The recent regulations pertaining to the circular economy have unlocked new prospects for
researchers. In contrast to the unsustainable models associated with the linear economy …

Predicting the heavy metals adsorption performance from contaminated water is a major
environment-associated topic, demanding information on different machine learning and …

Microplastics (MPs) are ubiquitously distributed in freshwater systems and they can
determine the environmental fate of organic pollutants (OPs) via sorption interaction …

Detoxifying ecologically persistent dyes is vital for environmental and human well-being.
Herein, crabshell waste is transformed into porous carbon (CB900) through pyrolysis …

The application of machine learning (ML) is promising to solve the difficulty of predicting the
adsorption of various organic pollutants on carbonaceous materials. This study highlights …

The flow-field reconstruction of a rotating detonation combustor (RDC) is essential to
understand the stability mechanism and performance of rotating detonation engines. This …

Removing hazardous substances like azo dyes and nitrophenols from drinking water is
essential for maintaining human health since these substances occur naturally in the …

Montmorillonite, as a natural mineral adsorption material that has high research value in
water pollution treatment. However, the adsorption capacity varies depending on the type of …

The majority of pharmaceuticals are found in the environment as mixtures. However, a
significant amount of these therapeutic compounds cannot be completely metabolized by …

Many researchers have examined the benefits of machine learning (ML) algorithms in
geothermal drilling, especially for predicting the rate of penetration (ROP) of drilling …