CO2 Hydrogenation to Methanol Over Cu/ZnO/Al2O3 Catalyst: Kinetic Modeling Based on Either Single- or Dual-Active Site Mechanism

CO₂ hydrogenation to CH₃OH via heterogeneous catalysis is one of the most promising and available approaches for mitigation of anthropogenic CO₂ issues. In this work, thermodynamic equilibria of CO₂ to methanol were compared with experimental results at given conditions using a commercial Cu/ZnO/Al₂O₃ catalyst for CO hydrogenation to methanol. It was found that, the high pressure, low temperature, and high H₂/CO₂ ratio are favorable to methanol synthesis from CO₂. Furthermore, the kinetic data were measured with an isothermal integral reactor under temperature between 160 and 240 °C, lower than that for CO hydrogenation to methanol reaction. Based on the single-active site and dual-active site LH mechanisms, both kinetic models can achieve full illustration of the influence of the operating conditions and the mechanisms. According to comparative analysis of the error variances of model correlations and the adsorbate coverages on the active sites, the dual-site mechanism identified to be superior to the single-site one for methanol synthesis from CO₂ feedstock. Overall, this paper provides fundamental understanding of the thermodynamic and kinetic aspects of a central route for CO₂ Valorisation.

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An IE-ODDM-MLFMA Scheme With DILU Preconditioner for Analysis of Electromagnetic Scattering From Large Complex Objects

For electrically large complex electromagnetic (EM) scattering problems, huge memory is often required for most EM solvers, which is too difficult to be handled by a personal computer (PC) even a workstation. Although the multilevel fast multipole algorithm (MLFMA) effectively deals with electrically large problems to some extent, it is still time and memory consuming for very large objects. In order to further reduce the CPU time and the memory requirement, a hybrid algorithm, based on the overlapped domain decomposition method for integral equations (IE-ODDM), MLFMA and block-diagonal, incomplete lower and upper triangular matrices (DILU) preconditioner, is proposed for the analysis of electrically large problems. The dominant memory requirement for plane wave expansions in the three processes of aggregation, translation and disaggregation in the MLFMA is drastically reduced by the first two techniques. The iterative procedure for each overlapped subdomain solved by the MLFMA is effectively sped up by the DILU preconditioner. After integrating these techniques, the proposed hybrid algorithm is more efficient in computing time and memory requirement compared to the conventional MLFMA and is more suitable for analyzing very large EM scattering problems. Enough accurate solution can be obtained within quite a few outer iterations, where an outer iteration means a complete sweep for all the subdomains. Some numerical examples are presented to demonstrate its validity and efficiency.