Industry 4.0

Smart controls and modified plasticizing systems help stabilize recyclate injection molding despite variations in viscosity and feedstock.

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

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.

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

Advanced printing technologies from CubiCure and Supernova are redefining additive manufacturing with high‑viscosity photopolymer resins.

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.

Engineers leverage thermotropic LCE phase transitions to power prosthetics, overcoming rigid motor constraints with flexible actuation.

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