Bio-ethanol steam reforming on Ni based catalyst. Kinetic study

Llera, I.; Mas, V.; Bergamini, M. L.; Laborde, Miguel; Amadeo, Norma

doi:10.1016/j.ces.2011.12.018

Cited by 63 publications

(57 citation statements)

References 32 publications

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“…The same authors substantially refined the first proposed kinetic model in a later work [53], based on an extensive data collection obtained by tests on a catalysts of Ni/alumina and Ni(II)/Al(III), taking advantage of the mechanism selection already worked out by Graschinsky et al [54] (data from a Rh/magnesia/alumina catalyst) and of a similar work by Sahoo et al [55] to explain their own data (Co/alumina). While these papers share the same core of RDS, the latter authors adopt an abridged stoichiometry where the methanation is not treated explicitly, as it were just the 'equilibration link' between "dry reforming" and a full "steam reforming".…”

Section: Rdsmentioning

confidence: 99%

Process Simulation for the Design and Scale Up of Heterogeneous Catalytic Process: Kinetic Modelling Issues

et al. 2017

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Abstract:Process simulation represents an important tool for plant design and optimization, either applied to well established or to newly developed processes. Suitable thermodynamic packages should be selected in order to properly describe the behavior of reactors and unit operations and to precisely define phase equilibria. Moreover, a detailed and representative kinetic scheme should be available to predict correctly the dependence of the process on its main variables. This review points out some models and methods for kinetic analysis specifically applied to the simulation of catalytic processes, as a basis for process design and optimization. Attention is paid also to microkinetic modelling and to the methods based on first principles, to elucidate mechanisms and independently calculate thermodynamic and kinetic parameters. Different case studies support the discussion. At first, we have selected two basic examples from the industrial chemistry practice, e.g., ammonia and methanol synthesis, which may be described through a relatively simple reaction pathway and the relative available kinetic scheme. Then, a more complex reaction network is deeply discussed to define the conversion of bioethanol into syngas/hydrogen or into building blocks, such as ethylene. In this case, lumped kinetic schemes completely fail the description of process behavior. Thus, in this case, more detailed-e.g., microkinetic-schemes should be available to implement into the simulator. However, the correct definition of all the kinetic data when complex microkinetic mechanisms are used, often leads to unreliable, highly correlated parameters. In such cases, greater effort to independently estimate some relevant kinetic/thermodynamic data through Density Functional Theory (DFT)/ab initio methods may be helpful to improve process description.

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Section: Rdsmentioning

confidence: 99%

Process Simulation for the Design and Scale Up of Heterogeneous Catalytic Process: Kinetic Modelling Issues

et al. 2017

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“…CH 4 production increased between 400 and 600 • C (Figure 1d). The decomposition of ethanol (Equation (5)) and slow CH 4 reforming (Equation (8)) could be taking place [26,54]. Above 600 • C, complete conversion of ethanol was ensured (Figure 1a), and a decrease in CH 4 production was observed in most of the catalysts (Figure 1d), except for Rh 0.2 Pt 0.6 /CeO 2 .…”

Section: Effect Of the Rh-pt Ratio On The Catalytic Performancementioning

confidence: 88%

“…At temperatures <500 • C, energy requirement decreased, likely due to the presence of an exothermic reaction, such as WGSR (−41.2 kJ/mol) [71]. Llera et al [54] reported that the activation energy and changes in enthalpy are closely related to intermediate reactions occurring during SRE. Then, the difference in the energy requirements of each catalyst could be an indication that the Rh-Pt ratio favors different reaction mechanisms, as previously discussed in Section 2.1.…”

Section: Energy Analysis From Rsm and Aspen Plus Integrationmentioning

confidence: 99%

Response Surface Methodology and Aspen Plus Integration for the Simulation of the Catalytic Steam Reforming of Ethanol

2017

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Abstract:The steam reforming of ethanol (SRE) on a bimetallic RhPt/CeO 2 catalyst was evaluated by the integration of Response Surface Methodology (RSM) and Aspen Plus (version 9.0, Aspen Tech, Burlington, MA, USA, 2016). First, the effect of the Rh-Pt weight ratio (1:0, 3:1, 1:1, 1:3, and 0:1) on the performance of SRE on RhPt/CeO 2 was assessed between 400 to 700 • C with a stoichiometric steam/ethanol molar ratio of 3. RSM enabled modeling of the system and identification of a maximum of 4.2 mol H 2 /mol EtOH (700 • C) with the Rh 0.4 Pt 0.4 /CeO 2 catalyst. The mathematical models were integrated into Aspen Plus through Excel in order to simulate a process involving SRE, H 2 purification, and electricity production in a fuel cell (FC). An energy sensitivity analysis of the process was performed in Aspen Plus, and the information obtained was used to generate new response surfaces. The response surfaces demonstrated that an increase in H 2 production requires more energy consumption in the steam reforming of ethanol. However, increasing H 2 production rebounds in more energy production in the fuel cell, which increases the overall efficiency of the system. The minimum H 2 yield needed to make the system energetically sustainable was identified as 1.2 mol H 2 /mol EtOH. According to the results of the integration of RSM models into Aspen Plus, the system using Rh 0.4 Pt 0.4 /CeO 2 can produce a maximum net energy of 742 kJ/mol H 2 , of which 40% could be converted into electricity in the FC (297 kJ/mol H 2 produced). The remaining energy can be recovered as heat.

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“…The same authors substantially refined the first proposed kinetic model in a later work [45], based on an extensive data collection obtained by tests on a catalysts of Ni/alumina and Ni(II)/Al(III), taking advantage of the mechanism selection already worked out by Graschinsky et al [46] (data from a Rh/magnesia/alumina catalyst) and of a similar work by Sahoo et al [47] to explain their own data (Co/alumina). While these papers share the same core of RDS, the latter authors adopt an abridged stoichiometry where the methanation is not treated explicitly, as it were just the 'equilibration link' between "dry reforming" and a full "steam reforming".…”

Section: Rdsmentioning

confidence: 99%

Kinetic Modelling at the Basis of Process Simulation for Heterogeneous Catalytic Process Design

Tripodi¹,

Compagnoni²,

Martinazzo³

et al. 2017

Preprint

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Process simulation represents an important tool for plant design and optimisation, either applied to well established or to newly developed processes. Suitable thermodynamic packages should be selected in order to properly describe the behaviour of reactors and unit operations and to precisely define phase equilibria. Moreover, a detailed and representative kinetic scheme should be available to predict correctly the dependence of the process on its main variables. This review points out some models and methods for kinetic analysis specifically applied to the simulation of catalytic processes, as a basis for process design and optimisation. Attention is paid also to microkinetic modelling and to the methods based on first principles, to elucidate mechanisms and calculate thermodynamic and kinetic parameters. Different case histories support the discussion. At first, we have selected two basic examples from the industrial chemistry practice, e.g. ammonia and methanol synthesis, which may be described through a relatively simple reaction pathway. Then, a more complex reaction network is deeply discussed to define the conversion of bioethanol into syngas/hydrogen or into building blocks, such as ethylene.

show abstract

Bio-ethanol steam reforming on Ni based catalyst. Kinetic study

Cited by 63 publications

References 32 publications

Process Simulation for the Design and Scale Up of Heterogeneous Catalytic Process: Kinetic Modelling Issues

Process Simulation for the Design and Scale Up of Heterogeneous Catalytic Process: Kinetic Modelling Issues

Response Surface Methodology and Aspen Plus Integration for the Simulation of the Catalytic Steam Reforming of Ethanol

Kinetic Modelling at the Basis of Process Simulation for Heterogeneous Catalytic Process Design

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