Artificial Intelligence

Engineers use machine learning algorithms to map polymer degradation, replacing physical trials with precise predictive models for industrial extrusion pipelines.

Engineers automate the manufacturing of artificial muscles by printing electroactive PVC gels and thermomechanical shape-memory polymers.

Designing high-performance polymeric coatings requires balancing multiple formulation variables that interact in complex and often unpredictable ways.

AI is helping researchers design sustainable flame-retardant biodegradable composites faster by optimizing fire performance, strength, and material efficiency.

Virtual injection molding training using digital twins improves skills, cuts costs, and reduces material waste.

Packaging design embraces imperfection, using messy typography and human flaws to counter AI-driven aesthetics and build consumer trust.

AI-driven reinforcement learning enables polymer design optimized for performance and manufacturability.

Advancements in biotechnology highlight how engineered microbial catalysts can recycle plastic waste in vivo.

A newly developed, open-access tool helps plastic recyclers pinpoint appropriate market applications.

AI-aided polyurethane simulation reduces modeling time from days to seconds. Digital material twins optimize tool design and predict foaming behavior.