Abstract Machine learning algorithms have emerged as an effective and popular decision-
making tool for solving complicated engineering problems and challenges. Although …

Flame retardants are currently used in a wide range of industry sectors for saving lives and
property by mitigating fire hazards. The growing fire safety requirements for materials boost …

Abstract Carbon Capture, Utilization, and Storage (CCUS) is an emerging industry in
response to climate change. With this, more pipelines are being built to transport CO 2 to …

This study proposed an approach utilizing machine learning (ML) to accelerate the design of
organic flame retardants (FRs) for epoxy resins (EPs), avoiding the limitations of traditional …

In 2019, we introduced Flame Retardancy Index (FRI) as a universal dimensionless index
for the classification of flame-retardant polymer materials (Polymers, 2019, 11 (3), 407). FRI …

With increasing the practical applications of polymeric materials, surging demands for the
high-performance flame-retardant polymer composites are obvious. Accurately predicting …

Data-driven methods or computational techniques have opened new paradigms for the
rational design of materials. The introduction of specific groups could largely enhance anti …

Within the toolbox of click chemistry, the utilization of thiol-ene reactions for polymer
synthesis and modification is a current area of intense attention. Thiol-ene click reactions are …

This state‐of‐the‐art review is geared towards elucidating the molecular understanding of
the carbon‐based flame‐retardant mechanisms for polymers via holistic characterisation …

Beyond addressing technological demands, the integration of machine learning (ML) into
human societies has also promoted sustainability through the adoption of digitalized …