Topology optimization is a powerful method for designing optimal structures within a given design domain, applicable not only to physical systems but also to systems involving chemical reactions. This study employs entropy generation analysis in nonequilibrium thermodynamics as a metric to evaluate optimization results in conjunction with topology optimization. To enhance our understanding of the relationship between topology optimization and entropy generation analysis, exact solutions were derived in a simple 0D case. Nevertheless, solving the partial differential equations associated with topology optimization can be computationally intensive and time-consuming. This study proposed an alternative approach that bypassed the need for optimization methods by introducing reasonable assumptions, thereby reducing the computational effort required. By assuming a linear distribution of species concentration, the proposed approach yielded comparable performance to that achieved by optimization methods. This research contributes to streamlining the design process of electrochemical devices and reducing the computational burden associated with optimization.