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 …

This comprehensive review investigates the multifaceted applications of machine learning in
materials research across six key dimensions, redefining the field's boundaries. It explains …

Increased water shortage due to industrialization and population increase requires
immediate action to address water contamination. Using dimethyl sulfate as a common …

In this study, superior carbon nanotubes (CNT) were chemically modified with itaconic acid
(IA) and a polyaniline (PANI) composite was formed and used to remove methylene blue …

This research focuses on predicting the adsorbed amount of N2, O2, and N2O on carbon
molecular sieve and activated carbon using the artificial neural network (ANN) approach …

In textile products, color plays an influential role in changing fashion trends. The main
challenge in dyeing processes is the achievement of the desired color output (CIELab value) …

Dyes rejected by various industries are one of the major hazardous pollutants to be
quantified. It is therefore necessary to remove the dye before discharging it into the main …

Abstract Machine learning (ML) is an evolving scientific field of advanced statistical models
and algorithms that are developed to imitate human intelligence by learning from data. In …

To meet sustainable development criteria, this paper deals with the possible utilization of
solid waste materials generated from single and multiple successive processing of sugar …

Artificial intelligence can learn, infer, and make intelligent decisions. One of the main
advantages of artificial intelligence is that by extracting patterns and learning from data, it …