Knowledge-Based Extraction for Inverse Design of Optical Thin-Films

In this paper, we've developed an inverse design framework for optical thin-films assisted by Generative Pre-trained Transformers (GPT). As a Large Language Models (LLMs)-powered tool, this creates an integrated platform for users to perform various functions related to inverse design on thin-films using an accessible and unique natural language interface via the assistant tool. With the consultant tool, users can query important design information and receive relevant answers to enhance the design knowledge of optical thin-films. This platform proves capable of speeding up design of thin-film structures compared to traditional ways and can also save many hours for repeated knowledge querying. The developed platform significantly reduces the resources and time (~3 x) for designers in developing optical thin-films to reach an optimal design. This will allow the thin-films' applications to be brought to the market faster and with increased efficiency.