This case study describes how AI enabled rapid polymer screening to accelerate sustainable product innovation. Faced with growing demand for green materials, the customer needed to evaluate new eco‑friendly ingredients while meeting strict thermal performance targets. Traditional polymer design relied on costly simulations, synthesis, and testing, slowing progress. Using an AI‑driven workflow, the team predicted thermal properties for more than 2,500 novel polymer candidates within five months. The approach significantly reduced experimental effort, identified promising formulations faster, and demonstrated how AI can streamline materials discovery while maintaining performance requirements.

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