The electrochemical reduction of carbon dioxide (CO 2 RR) to chemical feedstocks, such as ethylene (C 2 H 4 ), is an attractive means to mitigate emissions and store intermittent renewable electricity. Much research has focused on improving CO 2 electrolysis cell efficiency; less attention has been paid to the downstream purification of outlet product streams. In this work, we model the use of mature downstream separation technologies as part of the overall production of polymer-grade C 2 H 4 from CO 2 . We find that CO 2 removal is the most energy-intensive downstream separation step. We identify opportunities to reduce separation energies to ∼22 GJ/tonne C 2 H 4 through necessary improvements in C 2 H 4 selectivity (>57%), cathodic CO 2 conversion (>80%), and CO 2 crossover (0 mol CO 2 /mol e − ). This work highlights the influence of cell performance parameters on downstream separation costs and motivates the development of new, efficient separation processes better suited to the distinctive outlet streams of CO 2 electrolyzers.

Carbon dioxide (CO 2 ) electrolysis powered with renewable electricity can help close the carbon cycle by converting emissions into chemicals and fuels. Two key advancements are required to bridge the technological gaps for industrial implementation: pilot plant demonstrations with detailed performance data; and chemical engineering process models built and tested with lab-and pilot-scale data. Here, we develop a semi-empirical electrolyzer model in Aspen Custom Modeler which is trained on a 5 cm 2 lab-scale CO 2 electrolyzer. We then scale to a pilot-scale 800 cm 2 single cell and 10 × 800 cm 2 stack and use the results to validate the model; at 100 mA cm −2 , the model can predict six of seven cell performance metrics within 16% absolute error and three of five stack metrics within 11% absolute error. With the combination of the electrolyzer model and the pilot-scale data, this work provides the prerequisites for further scaling of CO 2 electrolysis.

A computational fluid dynamics model was developed to represent high‐solids enzymatic hydrolysis. This model accounted for the transient and multiphase (solids‐slurry) nature of the high‐solids enzymatic hydrolysis process. The model investigated the effect of slurry viscosity, rotational speed, and two impeller configurations on the distribution of insoluble solids. Initial CFD results identified segregation of the velocity contours for the non‐Newtonian slurry, which could potentially affect the reactor performance. The multiphase, transient CFD simulations showed that the first impeller configuration delayed the distribution of solids, and compartmentalized mixing in the reactor. The second impeller configuration, meanwhile, improved solids mixing and hydrolysis, while using lower rotational speeds (and thus, energy). The second impeller configuration also expanded the size of the pseudo‐cavern between impellers, which is critical for better dispersion of the solids. The CFD trends of the second impeller configuration were experimentally verified by conducting fed‐batch, high‐solids enzymatic hydrolysis trials with pretreated lignocellulose. The experimental results showed that the second impeller configuration provided better mixing of the non‐Newtonian slurry and enhanced solids‐enzyme interactions, leading to improved glucan‐to‐glucose conversion. This work illustrates that a transient multiphase CFD model can provide valuable insights into the design and optimization of high‐solids enzymatic hydrolysis reactors. The CFD model has identified pathways to improve the distribution of solids while reducing the energy needed for mixing. The CFD model can also guide experimental and design work to scale up these reactors from the laboratory to pilot and commercial scale.

The electrochemical reduction of carbon dioxide (CO2RR) to chemical feedstocks, such as ethylene (C2H4), is an attractive means to mitigate emissions and store intermittent renewable electricity. Much research has focused on improving CO2 electrolysis cell efficiency; less attention has been paid to the downstream purification of outlet product streams. In this presentation, we model the use of mature downstream separation technologies as part of the overall production of polymer-grade C2H4 from CO2. We find that CO2 removal is the most energy-intensive downstream separation step. We identify opportunities to reduce separation energies ten-fold to ∼22 GJ/tonne C2H4 through necessary improvements in C2H4 selectivity (>57%), cathodic CO2 conversion (>80%), and CO2 crossover (0 mol CO2/mol e−). This work highlights the influence of cell performance parameters on downstream separation costs and motivates the development of new, efficient separation processes better suited to the distinctive outlet streams of CO2 electrolyzers.

This study presents a novel computational fluid dynamics (CFD) model to investigate important aspects of the complex high-solids enzymatic hydrolysis (HSEH) process. The uniqueness of this CFD model lies in integrating the biochemical reaction taking place in the secondary phase and the corresponding mass transfer of the products from the secondary phase to the non-Newtonian primary phase, while dual axial impellers blend the multiphase system. The distribution of the reactants and products in the non-Newtonian primary phase affects the overall conversion of glucan to glucose, which, in turn, affects the commercial deployment of these systems for the production of renewable sugars. We investigated the effect of slurry viscosity on insoluble and soluble solids distribution, the impact of initial insoluble solids loading on total solids distribution, and varying the initial chemical composition of the insoluble solids on the total solids distribution. The comprehensive CFD model results show that variations in the chemical composition of the insoluble solids and the solids loading can each have a pronounced effect on the distribution of solids. This behavior would then affect the rate and extent of conversion of insoluble solids to soluble solids. Thus, the comprehensive CFD model can account for the interactions between independent variables, facilitating the design of small and large-scale reactors, while improving the conversion of insoluble solids to soluble solids. This novel CFD model thus represents the combined effects of key factors that influence HSEH in a realistic process environment.