Examining the game-changing possibilities of explainable machine learning techniques, this
study explores the fast-growing area of biochar production prediction. The paper …

Modern machine learning (ML) techniques are making inroads in every aspect of renewable
energy for optimization and model prediction. The effective utilization of ML techniques for …

Biomass and organic residues are increasingly recognized as valuable resources for
bioenergy production. Lignocellulosic biomass offers sustainable alternatives to fossil fuels …

Pyrolysis is an efficient thermochemical conversion process, but accurate prediction of yield
and properties of biochar presents a significant challenge. Three prominent ensemble …

Recent research has extensively focused on 2D materials such as graphene oxide (GO) and
MXene due to their intriguing properties, significantly advancing nanotechnology and …

Alternative fuels derived from organic matter like biomass can be a viable solution in the
present scenario of increasing greenhouse gases. In the present study, waste food and …

The impact of feedstock type, pyrolysis conditions, and post-pyrolysis modifications on the
physicochemical properties of biochar has not been systematically evaluated. To this, a …

Biomass pyrolysis is a sustainable process for generating biochar from agricultural waste,
though it is generally energy-intensive and time-consuming. To address this issue, the …

Underground hydrogen storage (UHS) critically relies on cushion gas to maintain pressure
balance during injection and withdrawal cycles, prevent excessive water inflow, and expand …

Renewable energy research has become significant in the modern period owing to
escalating prices of fossil fuels and the pressing need to reduce greenhouse gas emissions …