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The utilization of bio-based technology for energy has piqued researchers' curiosity around the world. As a result, bioethanol fermentation has been a hot topic of research for many scientists since it uses less energy and chemicals, produces fewer harmful by-products and emissions, and has environmentally favorable applications. The modeling and simulations of one-dimensional product and substrate inhibitions for sorghum, maize, and cassava extracts are discussed in this paper. Because it provides an edge over other methodologies, mechanistic modeling techniques are used. Models of substrate and product inhibitions in one dimension (1-D) are constructed. These 1-D models are then confirmed using parameter estimates before being employed in the work's simulations. For each dynamic model constructed, model fitness coefficients (α) are calculated. For the product, the exponential inhibition model, sorghum extract data has the best model fitness coefficient (α = 0.4088), for product sudden stop inhibition model and cassava extract data gives the best model fitness coefficient (   $$\alpha $$  α = 0.4417) for product exponential model. The projected yield increases for substrate exponential inhibition with sorghum extract data, substrate linear inhibition with maize extract data, and substrate linear inhibition with cassava extract data are 74%, 27%, and 25%, respectively. This unique framework has offered the industry a wide choice of kinetics models to choose from to alleviate inhibitions in fermentation systems and maximize yield and productivity in the bioethanol fermentation process. Article Highlights The modeling of inhibitions namely linear, sudden stop, and exponential in batch fermentation processes are presented in this article. Model fitness coefficient analysis showed the product as a primary inhibitor and substrate as a secondary inhibitor during the process The cassava and maize processes described linear inhibition model and sorghum fermentation showed exponential product inhibition model.

Theoretical formulations and simulations of one-dimensional inhibition kinetics of ethanologenic microorganisms in batch fermenters