A review on utilization of wood biomass as a sustainable precursor for activated carbon production and application
Activated carbon has been an ideal material for the separation of a variety of chemical
pollutants. Its extensive use is limited due to the cost of production, which has triggered the …
pollutants. Its extensive use is limited due to the cost of production, which has triggered the …
Comprehensive review on machine learning methodologies for modeling dye removal processes in wastewater
A wide range of dyes are being disposed in water bodies from several industrial runoff and
the quantity is rapidly increasing over the years. From an environmental safety point of view …
the quantity is rapidly increasing over the years. From an environmental safety point of view …
Insights into the adsorption of pharmaceuticals and personal care products (PPCPs) on biochar and activated carbon with the aid of machine learning
The science-informed design of 'green'carbonaceous materials (eg, biochar and activated
carbon) with high removal capacity of recalcitrant organic contaminants (eg …
carbon) with high removal capacity of recalcitrant organic contaminants (eg …
Synthesis of metal-organic framework hybrid nanocomposites based on GO and CNT with high adsorption capacity for dye removal
In this study, zeolitic imidazolate framework (ZIF-8) as a metal-organic framework (MOF) and
its hybrid nanocomposites based on graphene oxide (GO) and carbon nanotubes (CNTs) …
its hybrid nanocomposites based on graphene oxide (GO) and carbon nanotubes (CNTs) …
The application of machine learning methods for prediction of metal sorption onto biochars
The adsorption of six heavy metals (lead, cadmium, nickel, arsenic, copper, and zinc) on 44
biochars were modeled using artificial neural network (ANN) and random forest (RF) based …
biochars were modeled using artificial neural network (ANN) and random forest (RF) based …
The state of art on the prediction of efficiency and modeling of the processes of pollutants removal based on machine learning
N Taoufik, W Boumya, M Achak, H Chennouk… - Science of the Total …, 2022 - Elsevier
During the last few years, important advances have been made in big data exploration,
complex pattern recognition and prediction of complex variables. Machine learning (ML) …
complex pattern recognition and prediction of complex variables. Machine learning (ML) …
Applications of artificial neural networks for adsorption removal of dyes from aqueous solution: a review
AM Ghaedi, A Vafaei - Advances in colloid and interface science, 2017 - Elsevier
Artificial neural networks (ANNs) have been widely applied for the prediction of dye
adsorption during the last decade. In this paper, the applications of ANN methods, namely …
adsorption during the last decade. In this paper, the applications of ANN methods, namely …
Activated carbon loaded with Ni-Co-S nanoparticle for superior adsorption capacity of antibiotics and dye from wastewater: kinetics and isotherms
Activated carbon (AC) was synthesized using inexpensive rice husk and was subsequently
loaded with Ni-Co-S (NCS) nanoparticle by a simple and efficient method with very high …
loaded with Ni-Co-S (NCS) nanoparticle by a simple and efficient method with very high …
Ti3C2Tx/ZIF-67 hybrid nanocomposite as a highly effective adsorbent for Pb (II) removal from water: Synthesis and DFT calculations
The efficient elimination of heavy metal ions including Pb (II) from aqueous solutions, which
provide serious risks for the human and environment, by various adsorbents has received …
provide serious risks for the human and environment, by various adsorbents has received …
A systematic and critical review on development of machine learning based-ensemble models for prediction of adsorption process efficiency
The development of machine learning-based ensemble models for the prediction of complex
processes with non-linear nature (such as adsorption) has been remarkably advanced over …
processes with non-linear nature (such as adsorption) has been remarkably advanced over …