Significant efforts have been dedicated to advancing electrochemical CO2 conversion technologies. However, existing techno-economic analysis (TEA) approaches often lack the capability to address the multifaceted barriers associated with scaling and commercializing these emerging technologies. To bridge this gap, we present an integrated assessment framework that enhances TEA by incorporating bottom-up component cost, manufacturing cost, learning rates, and market adoption dynamics. This framework provides a rigorous, data-driven approach to predicting the scaling and commercialization potential of electrochemical CO2 conversion technologies.
To develop the integrated scaling up and commercialization assessment methodology, we start with consolidating benchmark data, including technology performance metrics, cost parameters, supply chain considerations, and market trends, facilitating the development of learning and adoption curves. Then we leverage the collected data and process models to generate process designs, material and manufacturing cost estimations, and cost breakdowns, enabling the identification of key cost-driving factors. Subsequently, we integrate the data and function into an open-source platform, allowing for rapid scenario exploration, sensitivity analysis, and estimation of commercialization timescales and realistic manufacturing scale-up costs.
Within the scope of scaling up and commercialization assessment of electrochemical CO2 conversion technologies, we first focus on a typical membrane electrode assembly (MEA)-based electrolyzer system. The key components identified include the supply module (CO2, water, and power), the core electrolyzer module, the separation module, the recycle system, and the separation and storage module. Cost projections for these components and the assembly process are derived using learning curves based on Wright’s law. Given the nascent stage of the target technologies, data from related electrochemical systems, such as flow batteries and water reduction technologies, are incorporated to enhance accuracy. Preliminary results indicate that customization requirements (e.g., catalysts), assembly complexity, and system stability are important factors influencing uncertainties and ultimately determining the scalability and commercialization potential of these technologies. In summary, the developed integrated assessment framework helps identify key areas where improved data accuracy could significantly enhance predictive reliability. By integrating techno-economic and market analysis, this work supports the acceleration of electrochemical CO2 conversion technologies from research to commercial deployment.
