Machine learning (ML) and deep learning (DL) are a subset of artificial intelligence (AI) that
can automatically learn from data and can perform tasks such as predictions and decision …

In the process industries, the flammable and explosive hazards of aerosols receive less
attention and have less understanding as compared to gases and dust clouds. Numerous …

In onshore hazardous liquid transmission pipelines, corrosion-induced incidents are
potentially significant hazard to people, property and environment. Therefore, several …

In this paper, we propose an innovative machine learning approach for predicting
overpressure wave propagation generated by Boiling Liquid Expanding Vapor Explosion …

The power transformer analysis focused internal fault identification is important for the
energy efficiency in all the countries, the partial discharge is one of the main failure modes, it …

Ionic liquids (ILs) can be used as capturing acidic gases that damage the environment. By
establishing a quantitative structure–property relationship (QSPR) model of the IL structure …

Surface-enhanced Raman spectroscopy (SERS) is a powerful tool for molecule
identification. However, profiling complex samples remains a challenge because SERS …

Improving the flame retardancy of polymeric materials used in engineering applications is an
increasingly important strategy for limiting fire hazards. However, the wide variety of flame …

Flammable and explosive hazards, which have been well studied, are major safety concerns
in industrial processes. However, the liquid aerosolization phenomenon, which increases …

Data driven material research is a hot topic in the cross field of artificial intelligence and
materials science. The core of new material prediction is to find the relationship between …