-based surrogate models.