In the recent decades, with rapid development in computing power and algorithms, machine
learning (ML) has exhibited its enormous potential in new polymer discovery. Herein, the …

Biomaterials often have subtle properties that ultimately drive their bespoke performance.
Given this nuanced structure–function behavior, the standard scientific approach of one …

The forward screening and reverse design of drug molecules, inorganic molecules, and
polymers with enhanced properties are vital for accelerating the transition from laboratory …

Two-dimensional (2D) materials have intriguing physical and chemical properties, which
exhibit promising applications in the fields of electronics, optoelectronics, as well as energy …

Establishing the structure–property relationship by machine learning (ML) models is
extremely valuable for accelerating the molecular design of polymers. However, existing ML …

The use of machine learning (ML) models to screen new materials is becoming increasingly
common as they accelerate material discovery and increase sustainability. In this work, the …

Here we report a thermoset shape memory polymer-based syntactic foam inherently
integrated with flame retardancy, good mechanical properties, excellent shape memory …

Thermomechanical constitutive modeling is essential for shape memory polymers (SMPs) to
be used in engineering structures and devices. However, the classical method of deriving …

Improving the fireproof performance of polymers is crucial for ensuring human safety and
enabling future space colonization. However, the complexity of the mechanisms for flame …

There have been many new developments since the first edition of this book was published
back in 2015. These can be summarized as follows: integration of multiple properties into …