Artificial neural networks (ANNs) are a method of machine learning (ML) that is now widely
used in physics, chemistry, and material science. ANN can learn from data to identify …

For the first time, a novel hybrid machine learning model named the least-squares support
vector machine-arithmetic optimization algorithm (LSSVM-AOA) was proposed. The …

In this research, a biohybrid nanocomposite (BHNC) reinforced with graphene (GF), multi-
walled carbon nanotube (MWCNT), silicon carbide (SiC), and modified palm oil (MPO) has …

Ethanolic ionic liquid (IL) solutions, containing different 1-n-butyl-3-methylimidazolium
chloride (C 4 MImCl) concentrations were used to modify the surface of commercial …

Cotton is one of the most important fibers used in the textile industry. The dyeing of cotton
with synthetic anionic dyes consumes large amounts of salt and alkali, which makes it a …

The molar mass of the polyurethanes (PUs)'reagents directly influences their thermal
response, affecting both the polymerization process and the enthalpy and the degree of …

Fiber-reinforced composite materials are lightweight and can withstand heavy loading
conditions. Reinforcement augments the strength of the composite material, which is …

In this study, we investigated the impact of chain extenders with varying numbers of carbon
atoms (2–6) on the thermal degradation behavior of thermoplastic polyurethanes based on …

The objective is focusing on the prediction of dielectric properties of the polypropylene
composites reinforced with banana fiber using an Artificial Neural Network (ANN). To …

Natural fibers have been widely employed in different fields as composite materials.
However, the thermal behavior of natural materials is not fully understood since the chemical …