Advances in reforming and partial oxidation of hydrocarbons for hydrogen production and fuel cell applications

One of the most attractive routes for the production of hydrogen or syngas for use in fuel cell applications is the reforming and partial oxidation of hydrocarbons. The use of hydrocarbons in high temperature fuel cells is achieved through either external or internal reforming. Reforming and partial oxidation catalysis to convert hydrocarbons to hydrogen rich syngas plays an important role in fuel processing technology. The current research in the area of reforming and partial oxidation of methane, methanol and ethanol includes catalysts for reforming and oxidation, methods of catalyst synthesis, and the effective utilization of fuel for both external and internal reforming processes. In this paper the recent progress in these areas of research is reviewed along with the reforming of liquid hydrocarbons, from this an overview of the current best performing catalysts for the reforming and partial oxidizing of hydrocarbons for hydrogen production is summarized

Artificial neural networks assisted catalyst design and optimisation of methane steam reforming

Hydrogen has diverse industrial applications namely in ammonia synthesis, petroleum refining and methanol production. The advent of fuel cell technology had prompted hydrogen as an efficient source of energy carrier. Catalytic steam reforming of natural gas (primarily methane) supplies half of global hydrogen demand. Since methane is the major component of natural gas, catalytic steam reforming of natural gas is referred as methane steam reforming (MSR). However this process is energy intensive because of industrial operations that are carried out at stem-to-carbon feed ratio (S:C) > 3 to avoid carbon formation. The most cost effective way of optimising this mature technology may be carried out via design of novel catalyst that are highly active at low S:C, thermally stable and resistant to carbon formation. Catalyst design and evaluation for MSR is a multifactorial multi-objective optimisation problem and the absence of well-defined mechanistic relationships between wide ranging input-output variables has stimulated interest in the application of artificial neural network (ANN) for the analysis of the large body of empirical data available. However, single ANN models generally have limited predictive capability and insufficient to capture the broad range of features inherent in the voluminous but dispersed data sources. In this study, a Fibonacci approach to select optimal number of neurons for the ANN architecture followed by a new weighted optimal combination of statistically-derived candidate ANN models in a multi-error sense was employed. The results from the experimental validation was consistent with ANN model prediction and further investigation identified 1 wt% Ce promoted 10 wt% Ni/SBA-15 as an efficient catalyst for MSR. This catalyst displayed excellent activity for MSR with a feed composition of S:C = 1:1 2:1 at atmospheric pressure and reaction temperature 1073 K for 72 h time-on-stream resulting in 92% - 99% methane conversion rates under steady-state conditions. Under these experimental conditions surprisingly, in particular the S:C = 1:1 runs did not exhibit any signs of carbon deposition which may be attributed to 1 wt% promotion of Ce. Moreover, an activation energy of 49.8 kJ mol-1 was obtained for MSR over this catalyst through a macro power-law modelling

Mechanistic investigation of methane steam reforming over Ce-promoted Ni/SBA-15 catalyst

Methane steam reforming experiments were carried out at atmospheric pressure for temperatures between 873 and 1073 K and by varying the partial pressure of methane and steam to achieve S:C between 0.5 and 2.5. Mechanistic considerations for Methane steam reforming (MSR) were derived on the basis of Langmuir–Hinshelwood and Eley–Rideal reaction mechanisms based on single- and dual-site associative and dissociative adsorption of one or both reactants. However, discrimination of these models on statistical and thermodynamic grounds revealed that the model representing a single-site dissociative adsorption of methane and steam most adequately explained the data. However, the product formation rates from these experiments were reasonably captured by power-law model. The parameter estimates from the power-law model revealed an order of 0.94 with respect to methane and -0.16 for steam with activation energy of 49.8 kJ mol-1 for MSR. The negative order with respect to steam for methane consumption was likely due to steam inhibition

Promotional Effect of Ce-dopant on Al2O3-supported Co Catalysts for Syngas Production via CO2 Reforming of Ethanol

The effect of ceria promotion on Co/Al2O3 catalysts for ethanol dry reforming has been investigated at stoichiometric feed composition and 973 K under atmospheric pressure. Ce-promoted catalysts were synthesized using a wet co-impregnation method and evaluated in a quartz fixed-bed reactor. X-ray diffraction measurements indicated the formation of CeO2, Co3O4 and CoAl2O4 phases on catalyst surface. Ce-addition eased the reduction process of Co3O4 to CoO phase which was subsequently reduced to metallic Co0 form. H2 nd CO yields as well as ethanol conversion increased with growing Ce loading and approached the greatest value at 3 wt.%Ce followed by a considerable drop beyond this optimal Ce content. Both promoted and unpromoted catalysts were stable with time-on-stream and the improvement of catalytic performance with Ce-addition was reasonably due to the high oxygen storage capacity of CeO2 promoter which oxidizing carbonaceous species. The heterogeneous nature of deposited carbons containing carbon nanofilament and graphite on spent catalyst surface was evident by scanning electron microscopy. However, the filamentous carbon appeared to be predominant on the surface of spent catalyst in comparison with undesirable graphite responsible for catalyst deterioration. Additionally, Ce-promoted catalysts were resistant to carbon deposition. ?? 2016 The Authors. Published by Elsevier Ltd