Application of modern approaches to the synthesis of biohydrogen from organic waste

Hydrogen production with the use of biological processes and renewable feedstock may be considered an economical and sustainable alternative fuel. The high calorific value and zero emission in the production of biohydrogen make it the best possible source for energy security and environmental sustainability. Solar energy, microorganisms, and feedstock such as organic waste and lignocellulosic biomasses of different feedstock are the only requirements of biohydrogen production along with specific environmental conditions for the growth of microorganisms. Hydrogen is also named as ‘fuel of the future’. This study presents different pathways of biohydrogen production. Because of breakthroughs in R&D, biohydrogen has been elevated to the status of a viable biofuel for the future. However, significant problems such as the cost of preprocessing, oxygen-hypersensitive enzymes, a lack of uniform light illumination for photobiological processes, and other expenses requiring intensification process limits are faced throughout the biohydrogen production process. Despite concerns regarding nanoparticle (NP) toxicity at higher concentrations, proper NP concentrations may improve hydrogen production dramatically by dissolving the substrates for bacterial hydrogen transformation. The data-driven Machine Learning (ML) model allows for quick response approximation for fermentative biohydrogen production while accounting for non-linear interactions between input variables. Scaling up biohydrogen production for future commercial-scale applications requires combining cost-benefit evaluations and life cycle effects with machine learning.