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Scientists Build an Efficient Model for Converting Carbon Dioxide into Fuels and Products

Screenshot 2024-06-14 at 2.01.58 AM

Scientists Build an Efficient Model for Converting Carbon Dioxide into Fuels and Products

Climate Insider Brief:

  • A team from Berkeley Lab and UC Berkeley has developed a digital model using Marcus–Hush–Chidsey kinetics to better understand and optimise MEAs for CO2 conversion, significantly improving predictive accuracy and addressing issues like CO2 crossover.
  • The enhanced model allows for virtual experiments to optimise MEA designs, focusing on factors like catalyst-layer thickness and ion transport. Future research aims to further refine the model, promising advancements in CO2 conversion technologies and sustainable industrial processes.
  • Excess renewable energy can be utilised to convert CO2 into valuable products using membrane-electrode assemblies (MEAs), which are complex systems also used in fuel cells to convert hydrogen into electricity.

In some regions, the production of renewable electricity has become so efficient and cost-effective that it occasionally leads to an excess supply. One innovative use for this surplus energy is the conversion of carbon dioxide (CO2) into fuel and other valuable products using membrane-electrode assemblies (MEAs).

A collaborative team of scientists from Lawrence Berkeley National Laboratory (Berkeley Lab) and the University of California, Berkeley, has made significant strides in understanding and optimising this promising technology through advanced physics modelling. Their recent study, published in the journal Nature Chemical Engineering, offers insights that could enhance the efficiency of MEAs.

MEAs, which are also used in fuel cells for converting hydrogen into electricity, hold potential for utilising excess renewable energy to drive reactions that convert CO2 into useful chemicals such as carbon monoxide and ethylene. These chemicals serve as feedstocks for a variety of industrial products, including chemicals and packaging materials. However, the efficiency of MEAs has been a challenge, and their complex workings are not fully understood.

Adam Weber, a senior scientist at Berkeley Lab and the study’s corresponding author, explains the complexity of MEAs: “Membrane-electrode assemblies are complicated systems with multiple layers. Each layer holds different chemical species, additives, and particles. Often, we don’t really know why experiments with membrane-electrode assemblies produce certain products, or why they fail to convert a larger percentage of a given amount of carbon dioxide.”

To address these challenges, the researchers developed a digital model designed to accelerate the optimization of MEAs for CO2 conversion. This model incorporates Marcus–Hush–Chidsey kinetics, a theoretical framework critical for understanding the reaction mechanisms within MEAs, which had not previously been applied to this type of modelling. This integration allowed the researchers to more accurately predict real-world outcomes and address issues like crossover, where CO2 moves across the membrane instead of reacting.

Validation of the model against experimental data demonstrated its improved predictive capabilities over previous models. The enhanced accuracy stems from the model’s ability to account for the role of water orientation, among other factors.

Using their advanced model, the team conducted virtual experiments to explore the performance of various MEA designs. These experiments focused on variables such as catalyst-layer thickness and catalyst-specific surface area. The researchers identified key design rules related to the importance of coupled ion and water transport, as well as the trade-offs between transport phenomena, reaction kinetics, and buffer kinetics. These findings are crucial for optimising the overall energy efficiency, product yield, and CO2 conversion rate of MEAs.

“Having a digital twin of a system allows you to probe a much larger parameter space much more rapidly than in experiments, which are typically complex and require special equipment,” Weber noted. “We can’t see where every molecule is in an experiment. But in a model, we can.”

Looking ahead, the research team aims to increase the complexity of their model to evaluate the performance of MEAs over their operational lifetime and under various conditions. This ongoing research holds promise for advancing the use of renewable energy in CO2 conversion technologies, contributing to more sustainable industrial processes and energy solutions.

SOURCE: Microsoft Start

Featured Image: Credit: Nature Chemical Engineering

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