Identifying key drivers of product formation in microbial electrosynthesis with a mixed linear regression analysis

Defossilization of industrial processes has led to a growing interest in alternative biotechnologies capable of producing chemicals from renewable resources. Microbial electrosynthesis (MES) is an emerging technology in which electrotrophic microorganisms utilize electrons from a cathode and CO₂ to produce multi-carbon compounds. To reach industrial application, clearer insights into the interactions between underlying biological, electrochemical, and physicochemical processes are required. Although individual parameters have been widely studied, identifying the most influential factors and their interactions remains challenging. This study applies design of experiments (DoE) and mixed linear regression modeling (MLRM) to examine the influence of pH, CO₂ and H₂ partial pressures, acetic acid concentration, and the addition of tungsten and selenium on the production spectrum in biofilm-driven MES. The developed DoE-MLRM approach highlights the key role of pH and CO₂ availability in supporting carbon fixation and acetate production, while the trace metals selenium and tungsten mostly promote chain elongation.