Data-driven pilot optimization for electrochemical CO mass production

Abstract

Electroreduction systems to convert CO(2)into COviaAg electrodes have been intensely studied as a means of producing carbon-neutral fuels or chemical products. However, despite many efforts to maximize the performance of CO-producing systems, the performance of electrochemical cells that produce CO has not yet reached the level of economic viability. Moreover, compared with electrode development attempts, studies on the optimization of large-scale CO-producing systems are lacking, thus impeding the commercialization of electrochemical CO(2)reduction systems. In this study, we present optimization results of a pilot-scale CO production system. Operating conditions such as pressure, temperature, and cell voltage were considered as the optimization variables to improve the CO partial current density. To facilitate experiment-based optimization of the pilot-scale operation, we adopted an efficient design of the experiment, for which data points were decided by input-output relations. As a result, the maximum CO partial current reached 2.56 A using a 50 cm(2)electrode within 25 experiments. In addition, regression analysis results were provided for future studies on the systematic optimization of electrochemical systems. The operating temperature and CO(2)solubility were more highly correlated with the current density and selectivity than was the applied cell voltage, and the CO current density could be predicted with high accuracy.