Case Study: a leading glass manufacturer accelerates materials research and improves optical and mechanical performance with Citrine Informatics

Leading Glass Manufacturer Company finds 23 better-performing materials in 18 weeks with Citrine Informatics

A leading glass manufacturer faced the challenge of optimizing both optical and mechanical properties in a new material while adhering to strict manufacturability constraints. With tens of thousands of potential candidates but only two that initially met all criteria, they partnered with Citrine Informatics and used the Citrine Platform to enable a data-driven, AI-enabled approach to their R&D.

Using the Citrine Platform, the customer implemented a sequential learning process where machine learning models were iteratively trained and improved. This approach allowed them to identify 23 higher-performing candidate materials in just 18 weeks, requiring only 81 samples to be tested. Citrine Informatics' solution provided new insight for strategic direction and delivered a reusable AI model that later reduced processing parameter set up time by 50%.

Leading Glass Manufacturer Company