Department of Applied Mathematics, University of Colorado Boulder
Model Selection & Bioelectrochemical Systems
Microbial electrolysis cells (MECs) are devices that produce hydrogen from renewable organic matter, such as wastewater. These devices require less energy input than water electrolysis and have greater efficiency than fermentative hydrogen production. We present a sensitivity and bifurcation analysis of a differential-algebraic equation (DAE) to study microbial competition and MEC operation. We will also discuss model selection methods, particularly a data-driven discovery method known as sparse identification of nonlinear dynamical systems (SINDy).