This study explores why large-scale biogas plants are not widely installed in India despite the wealth of biomass resources. The methodology includes an extensive literature review and surveyed biogas experts in different sectors, such as private, pu...
Aerobic Granular Sludge (AGS) has advantages over Activated sludge (AS) but faces challenges with long granulation periods. In this study, a novel grey-box model is devised to optimize the cultivation of AGS to shorten the formation time. This model ...
Cellulose and hemicellulose are key cross-linked carbohydrates affecting bioethanol production in maize stalks. Traditional wet chemical methods for their detection are labor-intensive, highlighting the need for high-throughput techniques. This study...
Filamentous fungi's secondary metabolites (SMs) possess significant application owing to their distinct structure and diverse bioactivities, yet their restricted yield levels often hinder further research and application. The study developed a respon...
This paper presents an inverse design methodology that utilizes artificial intelligence (AI)-driven experiments to optimize the chemoenzymatic epoxidation of soyabean oil using hydrogen peroxide and lipase (Novozym 435). First, experiments are conduc...
Photosynthetic biohybrid systems (PBSs) composed of semiconductor-microbial hybrids provide a novel approach for converting light into chemical energy. However, comprehending the intricate interactions between materials and microbes that lead to PBSs...
Dissolved organic matter (DOM) is essential in biological treatment, yet its specific roles remain incompletely understood. This study introduces a machine learning (ML) framework to interpret DOM biodegradability in the anaerobic digestion (AD) of s...
The amounts of gases emitted from composting are key to evaluating global warming potential (GWP). However, few methods can accurately predict the quantities of relevant gas emissions. In this study, three developed machine-learning models were used ...
In this study, four machine learning (ML) prediction models were developed to predict and optimize the production performance of caproic acid based on substrates, products, and process parameters. The XGBoost outperformed others, with a high R of 0.9...
This article reveals the basic laws of straw supercritical water gasification (SCWG) and provides basic experimental data for the effective utilization of straw. The paper studied the impact of three operational conditions on the production of high-c...